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Ozkaya E, Kennedy P, Chen J, Bane O, Dillman JR, Jhaveri KS, Ohliger MA, Rossman PJ, Tkach JA, Doucette JT, Venkatesh SK, Ehman RL, Taouli B. Precision and Test-Retest Repeatability of Stiffness Measurement with MR Elastography: A Multicenter Phantom Study. Radiology 2024; 311:e233136. [PMID: 38742971 DOI: 10.1148/radiol.233136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background MR elastography (MRE) has been shown to have excellent performance for noninvasive liver fibrosis staging. However, there is limited knowledge regarding the precision and test-retest repeatability of stiffness measurement with MRE in the multicenter setting. Purpose To determine the precision and test-retest repeatability of stiffness measurement with MRE across multiple centers using the same phantoms. Materials and Methods In this study, three cylindrical phantoms made of polyvinyl chloride gel mimicking different degrees of liver stiffness in humans (phantoms 1-3: soft, medium, and hard stiffness, respectively) were evaluated. Between January 2021 and January 2022, phantoms were circulated between five different centers and scanned with 10 MRE-equipped clinical 1.5-T and 3-T systems from three major vendors, using two-dimensional (2D) gradient-recalled echo (GRE) imaging and/or 2D spin-echo (SE) echo-planar imaging (EPI). Similar MRE acquisition parameters, hardware, and reconstruction algorithms were used at each center. Mean stiffness was measured by a single observer for each phantom and acquisition on a single section. Stiffness measurement precision and same-session test-retest repeatability were assessed using the coefficient of variation (CV) and the repeatability coefficient (RC), respectively. Results The mean precision represented by the CV was 5.8% (95% CI: 3.8, 7.7) for all phantoms and both sequences combined. For all phantoms, 2D GRE achieved a CV of 4.5% (95% CI: 3.3, 5.7) whereas 2D SE EPI achieved a CV of 7.8% (95% CI: 3.1, 12.6). The mean RC of stiffness measurement was 5.8% (95% CI: 3.7, 7.8) for all phantoms and both sequences combined, 4.9% (95% CI: 2.7, 7.0) for 2D GRE, and 7.0% (95% CI: 2.9, 11.2) for 2D SE EPI (all phantoms). Conclusion MRE had excellent in vitro precision and same-session test-retest repeatability in the multicenter setting when similar imaging protocols, hardware, and reconstruction algorithms were used. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Tang in this issue.
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Affiliation(s)
- Efe Ozkaya
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Paul Kennedy
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Jun Chen
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Octavia Bane
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Jonathan R Dillman
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Kartik S Jhaveri
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Michael A Ohliger
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Phillip J Rossman
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Jean A Tkach
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - John T Doucette
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Sudhakar K Venkatesh
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Richard L Ehman
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Bachir Taouli
- From the BioMedical Engineering and Imaging Institute (E.O., P.K., O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health (J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R., S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, Toronto, Canada (K.S.J.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, Calif (M.A.O.); and Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
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Al-Mubarak H, Bane O, Gillingham N, Kyriakakos C, Abboud G, Cuevas J, Gonzalez J, Meilika K, Horowitz A, Huang HHV, Daza J, Fauveau V, Badani K, Viswanath SE, Taouli B, Lewis S. Characterization of renal masses with MRI-based radiomics: assessment of inter-package and inter-observer reproducibility in a prospective pilot study. Abdom Radiol (NY) 2024:10.1007/s00261-024-04212-z. [PMID: 38467854 DOI: 10.1007/s00261-024-04212-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 01/17/2024] [Accepted: 01/17/2024] [Indexed: 03/13/2024]
Abstract
OBJECTIVES To evaluate radiomics features' reproducibility using inter-package/inter-observer measurement analysis in renal masses (RMs) based on MRI and to employ machine learning (ML) models for RM characterization. METHODS 32 Patients (23M/9F; age 61.8 ± 10.6 years) with RMs (25 renal cell carcinomas (RCC)/7 benign masses; mean size, 3.43 ± 1.73 cm) undergoing resection were prospectively recruited. All patients underwent 1.5 T MRI with T2-weighted (T2-WI), diffusion-weighted (DWI)/apparent diffusion coefficient (ADC), and pre-/post-contrast-enhanced T1-weighted imaging (T1-WI). RMs were manually segmented using volume of interest (VOI) on T2-WI, DWI/ADC, and T1-WI pre-/post-contrast imaging (1-min, 3-min post-injection) by two independent observers using two radiomics software packages for inter-package and inter-observer assessments of shape/histogram/texture features common to both packages (104 features; n = 26 patients). Intra-class correlation coefficients (ICCs) were calculated to assess inter-observer and inter-package reproducibility of radiomics measurements [good (ICC ≥ 0.8)/moderate (ICC = 0.5-0.8)/poor (ICC < 0.5)]. ML models were employed using reproducible features (between observers and packages, ICC > 0.8) to distinguish RCC from benign RM. RESULTS Inter-package comparisons demonstrated that radiomics features from T1-WI-post-contrast had the highest proportion of good/moderate ICCs (54.8-58.6% for T1-WI-1 min), while most features extracted from T2-WI, T1-WI-pre-contrast, and ADC exhibited poor ICCs. Inter-observer comparisons found that radiomics measurements from T1-WI pre/post-contrast and T2-WI had the greatest proportion of features with good/moderate ICCs (95.3-99.1% T1-WI-post-contrast 1-min), while ADC measurements yielded mostly poor ICCs. ML models generated an AUC of 0.71 [95% confidence interval = 0.67-0.75] for diagnosis of RCC vs. benign RM. CONCLUSION Radiomics features extracted from T1-WI-post-contrast demonstrated greater inter-package and inter-observer reproducibility compared to ADC, with fair accuracy for distinguishing RCC from benign RM. CLINICAL RELEVANCE Knowledge of reproducibility of MRI radiomics features obtained on renal masses will aid in future study design and may enhance the diagnostic utility of radiomics models for renal mass characterization.
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Affiliation(s)
- Haitham Al-Mubarak
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, New York, NY, USA
| | - Nicolas Gillingham
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai West, New York, NY, 10019, USA
| | - Christopher Kyriakakos
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, New York, NY, USA
| | - Ghadi Abboud
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, New York, NY, USA
| | - Jordan Cuevas
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, New York, NY, USA
| | - Janette Gonzalez
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, New York, NY, USA
| | - Kirolos Meilika
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amir Horowitz
- Precision Immunology Institute/Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hsin-Hui Vivien Huang
- Department of Population Sciences and Health Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jorge Daza
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute/Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Valentin Fauveau
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ketan Badani
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Satish E Viswanath
- Department of Biomedical Engineering, School of Medicine, Case School of Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of Radiology, Case School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, New York, NY, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, Box 1234, New York, NY, 10029, USA.
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3
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El Homsi M, Bane O, Fauveau V, Hectors S, Vietti Violi N, Sylla P, Ko HB, Cuevas J, Carbonell G, Nehlsen A, Vanguri R, Viswanath S, Jambawalikar S, Shaish H, Taouli B. Prediction of locally advanced rectal cancer response to neoadjuvant chemoradiation therapy using volumetric multiparametric MRI-based radiomics. Abdom Radiol (NY) 2024; 49:791-800. [PMID: 38150143 DOI: 10.1007/s00261-023-04128-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/06/2023] [Accepted: 11/12/2023] [Indexed: 12/28/2023]
Abstract
PURPOSE To assess the role of pretreatment multiparametric (mp)MRI-based radiomic features in predicting pathologic complete response (pCR) of locally advanced rectal cancer (LARC) to neoadjuvant chemoradiation therapy (nCRT). METHODS This was a retrospective dual-center study including 98 patients (M/F 77/21, mean age 60 years) with LARC who underwent pretreatment mpMRI followed by nCRT and total mesorectal excision or watch and wait. Fifty-eight patients from institution 1 constituted the training set and 40 from institution 2 the validation set. Manual segmentation using volumes of interest was performed on T1WI pre-/post-contrast, T2WI and diffusion-weighted imaging (DWI) sequences. Demographic information and serum carcinoembryonic antigen (CEA) levels were collected. Shape, 1st and 2nd order radiomic features were extracted and entered in models based on principal component analysis used to predict pCR. The best model was obtained using a k-fold cross-validation method on the training set, and AUC, sensitivity and specificity for prediction of pCR were calculated on the validation set. RESULTS Stage distribution was T3 (n = 79) or T4 (n = 19). Overall, 16 (16.3%) patients achieved pCR. Demographics, MRI TNM stage, and CEA were not predictive of pCR (p range 0.59-0.96), while several radiomic models achieved high diagnostic performance for prediction of pCR (in the validation set), with AUCs ranging from 0.7 to 0.9, with the best model based on high b-value DWI demonstrating AUC of 0.9 [95% confidence intervals: 0.67, 1], sensitivity of 100% [100%, 100%], and specificity of 81% [66%, 96%]. CONCLUSION Radiomic models obtained from pre-treatment MRI show good to excellent performance for the prediction of pCR in patients with LARC, superior to clinical parameters and CEA. A larger study is needed for confirmation of these results.
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Affiliation(s)
- Maria El Homsi
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, USA.
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York av, New York, USA.
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Valentin Fauveau
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefanie Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Naik Vietti Violi
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Patricia Sylla
- Department of Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Huai-Bin Ko
- Department of Pathology, Molecular and Cell Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pathology, Columbia University Medical Center, New York, NY, USA
| | - Jordan Cuevas
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Guillermo Carbonell
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Virgen de la Arrixaca University Clinical Hospital, University of Murcia, Murcia, Spain
| | - Anthony Nehlsen
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rami Vanguri
- Department of Epidemiology & Biostatistics, Columbia University Medical Center, New York, NY, USA
| | - Satish Viswanath
- Department of Radiology, Case Western University, Cleveland, OH, USA
| | - Sachin Jambawalikar
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Hiram Shaish
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Bachir Taouli
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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4
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Bane O, Lewis SC, Lim RP, Carney BW, Shah A, Fananapazir G. Contemporary and Emerging MRI Strategies for Assessing Kidney Allograft Complications: Arterial Stenosis and Parenchymal Injury, From the AJR Special Series on Imaging of Fibrosis. AJR Am J Roentgenol 2024; 222:e2329418. [PMID: 37315018 PMCID: PMC11006565 DOI: 10.2214/ajr.23.29418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
MRI plays an important role in the evaluation of kidney allografts for vascular complications as well as parenchymal insults. Transplant renal artery stenosis, the most common vascular complication of kidney transplant, can be evaluated by MRA using gadolinium and nongadolinium contrast agents as well as by unenhanced MRA techniques. Parenchymal injury occurs through a variety of pathways, including graft rejection, acute tubular injury, BK polyomavirus infection, drug-induced interstitial nephritis, and pyelonephritis. Investigational MRI techniques have sought to differentiate among these causes of dysfunction as well as to assess the degree of interstitial fibrosis or tubular atrophy (IFTA)-the common end pathway for all of these processes-which is currently evaluated by invasively obtained core biopsies. Some of these MRI sequences have shown promise in not only assessing the cause of parenchymal injury but also assessing IFTA noninvasively. This review describes current clinically used MRI techniques and previews promising investigational MRI techniques for assessing complications of kidney grafts.
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Affiliation(s)
- Octavia Bane
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Sara C Lewis
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ruth P Lim
- Department of Radiology and Department of Surgery, University of Melbourne, Austin Health, Melbourne, Australia
| | - Benjamin W Carney
- Department of Radiology, University of California Davis Medical Center, 4860 Y St, Ste 3100, Sacramento, CA 95816
| | - Amar Shah
- Department of Radiology, Mayo Clinic Arizona, Phoenix, AZ
| | - Ghaneh Fananapazir
- Department of Radiology, University of California Davis Medical Center, 4860 Y St, Ste 3100, Sacramento, CA 95816
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5
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Bane O, Seeliger E, Cox E, Stabinska J, Bechler E, Lewis S, Hickson LJ, Francis S, Sigmund E, Niendorf T. Renal MRI: From Nephron to NMR Signal. J Magn Reson Imaging 2023; 58:1660-1679. [PMID: 37243378 PMCID: PMC11025392 DOI: 10.1002/jmri.28828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 05/11/2023] [Accepted: 05/12/2023] [Indexed: 05/28/2023] Open
Abstract
Renal diseases pose a significant socio-economic burden on healthcare systems. The development of better diagnostics and prognostics is well-recognized as a key strategy to resolve these challenges. Central to these developments are MRI biomarkers, due to their potential for monitoring of early pathophysiological changes, renal disease progression or treatment effects. The surge in renal MRI involves major cross-domain initiatives, large clinical studies, and educational programs. In parallel with these translational efforts, the need for greater (patho)physiological specificity remains, to enable engagement with clinical nephrologists and increase the associated health impact. The ISMRM 2022 Member Initiated Symposium (MIS) on renal MRI spotlighted this issue with the goal of inspiring more solutions from the ISMRM community. This work is a summary of the MIS presentations devoted to: 1) educating imaging scientists and clinicians on renal (patho)physiology and demands from clinical nephrologists, 2) elucidating the connection of MRI parameters with renal physiology, 3) presenting the current state of leading MR surrogates in assessing renal structure and functions as well as their next generation of innovation, and 4) describing the potential of these imaging markers for providing clinically meaningful renal characterization to guide or supplement clinical decision making. We hope to continue momentum of recent years and introduce new entrants to the development process, connecting (patho)physiology with (bio)physics, and conceiving new clinical applications. We envision this process to benefit from cross-disciplinary collaboration and analogous efforts in other body organs, but also to maximally leverage the unique opportunities of renal physiology. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Octavia Bane
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute, New York City, New York, USA
| | - Erdmann Seeliger
- Institute of Translational Physiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Eleanor Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Julia Stabinska
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Eric Bechler
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sara Lewis
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - LaTonya J Hickson
- Division of Nephrology and Hypertension, Mayo Clinic, Jacksonville, Florida, USA
| | - Sue Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Eric Sigmund
- Bernard and Irene Schwartz Center for Biomedical Imaging Center for Advanced Imaging Innovation and Research (CAI2R), New York University Langone Health, New York City, New York, USA
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
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6
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Bhuiyan EH, Ozkaya E, Kennedy P, Del Hoyo JL, Achkar BE, Thung S, Lewis S, Bane O, Taouli B. Magnetic resonance elastography for noninvasive detection of liver fibrosis: is there an added value of 3D acquisition? Abdom Radiol (NY) 2023; 48:3420-3429. [PMID: 37700185 DOI: 10.1007/s00261-023-04036-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 08/22/2023] [Accepted: 08/24/2023] [Indexed: 09/14/2023]
Abstract
PURPOSE (1) Assess the diagnostic performance of liver 3D magnetic resonance elastography (MRE) parameters (including stiffness, storage/loss modulus and damping ratio) compared to liver stiffness measured with 2D MRE for noninvasive detection of advanced liver fibrosis (F3-F4) and cirrhosis (F4) in patients with chronic liver disease. (2) Assess the value of serum markers (FIB-4) in detecting advanced liver fibrosis and cirrhosis in the same patients. METHODS This was a single center, prospective IRB-approved cross-sectional study that included 49 patients (M/F: 23/26, mean age 50.8 y) with chronic liver disease and concomitant liver biopsy. MRE was acquired at 1.5T using a spin echo-EPI sequence. The following parameters were measured: liver stiffness using 2D MRE (LS-2D) and 3D MRE parameters (LS-3D, liver storage, loss modulus and damping ratio). The Mann-Whitney U test, ROC curve analysis, Spearman correlation and logistic regression were performed to evaluate diagnostic performance of MRE parameters and FIB-4. RESULTS LS-2D and LS-3D had similar diagnostic performance for diagnosis of F3-F4, with AUCs of 0.87 and 0.88, sensitivity of 0.71 and 0.81, specificity of 0.89 for both. For diagnosis of F4, LS-2D and LS-3D had similar performance with AUCs of 0.81 for both, sensitivity of 0.75 and 0.83, and specificity of 0.84 and 0.73, respectively. Additional 3D parameters (storage modulus, loss modulus, damping ratio) had variable performance, with AUC range of 0.59-0.78 for F3-F4; and 0.52-0.70 for F4. FIB-4 had lower diagnostic performance, with AUCs of 0.66 for F3-F4, and 0.68 for F4. CONCLUSION Our study shows no added value of 3D MRE compared to 2D MRE for detection of advanced fibrosis and cirrhosis, while FIB-4 had lower diagnostic performance.
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Affiliation(s)
- Enamul H Bhuiyan
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Efe Ozkaya
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paul Kennedy
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Juan Lloret Del Hoyo
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Bassam El Achkar
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Swan Thung
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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7
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Said D, Carbonell G, Stocker D, Hectors S, Vietti-Violi N, Bane O, Chin X, Schwartz M, Tabrizian P, Lewis S, Greenspan H, Jégou S, Schiratti JB, Jehanno P, Taouli B. Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks. Eur Radiol 2023; 33:6020-6032. [PMID: 37071167 DOI: 10.1007/s00330-023-09613-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 02/09/2023] [Accepted: 02/26/2023] [Indexed: 04/19/2023]
Abstract
OBJECTIVE To assess the performance of convolutional neural networks (CNNs) for semiautomated segmentation of hepatocellular carcinoma (HCC) tumors on MRI. METHODS This retrospective single-center study included 292 patients (237 M/55F, mean age 61 years) with pathologically confirmed HCC between 08/2015 and 06/2019 and who underwent MRI before surgery. The dataset was randomly divided into training (n = 195), validation (n = 66), and test sets (n = 31). Volumes of interest (VOIs) were manually placed on index lesions by 3 independent radiologists on different sequences (T2-weighted imaging [WI], T1WI pre-and post-contrast on arterial [AP], portal venous [PVP], delayed [DP, 3 min post-contrast] and hepatobiliary phases [HBP, when using gadoxetate], and diffusion-weighted imaging [DWI]). Manual segmentation was used as ground truth to train and validate a CNN-based pipeline. For semiautomated segmentation of tumors, we selected a random pixel inside the VOI, and the CNN provided two outputs: single slice and volumetric outputs. Segmentation performance and inter-observer agreement were analyzed using the 3D Dice similarity coefficient (DSC). RESULTS A total of 261 HCCs were segmented on the training/validation sets, and 31 on the test set. The median lesion size was 3.0 cm (IQR 2.0-5.2 cm). Mean DSC (test set) varied depending on the MRI sequence with a range between 0.442 (ADC) and 0.778 (high b-value DWI) for single-slice segmentation; and between 0.305 (ADC) and 0.667 (T1WI pre) for volumetric-segmentation. Comparison between the two models showed better performance in single-slice segmentation, with statistical significance on T2WI, T1WI-PVP, DWI, and ADC. Inter-observer reproducibility of segmentation analysis showed a mean DSC of 0.71 in lesions between 1 and 2 cm, 0.85 in lesions between 2 and 5 cm, and 0.82 in lesions > 5 cm. CONCLUSION CNN models have fair to good performance for semiautomated HCC segmentation, depending on the sequence and tumor size, with better performance for the single-slice approach. Refinement of volumetric approaches is needed in future studies. KEY POINTS • Semiautomated single-slice and volumetric segmentation using convolutional neural networks (CNNs) models provided fair to good performance for hepatocellular carcinoma segmentation on MRI. • CNN models' performance for HCC segmentation accuracy depends on the MRI sequence and tumor size, with the best results on diffusion-weighted imaging and T1-weighted imaging pre-contrast, and for larger lesions.
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Affiliation(s)
- Daniela Said
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Clínica Universidad de los Andes, Santiago, Chile
| | - Guillermo Carbonell
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, University Hospital Virgen de La Arrixaca, Murcia, Spain
| | - Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Stefanie Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Naik Vietti-Violi
- Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xing Chin
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Myron Schwartz
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Parissa Tabrizian
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA
| | - Hayit Greenspan
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | | | | | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA.
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8
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Laothamatas I, Al Mubarak H, Reddy A, Wax R, Badani K, Taouli B, Bane O, Lewis S. Multiparametric MRI of Solid Renal Masses: Principles and Applications of Advanced Quantitative and Functional Methods for Tumor Diagnosis and Characterization. J Magn Reson Imaging 2023. [PMID: 37052601 DOI: 10.1002/jmri.28718] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 04/14/2023] Open
Abstract
Solid renal masses (SRMs) are increasingly detected and encompass both benign and malignant masses, with renal cell carcinoma (RCC) being the most common malignant SRM. Most patients with SRMs will undergo management without a priori pathologic confirmation. There is an unmet need to noninvasively diagnose and characterize RCCs, as significant variability in clinical behavior is observed and a wide range of differing management options exist. Cross-sectional imaging modalities, including magnetic resonance imaging (MRI), are increasingly used for SRM characterization. Multiparametric (mp) MRI techniques can provide insight into tumor biology by probing different physiologic/pathophysiologic processes noninvasively. These include sequences that probe tissue microstructure, including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and T1 relaxometry; oxygen metabolism (blood oxygen level dependent [BOLD-MRI]); as well as vascular flow and perfusion (dynamic contrast-enhanced MRI [DCE-MRI] and arterial spin labeling [ASL]). In this review, we will discuss each mpMRI method in terms of its principles, roles, and discuss the results of human studies for SRM assessment. Future validation of these methods may help to enable a personalized management approach for patients with SRM in the emerging era of precision medicine. EVIDENCE LEVEL: 5. TECHNICAL EFFICACY: 2.
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Affiliation(s)
- Indira Laothamatas
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Haitham Al Mubarak
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Arthi Reddy
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Rebecca Wax
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ketan Badani
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Octavia Bane
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Sara Lewis
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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9
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Daza J, Salomé B, Okhawere K, Bane O, Meilika KN, Korn TG, Qi J, Xe H, Patel M, Brody R, Kim-Schulze S, Sfakianos JP, Lewis S, Rich JM, Zuluaga L, Badani KK, Horowitz A. Urine supernatant reveals a signature that predicts survival in clear-cell renal cell carcinoma. BJU Int 2023. [PMID: 36797809 DOI: 10.1111/bju.15989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
OBJECTIVE To profile the cell-free urine supernatant and plasma of a small cohort of clear-cell renal cell carcinoma (ccRCC) patients by measuring the relative concentrations of 92 proteins related to inflammation. Using The Cancer Genome Atlas (TCGA), we then performed a targeted mRNA analysis of genes encoding the above proteins and defined their effects on overall survival (OS). SUBJECTS/PATIENTS AND METHODS Samples were collected prospectively from ccRCC patients. A multiplex proximity extension assay was used to measure the concentrations of 92 inflammation-related proteins in cell-free urine supernatants and plasma. Transcriptomic and clinical information from ccRCC patients was obtained from TCGA. Unsupervised clustering and differential protein expression analyses were performed on protein concentration data. Targeted mRNA analysis on genes encoding significant differentially expressed proteins was performed using TCGA. Backward stepwise regression analyses were used to build a nomogram. The performance of the nomogram and clinical benefit was assessed by discrimination and calibration, and a decision curve analysis, respectively. RESULTS Unsupervised clustering analysis revealed inflammatory signatures in the cell-free urine supernatant of ccRCC patients. Backward stepwise regressions using TCGA data identified transcriptomic risk factors and risk groups associated with OS. A nomogram to predict 2-year and 5-year OS was developed using these risk factors. The decision curve analysis showed that our model was associated with a net benefit improvement compared to the treat-all/none strategies. CONCLUSION We defined four novel biomarkers using proteomic and transcriptomic data that distinguish severity of prognosis in ccRCC. We showed that these biomarkers can be used in a model to predict 2-year and 5-year OS in ccRCC across different tumour stages. This type of analysis, if validated in the future, provides non-invasive prognostic information that could inform either management or surveillance strategies for patients.
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Affiliation(s)
- Jorge Daza
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bérengère Salomé
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kennedy Okhawere
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Octavia Bane
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kirolos N Meilika
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Talia G Korn
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jingjing Qi
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hui Xe
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manishkumar Patel
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rachel Brody
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Seunghee Kim-Schulze
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John P Sfakianos
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Lewis
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jordan M Rich
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Laura Zuluaga
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ketan K Badani
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amir Horowitz
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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10
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Bane O, Stocker D, Kennedy P, Hectors SJ, Bollache E, Schnell S, Schiano T, Thung S, Fischman A, Markl M, Taouli B. 4D flow MRI in abdominal vessels: prospective comparison of k-t accelerated free breathing acquisition to standard respiratory navigator gated acquisition. Sci Rep 2022; 12:19886. [PMID: 36400918 PMCID: PMC9674613 DOI: 10.1038/s41598-022-23864-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 11/07/2022] [Indexed: 11/19/2022] Open
Abstract
Volumetric phase-contrast magnetic resonance imaging with three-dimensional velocity encoding (4D flow MRI) has shown utility as a non-invasive tool to examine altered blood flow in chronic liver disease. Novel 4D flow MRI pulse sequences with spatio-temporal acceleration can mitigate the long acquisition times of standard 4D flow MRI, which are an impediment to clinical adoption. The purpose of our study was to demonstrate feasibility of a free-breathing, spatio-temporal (k-t) accelerated 4D flow MRI acquisition for flow quantification in abdominal vessels and to compare its image quality, flow quantification and inter-observer reproducibility with a standard respiratory navigator-gated 4D flow MRI acquisition. Ten prospectively enrolled patients (M/F: 7/3, mean age = 58y) with suspected portal hypertension underwent both 4D flow MRI acquisitions. The k-t accelerated acquisition was approximately three times faster (3:11 min ± 0:12 min/9:17 min ± 1:41 min, p < 0.001) than the standard respiratory-triggered acquisition. Vessel identification agreement was substantial between acquisitions and observers. Average flow had substantial inter-sequence agreement in the portal vein and aorta (CV < 15%) and poorer agreement in hepatic and splenic arteries (CV = 11-38%). The k-t accelerated acquisition recorded reduced velocities in small arteries and reduced splenic vein flow. Respiratory gating combined with increased acceleration and spatial resolution are needed to improve flow measurements in these vessels.
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Affiliation(s)
- Octavia Bane
- grid.59734.3c0000 0001 0670 2351Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY 10029 USA ,grid.59734.3c0000 0001 0670 2351BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Daniel Stocker
- grid.59734.3c0000 0001 0670 2351Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY 10029 USA ,grid.59734.3c0000 0001 0670 2351BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Paul Kennedy
- grid.59734.3c0000 0001 0670 2351Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY 10029 USA ,grid.59734.3c0000 0001 0670 2351BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Stefanie J. Hectors
- grid.59734.3c0000 0001 0670 2351Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY 10029 USA ,grid.59734.3c0000 0001 0670 2351BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Emilie Bollache
- grid.16753.360000 0001 2299 3507Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL USA ,grid.7429.80000000121866389Laboratoire d’Imagerie Biomédicale, INSERM, Paris, France
| | - Susanne Schnell
- grid.16753.360000 0001 2299 3507Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL USA ,grid.5603.0Department of Medical Physics, Universität Greifswald, Greifswald, Germany
| | - Thomas Schiano
- grid.59734.3c0000 0001 0670 2351Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Swan Thung
- grid.59734.3c0000 0001 0670 2351Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Aaron Fischman
- grid.59734.3c0000 0001 0670 2351Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY 10029 USA
| | - Michael Markl
- grid.16753.360000 0001 2299 3507Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL USA ,grid.16753.360000 0001 2299 3507Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL USA
| | - Bachir Taouli
- grid.59734.3c0000 0001 0670 2351Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY 10029 USA ,grid.59734.3c0000 0001 0670 2351BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
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11
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Altinmakas E, Bane O, Hectors SJ, Issa R, Carbonell G, Abboud G, Schiano TD, Thung S, Fischman A, Kelly MD, Friedman SL, Kennedy P, Taouli B. Performance of native and gadoxetate-enhanced liver and spleen T 1 mapping for noninvasive diagnosis of clinically significant portal hypertension: preliminary results. Abdom Radiol (NY) 2022; 47:3758-3769. [PMID: 36085378 DOI: 10.1007/s00261-022-03645-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/03/2022] [Accepted: 08/03/2022] [Indexed: 01/18/2023]
Abstract
PURPOSE In this preliminary study, our aim was to assess the utility of quantitative native-T1 (T1-pre), iron-corrected T1 (cT1) of the liver/spleen and T1 mapping of the liver obtained during hepatobiliary phase (T1-HBP) post-gadoxetate disodium, compared to spleen size/volume and APRI (aspartate aminotransferase-to-platelet ratio index) for noninvasive diagnosis of clinically significant portal hypertension [CSPH, defined as hepatic venous pressure gradient (HVPG) ≥ 10 mm Hg]. METHODS Forty-nine patients (M/F: 27/22, mean age 53y) with chronic liver disease, HVPG measurement and MRI were included. Breath-held T1 and cT1 measurements were obtained using an inversion recovery Look-Locker sequence and a T2* corrected modified Look-Locker sequence, respectively. Liver T1-pre (n = 49), spleen T1 (obtained pre-contrast, n = 47), liver and spleen cT1 (both obtained pre-contrast, n = 30), liver T1-HBP (obtained 20 min post gadoxetate disodium injection, n = 36) and liver T1 uptake (ΔT1, n = 36) were measured. Spleen size/volume and APRI were also obtained. Spearman correlation coefficients were used to assess the correlation between each of liver/spleen T1/cT1 parameters, spleen size/volume and APRI with HVPG. ROC analysis was performed to determine the performance of measured parameters for diagnosis of CSPH. RESULTS There were 12/49 (24%) patients with CSPH. Liver T1-pre (r = 0.287, p = 0.045), liver T1-HBP (r = 0.543, p = 0.001), liver ΔT1 (r = - 0.437, p = 0.008), spleen T1 (r = 0.311, p = 0.033) and APRI (r = 0.394, p = 0.005) were all significantly correlated with HVPG, while liver cT1, spleen cT1 and spleen size/volume were not. The highest AUCs for the diagnosis of CSPH were achieved with liver T1-HBP, liver ΔT1 and spleen T1: 0.881 (95%CI 0.76-1.0, p = 0.001), 0.852 (0.72-0.98, p = 0.002) and 0.781 (0.60-0.95, p = 0.004), respectively. CONCLUSION Our preliminary results demonstrate the potential of liver T1 mapping obtained during HBP post gadoxetate disodium for the diagnosis of CSPH. These results require further validation.
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Affiliation(s)
- Emre Altinmakas
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Koc University School of Medicine, Istanbul, Turkey
| | - Octavia Bane
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefanie J Hectors
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rayane Issa
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA
| | - Guillermo Carbonell
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Virgen de La Arrixaca University Clinical Hospital, University of Murcia, Murcia, Spain
| | - Ghadi Abboud
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas D Schiano
- Icahn School of Medicine at Mount Sinai, Recanati/Miller Transplantation Institute, New York, NY, USA
| | - Swan Thung
- Department of Pathology, Molecular and Cell Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aaron Fischman
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA
| | | | - Scott L Friedman
- Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paul Kennedy
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York, NY, 10029, USA. .,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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12
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Kennedy P, Stocker D, Carbonell G, Said D, Bane O, Hectors S, Abboud G, Cuevas J, Bolster BD, Friedman SL, Lewis S, Schiano T, Bhattacharya D, Fischman A, Thung S, Taouli B. MR elastography outperforms shear wave elastography for the diagnosis of clinically significant portal hypertension. Eur Radiol 2022; 32:8339-8349. [PMID: 35727321 PMCID: PMC10149092 DOI: 10.1007/s00330-022-08935-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 05/11/2022] [Accepted: 05/30/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES Portal hypertension (PH) is associated with complications such as ascites and esophageal varices and is typically diagnosed through invasive hepatic venous pressure gradient (HVPG) measurement, which is not widely available. In this study, we aim to assess the diagnostic performance of 2D/3D MR elastography (MRE) and shear wave elastography (SWE) measures of liver and spleen stiffness (LS and SS) and spleen volume, to noninvasively diagnose clinically significant portal hypertension (CSPH) using HVPG measurement as the reference. METHODS In this prospective study, patients with liver disease underwent 2D/3D MRE and SWE of the liver and spleen, as well as HVPG measurement. The correlation between MRE/SWE measures of LS/SS and spleen volume with HVPG was assessed. ROC analysis was used to determine the utility of MRE, SWE, and spleen volume for diagnosing CSPH. RESULTS Thirty-six patients (M/F 22/14, mean age 55 ± 14 years) were included. Of the evaluated parameters, 3D MRE SS had the strongest correlation with HVPG (r = 0.686, p < 0.001), followed by 2D MRE SS (r = 0.476, p = 0.004). 3D MRE SS displayed the best performance for diagnosis of CSPH (AUC = 0.911) followed by 2D MRE SS (AUC = 0.845) and 3D MRE LS (AUC = 0.804). SWE SS showed poor performance for diagnosis of CSPH (AUC = 0.583) while spleen volume was a fair predictor (AUC = 0.738). 3D MRE SS was significantly superior to SWE LS/SS (p ≤ 0.021) for the diagnosis of CSPH. CONCLUSION SS measured with 3D MRE outperforms SWE for the diagnosis of CSPH. SS appears to be a useful biomarker for assessing PH severity. These results need further validation. KEY POINTS • Spleen stiffness measured with 2D and 3D MR elastography correlates significantly with hepatic venous pressure gradient measurement. • Spleen stiffness measured with 3D MR elastography demonstrates excellent performance for the diagnosis of clinically significant portal hypertension (AUC 0.911). • Spleen stiffness measured with 3D MR elastography outperforms liver and spleen stiffness measured with shear wave elastography for diagnosis of clinically significant portal hypertension.
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Affiliation(s)
- Paul Kennedy
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Guillermo Carbonell
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Universidad de Murcia, Murcia, Spain
| | - Daniela Said
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Universidad de los Andes, Santiago, Chile
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefanie Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ghadi Abboud
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jordan Cuevas
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Scott L Friedman
- Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Schiano
- Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dipankar Bhattacharya
- Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aaron Fischman
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Swan Thung
- Department of Pathology, Molecular and Cell Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA.
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13
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Vietti Violi N, Gnerre J, Law A, Hectors S, Bane O, Doucette J, Abboud G, Kim E, Schwartz M, Fiel MI, Taouli B. Assessment of HCC response to Yttrium-90 radioembolization with gadoxetate disodium MRI: correlation with histopathology. Eur Radiol 2022; 32:6493-6503. [PMID: 35380226 DOI: 10.1007/s00330-022-08732-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/19/2022] [Accepted: 03/11/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND AND AIMS Transarterial 90Y radioembolization (TARE) is increasingly being used for hepatocellular carcinoma (HCC) treatment. However, tumor response assessment after TARE may be challenging. We aimed to assess the diagnostic performance of gadoxetate disodium MRI for predicting complete pathologic necrosis (CPN) of HCC treated with TARE, using histopathology as the reference standard. METHODS This retrospective study included 48 patients (M/F: 36/12, mean age: 62 years) with HCC treated by TARE followed by surgery with gadoxetate disodium MRI within 90 days of surgery. Two radiologists evaluated tumor response using RECIST1.1, mRECIST, EASL, and LI-RADS-TR criteria and evaluated the percentage of necrosis on subtraction during late arterial, portal venous, and hepatobiliary phases (AP/PVP/HBP). Statistical analysis included inter-reader agreement, correlation between radiologic and pathologic percentage of necrosis, and prediction of CPN using logistic regression and ROC analyses. RESULTS Histopathology demonstrated 71 HCCs (2.8 ± 1.7 cm, range: 0.5-7.5 cm) including 42 with CPN, 22 with partial necrosis, and 7 without necrosis. EASL and percentage of tumor necrosis on subtraction at the AP/PVP were independent predictors of CPN (p = 0.02-0.03). Percentage of necrosis, mRECIST, EASL, and LI-RADS-TR had fair to good performance for diagnosing CPN (AUCs: 0.78 - 0.83), with a significant difference between subtraction and LI-RADS-TR for reader 2, and in specificity between subtraction and other criteria for both readers (p-range: 0.01-0.04). Radiologic percentage of necrosis was significantly correlated to histopathologic degree of tumor necrosis (r = 0.66 - 0.8, p < 0.001). CONCLUSIONS Percentage of tumor necrosis on subtraction and EASL criteria were significant independent predictors of CPN in HCC treated with TARE. Image subtraction should be considered for assessing HCC response to TARE when using MRI. KEY POINTS • Percentage of tumor necrosis on image subtraction and EASL criteria are significant independent predictors of complete pathologic necrosis in hepatocellular carcinoma treated with90Y radioembolization. • Subtraction, mRECIST, EASL, and LI-RADS-TR have fair to good performance for diagnosing complete pathologic necrosis in hepatocellular carcinoma treated with90Y radioembolization.
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Affiliation(s)
- Naik Vietti Violi
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine Mount Sinai, New York, NY, USA.,Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Jeffrey Gnerre
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Amy Law
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Stefanie Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine Mount Sinai, New York, NY, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine Mount Sinai, New York, NY, USA
| | - John Doucette
- Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ghadi Abboud
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine Mount Sinai, New York, NY, USA
| | - Edward Kim
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Myron Schwartz
- The Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - M Isabel Fiel
- Department of Pathology, Molecular and Cell Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine Mount Sinai, New York, NY, USA. .,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA.
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14
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Carbonell G, Kennedy P, Bane O, Kirmani A, El Homsi M, Stocker D, Said D, Mukherjee P, Gevaert O, Lewis S, Hectors S, Taouli B. Precision of MRI radiomics features in the liver and hepatocellular carcinoma. Eur Radiol 2022; 32:2030-2040. [PMID: 34564745 DOI: 10.1007/s00330-021-08282-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/12/2021] [Accepted: 08/17/2021] [Indexed: 01/08/2023]
Abstract
OBJECTIVES To assess the precision of MRI radiomics features in hepatocellular carcinoma (HCC) tumors and liver parenchyma. METHODS The study population consisted of 55 patients, including 16 with untreated HCCs, who underwent two repeat contrast-enhanced abdominal MRI exams within 1 month to evaluate: (1) test-retest repeatability using the same MRI system (n = 28, 10 HCCs); (2) inter-platform reproducibility between different MRI systems (n = 27, 6 HCCs); (3) inter-observer reproducibility (n = 16, 16 HCCs). Shape and 1st- and 2nd-order radiomics features were quantified on pre-contrast T1-weighted imaging (WI), T1WI portal venous phase (pvp), T2WI, and ADC (apparent diffusion coefficient), on liver regions of interest (ROIs) and HCC volumes of interest (VOIs). Precision was assessed by calculating intraclass correlation coefficient (ICC), concordance correlation coefficient (CCC), and coefficient of variation (CV). RESULTS There was moderate to excellent test-retest repeatability of shape and 1st- and 2nd-order features for all sequences in HCCs (ICC: 0.53-0.99; CV: 3-29%), and moderate to good test-retest repeatability of 1st- and 2nd-order features for T1WI sequences, and 2nd-order features for T2WI in the liver (ICC: 0.53-0.73; CV: 12-19%). There was poor inter-platform reproducibility for all features and sequences, except for shape and 1st-order features on T1WI in HCCs (CCC: 0.58-0.99; CV: 3-15%). Good to excellent inter-observer reproducibility was found for all features and sequences in HCCs (CCC: 0.80-0.99; CV: 4-15%) and moderate to good for liver (CCC: 0.45-0.86; CV: 6-25%). CONCLUSIONS MRI radiomics features have acceptable repeatability in the liver and HCC when using the same MRI system and across readers but have low reproducibility across MR systems, except for shape and 1st-order features on T1WI. Data must be interpreted with caution when performing multiplatform radiomics studies. KEY POINTS • MRI radiomics features have acceptable repeatability when using the same MRI system but less reproducible when using different MRI platforms. • MRI radiomics features extracted from T1 weighted-imaging show greater stability across exams than T2 weighted-imaging and ADC. • Inter-observer reproducibility of MRI radiomics features was found to be good in HCC tumors and acceptable in liver parenchyma.
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Affiliation(s)
- Guillermo Carbonell
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, University Hospital Virgen de La Arrixaca, Murcia, Spain
| | - Paul Kennedy
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ammar Kirmani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Maria El Homsi
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Daniela Said
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Universidad de los Andes, Santiago, Chile
| | | | - Olivier Gevaert
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefanie Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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15
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de Boer A, Villa G, Bane O, Bock M, Cox EF, Dekkers IA, Eckerbom P, Fernández‐Seara MA, Francis ST, Haddock B, Hall ME, Hall Barrientos P, Hermann I, Hockings PD, Lamb HJ, Laustsen C, Lim RP, Morris DM, Ringgaard S, Serai SD, Sharma K, Sourbron S, Takehara Y, Wentland AL, Wolf M, Zöllner FG, Nery F, Caroli A. Consensus-Based Technical Recommendations for Clinical Translation of Renal Phase Contrast MRI. J Magn Reson Imaging 2022; 55:323-335. [PMID: 33140551 PMCID: PMC9291014 DOI: 10.1002/jmri.27419] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 10/15/2020] [Accepted: 10/16/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Phase-contrast (PC) MRI is a feasible and valid noninvasive technique to measure renal artery blood flow, showing potential to support diagnosis and monitoring of renal diseases. However, the variability in measured renal blood flow values across studies is large, most likely due to differences in PC-MRI acquisition and processing. Standardized acquisition and processing protocols are therefore needed to minimize this variability and maximize the potential of renal PC-MRI as a clinically useful tool. PURPOSE To build technical recommendations for the acquisition, processing, and analysis of renal 2D PC-MRI data in human subjects to promote standardization of renal blood flow measurements and facilitate the comparability of results across scanners and in multicenter clinical studies. STUDY TYPE Systematic consensus process using a modified Delphi method. POPULATION Not applicable. SEQUENCE FIELD/STRENGTH Renal fast gradient echo-based 2D PC-MRI. ASSESSMENT An international panel of 27 experts from Europe, the USA, Australia, and Japan with 6 (interquartile range 4-10) years of experience in 2D PC-MRI formulated consensus statements on renal 2D PC-MRI in two rounds of surveys. Starting from a recently published systematic review article, literature-based and data-driven statements regarding patient preparation, hardware, acquisition protocol, analysis steps, and data reporting were formulated. STATISTICAL TESTS Consensus was defined as ≥75% unanimity in response, and a clear preference was defined as 60-74% agreement among the experts. RESULTS Among 60 statements, 57 (95%) achieved consensus after the second-round survey, while the remaining three showed a clear preference. Consensus statements resulted in specific recommendations for subject preparation, 2D renal PC-MRI data acquisition, processing, and reporting. DATA CONCLUSION These recommendations might promote a widespread adoption of renal PC-MRI, and may help foster the set-up of multicenter studies aimed at defining reference values and building larger and more definitive evidence, and will facilitate clinical translation of PC-MRI. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Anneloes de Boer
- Department of RadiologyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Giulia Villa
- Department of BioengineeringIstituto di Ricerche Farmacologiche Mario Negri IRCCSBergamoItaly
| | - Octavia Bane
- Biomedical Engineering and Imaging Institute/RadiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Michael Bock
- Department of Radiology ‐ Medical Physics, Medical CenterUniversity of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
| | - Eleanor F. Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - Ilona A. Dekkers
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Per Eckerbom
- Department of Surgical SciencesUppsala UniversityUppsalaSweden
| | | | - Susan T. Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - Bryan Haddock
- Department of Clinical Physiology, Nuclear Medicine and PET, RigshospitaletCopenhagen University HospitalCopenhagenDenmark
| | - Michael E. Hall
- Department of MedicineUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | | | - Ingo Hermann
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
| | | | - Hildo J. Lamb
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Christoffer Laustsen
- Department of Clinical Medicine, MR Research CentreAarhus UniversityAarhusDenmark
| | - Ruth P. Lim
- Departments of Radiology, Surgery and MedicineThe University of MelbourneParkvilleVictoriaAustralia
- Department of RadiologyAustin HealthHeidelbergVictoriaAustralia
| | - David M. Morris
- Centre for Inflammation ResearchUniversity of Edinburgh, Edinburgh BioquarterEdinburghUK
| | - Steffen Ringgaard
- Department of Clinical Medicine, MR Research CentreAarhus UniversityAarhusDenmark
| | - Suraj D. Serai
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Kanishka Sharma
- Department of Imaging, Infection, Immunity and Cardiovascular DiseaseThe University of SheffieldSheffieldUK
| | - Steven Sourbron
- Department of Imaging, Infection, Immunity and Cardiovascular DiseaseThe University of SheffieldSheffieldUK
| | - Yasuo Takehara
- Department of Fundamental Development for Advanced Low Invasive Diagnostic ImagingNagoya University, Graduate School of MedicineNagoyaJapan
| | | | - Marcos Wolf
- High Field MR Center, Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
| | - Frank G. Zöllner
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
| | - Fabio Nery
- Developmental Imaging and Biophysics SectionUCL Great Ormond Street Institute of Child HealthLondonUK
| | - Anna Caroli
- Department of BioengineeringIstituto di Ricerche Farmacologiche Mario Negri IRCCSBergamoItaly
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16
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Stocker D, King MJ, El Homsi M, Carbonell G, Bane O, Cuevas J, Liu Q, Cho J, Doucette JT, Greenstein AJ, Colombel JF, Harpaz N, Taouli B. Luminal Narrowing Alone Allows an Accurate Diagnosis of Crohn's Disease Small Bowel Strictures at Cross-Sectional Imaging. J Crohns Colitis 2021; 15:1009-1018. [PMID: 33319236 DOI: 10.1093/ecco-jcc/jjaa256] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND AIMS Current consensus recommendations define small bowel strictures [SBS] in Crohn's disease [CD] on imaging as luminal narrowing with unequivocal upstream bowel dilation. The aim of this study was to [1] evaluate the performance of cross-sectional imaging for SBS diagnosis in CD using luminal narrowing with upstream SB dilation and luminal narrowing with or without upstream dilation, and [2] compare the diagnostic performance of computed tomography [CT] and magnetic resonance enterography [MRE] for SBS diagnosis. METHODS In total, 111 CD patients [81 with pathologically confirmed SBS, 30 controls] who underwent CT and/or MRE were assessed. Two radiologists [R1, R2] blinded to pathology findings independently assessed the presence of luminal narrowing and upstream SB dilation. Statistical analysis was performed for [1] luminal narrowing with or without SB upstream dilation ['possible SBS'], and [2] luminal narrowing with upstream SB dilation ≥3 cm ['definite SBS']. RESULTS Sensitivity for detecting SBS was significantly higher using 'possible SBS' [R1, 82.1%; R2, 77.9%] compared to 'definite SBS' [R1, 62.1%; R2, 65.3%; p < 0.0001] with equivalent specificity [R1, 96.7%; R2, 93.3%; p > 0.9]. Using the criterion 'possible SBS', sensitivity/specificity were equivalent between CT [R1, 87.3%/93.3%; R2, 83.6%/86.7%] and MRE [R1, 75.0%/100%; R2: 70.0%/100%]. Using the criterion 'definite SBS', CT showed significantly higher sensitivity [78.2%] compared to MRE [40.0%] for R1 but not R2 with similar specificities [CT, 86.7-93.3%; MRE, 100%]. CONCLUSION SBS can be diagnosed using luminal narrowing alone without the need for upstream dilation. CT and MRE show similar diagnostic performance for SBS diagnosis using luminal narrowing with or without upstream dilation.
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Affiliation(s)
- Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael J King
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Maria El Homsi
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Guillermo Carbonell
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Virgen de la Arrixaca University Clinical Hospital, University of Murcia, Murcia, Spain
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jordan Cuevas
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Qingqing Liu
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Judy Cho
- Charles Bronfman Institute for Personalized Medicine, Departments of Genetics and Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John T Doucette
- Division of Biostatistics, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Jean-Frederic Colombel
- The Dr Henry D Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Noam Harpaz
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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17
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Stocker D, Hectors S, Bane O, Vietti-Violi N, Said D, Kennedy P, Cuevas J, Cunha GM, Sirlin CB, Fowler KJ, Lewis S, Taouli B. Dynamic contrast-enhanced MRI perfusion quantification in hepatocellular carcinoma: comparison of gadoxetate disodium and gadobenate dimeglumine. Eur Radiol 2021; 31:9306-9315. [PMID: 34043055 DOI: 10.1007/s00330-021-08068-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 04/22/2021] [Accepted: 05/11/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVES (1) To assess the quality of the arterial input function (AIF) during dynamic contrast-enhanced (DCE) MRI of the liver and (2) to quantify perfusion parameters of hepatocellular carcinoma (HCC) and liver parenchyma during the first 3 min post-contrast injection with DCE-MRI using gadoxetate disodium compared to gadobenate dimeglumine (Gd-BOPTA) in different patient populations. METHODS In this prospective study, we evaluated 66 patients with 83 HCCs who underwent DCE-MRI, using gadoxetate disodium (group 1, n = 28) or Gd-BOPTA (group 2, n = 38). AIF qualitative and quantitative features were assessed. Perfusion parameters (based on the initial 3 min post-contrast) were extracted in tumours and liver parenchyma, including model-free parameters (time-to-peak enhancement (TTP), time-to-washout) and modelled parameters (arterial flow (Fa), portal venous flow (Fp), total flow (Ft), arterial fraction, mean transit time (MTT), distribution volume (DV)). In addition, lesion-to-liver contrast ratios (LLCRs) were measured. Fisher's exact tests and Mann-Whitney U tests were used to compare the two groups. RESULTS AIF quality, modelled and model-free perfusion parameters in HCC were similar between the 2 groups (p = 0.054-0.932). Liver parenchymal flow was lower and liver enhancement occurred later in group 1 vs group 2 (Fp, p = 0.002; Ft, p = 0.001; TTP, MTT, all p < 0.001), while there were no significant differences in tumour LLCR (max. positive LLCR, p = 0.230; max. negative LLCR, p = 0.317). CONCLUSION Gadoxetate disodium provides comparable AIF quality and HCC perfusion parameters compared to Gd-BOPTA during dynamic phases. Despite delayed and decreased liver enhancement with gadoxetate disodium, LLCRs were equivalent between contrast agents, indicating similar tumour conspicuity. KEY POINTS • Arterial input function quality, modelled, and model-free dynamic parameters measured in hepatocellular carcinoma are similar in patients receiving gadoxetate disodium or gadobenate dimeglumine during the first 3 min post injection. • Gadoxetate disodium and gadobenate dimeglumine show similar lesion-to-liver contrast ratios during dynamic phases in patients with HCC. • There is lower portal and lower total hepatic flow and longer hepatic mean transit time and time-to-peak with gadoxetate disodium compared to gadobenate dimeglumine.
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Affiliation(s)
- Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Stefanie Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Naik Vietti-Violi
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Daniela Said
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Universidad de los Andes, Santiago, Chile
| | - Paul Kennedy
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Jordan Cuevas
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Guilherme M Cunha
- Liver Imaging Group, Radiology, University of California-San Diego, San Diego, CA, USA
| | - Claude B Sirlin
- Liver Imaging Group, Radiology, University of California-San Diego, San Diego, CA, USA
| | - Kathryn J Fowler
- Liver Imaging Group, Radiology, University of California-San Diego, San Diego, CA, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA.
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18
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Garteiser P, Bane O, Doblas S, Friedli I, Hectors S, Pagé G, Van Beers BE, Waterton JC. Experimental Protocols for MRI Mapping of Renal T 1. Methods Mol Biol 2021; 2216:383-402. [PMID: 33476012 DOI: 10.1007/978-1-0716-0978-1_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023]
Abstract
The water proton longitudinal relaxation time, T1, is a common and useful MR parameter in nephrology research. Here we provide three step-by-step T1-mapping protocols suitable for different types of nephrology research. Firstly, we provide a single-slice 2D saturation recovery protocol suitable for studies of global pathology, where whole-kidney coverage is unnecessary. Secondly, we provide an inversion recovery type imaging protocol that may be optimized for specific kidney disease applications. Finally, we also provide imaging protocol for small animal kidney imaging in a clinical scanner.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concept and experimental procedure.
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Affiliation(s)
- Philippe Garteiser
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris and AP-HP, Paris, France
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sabrina Doblas
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris and AP-HP, Paris, France
| | - Iris Friedli
- Antaros Medical, BioVenture Hub, Mölndal, Sweden
| | - Stefanie Hectors
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gwenaël Pagé
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris and AP-HP, Paris, France
| | - Bernard E Van Beers
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris and AP-HP, Paris, France
| | - John C Waterton
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
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19
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Hectors SJ, Garteiser P, Doblas S, Pagé G, Van Beers BE, Waterton JC, Bane O. MRI Mapping of Renal T 1: Basic Concept. Methods Mol Biol 2021; 2216:157-169. [PMID: 33475999 DOI: 10.1007/978-1-0716-0978-1_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023]
Abstract
In renal MRI, measurement of the T1 relaxation time of water molecules may provide a valuable biomarker for a variety of pathological conditions. Due to its sensitivity to the tissue microenvironment, T1 has gained substantial interest for noninvasive imaging of renal pathology, including inflammation and fibrosis. In this chapter, we will discuss the basic concept of T1 mapping and different T1 measurement techniques and we will provide an overview of emerging preclinical applications of T1 for imaging of kidney disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.
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Affiliation(s)
- Stefanie J Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Philippe Garteiser
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris, Paris, France
| | - Sabrina Doblas
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris, Paris, France
| | - Gwenaël Pagé
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris, Paris, France
| | - Bernard E Van Beers
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris and AP-HP, Paris, France
| | - John C Waterton
- Division of Informatics Imaging & Data Sciences, Faculty of Biology Medicine & Health, Centre for Imaging Sciences, School of Health Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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20
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Kennedy P, Lewis S, Bane O, Hectors SJ, Kim E, Schwartz M, Taouli B. Early effect of 90Y radioembolisation on hepatocellular carcinoma and liver parenchyma stiffness measured with MR elastography: initial experience. Eur Radiol 2021; 31:5791-5801. [PMID: 33475773 DOI: 10.1007/s00330-020-07636-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 11/24/2020] [Accepted: 12/16/2020] [Indexed: 12/12/2022]
Abstract
OBJECTIVES To quantify hepatocellular carcinoma (HCC) and liver parenchyma stiffness using MR elastography (MRE) and serum alpha fetoprotein (AFP), before and 6 weeks (6w) after 90Y radioembolisation (RE), and to assess the value of baseline tumour and liver stiffness (TS/LS) and AFP in predicting response at 6w and 6 months (6 m). METHODS Twenty-three patients (M/F 18/5, mean age 68.3 ± 9.3 years) scheduled to undergo RE were recruited into this prospective single-centre study. Patients underwent an MRI exam at baseline and 6w following RE (range 39-47 days) which included MRE using a prototype 2D EPI sequence. TS, peritumoural LS/LS remote from the tumour, tumour size, and AFP were measured at baseline and at 6w. Treatment response was determined using mRECIST at 6w and 6 m. RESULTS MRE was technically successful in 17 tumours which were classified at 6w as complete response (CR, n = 7), partial response (PR, n = 4), and stable disease (SD, n = 6). TS and peritumoural LS were significantly increased following RE (p = 0.016, p = 0.039, respectively), while LS remote from tumour was unchanged (p = 0.245). Baseline TS was significantly lower in patients who achieved CR at 6w (p = 0.014). Baseline TS, peritumoural LS (both AUC = 0.857), and AFP (AUC = 0.798) showed fair/excellent diagnostic performance in predicting CR at 6w, but were not significant predictors of OR or CR at 6 m. CONCLUSION Our initial results suggest that HCC TS and peritumoural LS increase early after RE. Baseline TS, peritumoural LS, and AFP were all significant predictors of CR to RE at 6w. These results should be confirmed in a larger study. KEY POINTS • Magnetic resonance elastography-derived tumour stiffness and peritumoural liver stiffness increase significantly at 6 weeks post radioembolisation whereas liver stiffness remote from the tumour is unchanged. • Baseline tumour stiffness and peritumoural liver stiffness are lower in patients who achieve complete response at 6 weeks post radioembolisation. • Baseline tumour size is significantly correlated with baseline tumour stiffness.
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Affiliation(s)
- Paul Kennedy
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefanie J Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Edward Kim
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA
| | - Myron Schwartz
- Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY, 10029, USA.
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21
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Kennedy P, Bane O, Hectors SJ, Fischman A, Schiano T, Lewis S, Taouli B. Noninvasive imaging assessment of portal hypertension. Abdom Radiol (NY) 2020; 45:3473-3495. [PMID: 32926209 PMCID: PMC10124623 DOI: 10.1007/s00261-020-02729-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 08/16/2020] [Accepted: 08/30/2020] [Indexed: 02/07/2023]
Abstract
Portal hypertension (PH) is a spectrum of complications of chronic liver disease (CLD) and cirrhosis, with manifestations including ascites, gastroesophageal varices, splenomegaly, hypersplenism, hepatic hydrothorax, hepatorenal syndrome, hepatopulmonary syndrome and portopulmonary hypertension. PH can vary in severity and is diagnosed via invasive hepatic venous pressure gradient measurement (HVPG), which is considered the reference standard. Accurate diagnosis of PH and assessment of severity are highly relevant as patients with clinically significant portal hypertension (CSPH) are at higher risk for developing acute variceal bleeding and mortality. In this review, we discuss current and upcoming noninvasive imaging methods for diagnosis and assessment of severity of PH.
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Said D, Hectors SJ, Wilck E, Rosen A, Stocker D, Bane O, Beksaç AT, Lewis S, Badani K, Taouli B. Characterization of solid renal neoplasms using MRI-based quantitative radiomics features. Abdom Radiol (NY) 2020; 45:2840-2850. [PMID: 32333073 DOI: 10.1007/s00261-020-02540-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE To assess the diagnostic value of magnetic resonance imaging (MRI)-based radiomics features using machine learning (ML) models in characterizing solid renal neoplasms, in comparison/combination with qualitative radiologic evaluation. METHODS Retrospective analysis of 125 patients (mean age 59 years, 67% males) with solid renal neoplasms that underwent MRI before surgery. Qualitative (signal and enhancement characteristics) and quantitative radiomics analyses (histogram and texture features) were performed on T2-weighted imaging (WI), T1-WI pre- and post-contrast, and DWI. Mann-Whitney U test and receiver-operating characteristic analysis were used in a training set (n = 88) to evaluate diagnostic performance of qualitative and radiomics features for differentiation of renal cell carcinomas (RCCs) from benign lesions, and characterization of RCC subtypes (clear cell RCC [ccRCC] and papillary RCC [pRCC]). Random forest ML models were developed for discrimination between tumor types on the training set, and validated on an independent set (n = 37). RESULTS We assessed 104 RCCs (51 ccRCC, 29 pRCC, and 24 other subtypes) and 21 benign lesions in 125 patients. Significant qualitative and quantitative radiomics features (area under the curve [AUC] between 0.62 and 0.90) were included for ML analysis. Models with best diagnostic performance on validation sets showed AUC of 0.73 (confidence interval [CI] 0.5-0.96) for differentiating RCC from benign lesions (using combination of qualitative and radiomics features); AUC of 0.77 (CI 0.62-0.92) for diagnosing ccRCC (using radiomics features), and AUC of 0.74 (CI 0.53-0.95) for diagnosing pRCC (using qualitative features). CONCLUSION ML models incorporating MRI-based radiomics features and qualitative radiologic assessment can help characterize renal masses.
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Affiliation(s)
- Daniela Said
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Universidad de los Andes, Santiago, Chile
| | - Stefanie J Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Eric Wilck
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ally Rosen
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Long Island School of Medicine, NYU-Winthrop Hospital, Mineola, NY, USA
| | - Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute of Interventional and Diagnostic Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alp Tuna Beksaç
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ketan Badani
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Bane O, Said D, Weiss A, Stocker D, Kennedy P, Hectors SJ, Khaim R, Salem F, Delaney V, Menon MC, Markl M, Lewis S, Taouli B. 4D flow MRI for the assessment of renal transplant dysfunction: initial results. Eur Radiol 2020; 31:909-919. [PMID: 32870395 DOI: 10.1007/s00330-020-07208-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 07/07/2020] [Accepted: 08/19/2020] [Indexed: 12/26/2022]
Abstract
OBJECTIVES (1) Determine inter-observer reproducibility and test-retest repeatability of 4D flow parameters in renal allograft vessels; (2) determine if 4D flow measurements in the renal artery (RA) and renal vein (RV) can distinguish between functional and dysfunctional allografts; (3) correlate haemodynamic parameters with estimated glomerular filtration rate (eGFR), perfusion measured with dynamic contrast-enhanced MRI (DCE-MRI) and histopathology. METHODS Twenty-five prospectively recruited renal transplant patients (stable function/chronic renal allograft dysfunction, 12/13) underwent 4D flow MRI at 1.5 T. 4D flow coronal oblique acquisitions were performed in the transplant renal artery (RA) (velocity encoding parameter, VENC = 120 cm/s) and renal vein (RV) (VENC = 45 cm/s). Test-retest repeatability (n = 3) and inter-observer reproducibility (n = 10) were assessed by Cohen's kappa, coefficient of variation (CoV) and Bland-Altman statistics. Haemodynamic parameters were compared between patients and correlated to the estimated glomerular filtration rate, DCE-MRI parameters (n = 10) and histopathology from allograft biopsies (n = 15). RESULTS For inter-observer reproducibility, kappa was > 0.99 and 0.62 and CoV of flow was 12.6% and 7.8% for RA and RV, respectively. For test-retest repeatability, kappa was > 0.99 and 0.5 and CoV of flow was 27.3% and 59.4%, for RA and RV, respectively. RA (p = 0.039) and RV (p = 0.019) flow were both significantly reduced in dysfunctional allografts. Both identified chronic allograft dysfunction with good diagnostic performance (RA: AUC = 0.76, p = 0.036; RV: AUC = 0.8, p = 0.018). RA flow correlated negatively with histopathologic interstitial fibrosis score ci (ρ = - 0.6, p = 0.03). CONCLUSIONS 4D flow parameters had better repeatability in the RA than in the RV. RA and RV flow can identify chronic renal allograft dysfunction, with RA flow correlating with histopathologic interstitial fibrosis score. KEY POINTS • Inter-observer reproducibility of 4D flow measurements was acceptable in both the transplant renal artery and vein, but test-retest repeatability was better in the renal artery than in the renal vein. • Blood flow measurements obtained with 4D flow MRI in the renal artery and renal vein are significantly reduced in dysfunctional renal transplants. • Renal transplant artery flow correlated negatively with histopathologic interstitial fibrosis score.
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Affiliation(s)
- Octavia Bane
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA
| | - Daniela Said
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA
| | - Amanda Weiss
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA
| | - Daniel Stocker
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA
| | - Paul Kennedy
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA
| | - Stefanie J Hectors
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA.,Department of Radiology, Weill Cornell Medicine, New York, New York, NY, USA
| | - Rafael Khaim
- Division of Renal Medicine, Recanati Miller Transplantation Institute, ISMMS, New York, NY, USA
| | - Fadi Salem
- Department of Pathology, ISMMS, New York, NY, USA
| | - Veronica Delaney
- Division of Renal Medicine, Recanati Miller Transplantation Institute, ISMMS, New York, NY, USA
| | - Madhav C Menon
- Division of Renal Medicine, Recanati Miller Transplantation Institute, ISMMS, New York, NY, USA
| | - Michael Markl
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA
| | - Sara Lewis
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA.,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA
| | - Bachir Taouli
- Department of Radiology, Icahn School of Medicine at Mount Sinai (ISMMS), 1470 Madison Avenue, New York, NY, 10029, USA. .,BioMedical Engineering and Imaging Institute, ISMMS, New York, NY, USA.
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Hectors SJ, Lewis S, Kennedy P, Bane O, Said D, Segall M, Schwartz M, Kim E, Taouli B. Assessment of Hepatocellular Carcinoma Response to 90Y Radioembolization Using Dynamic Contrast Material-enhanced MRI and Intravoxel Incoherent Motion Diffusion-weighted Imaging. Radiol Imaging Cancer 2020; 2:e190094. [PMID: 32803165 PMCID: PMC7398117 DOI: 10.1148/rycan.2020190094] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 04/13/2020] [Accepted: 04/28/2020] [Indexed: 04/21/2023]
Abstract
PURPOSE To quantify diffusion and perfusion changes in hepatocellular carcinoma (HCC) induced by yttrium 90 (90Y) radioembolization and to assess the value of dynamic contrast material-enhanced (DCE) MRI and intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for predicting HCC response. MATERIALS AND METHODS Institutional review board approval was obtained for this prospective study (clinical trial registry NCT01871545). Twenty-four participants with HCC (mean age, 69 years ± 9 [standard deviation], 18 men) underwent multiparametric MRI, including IVIM DWI and gadoxetic acid DCE MRI before (n = 24) and 6 weeks (n = 21) after radioembolization. IVIM DWI and DCE MRI histogram parameters were quantified in HCCs and liver parenchyma. HCC response was assessed by using modified Response Evaluation Criteria in Solid Tumors at 6 weeks and 6-12 months after radioembolization. Logistic regression analysis was used to evaluate the diagnostic performance of baseline MRI and clinical parameters for prediction of response. RESULTS Twenty-five HCCs were analyzed (mean size, 3.6 cm ± 1.9). Radioembolization resulted in significantly decreased perfusion (DCE MRI arterial flow, P = .002; IVIM pseudodiffusion coefficient [D*], P = .014). Multivariate logistic regression selected combined serum α-fetoprotein and portal flow (F p ) skewness (area under the curve [AUC] = 0.924) and combined D* standard deviation and F p kurtosis (AUC = 0.916) for prediction of objective and complete response at 6 weeks, respectively. Standard deviation of DCE MRI parameter arterial fraction was selected as the optimal predictor for complete response at 6-12 months (AUC = 0.857). CONCLUSION Diffusion and perfusion MRI can be used to evaluate the response of HCC to radioembolization. Pretreatment DCE MRI histogram parameters may be useful for radioembolization treatment stratification. Supplemental material is available for this article. © RSNA, 2020.
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Kennedy P, Bane O, Hectors SJ, Gordic S, Berger M, Delaney V, Salem F, Lewis S, Menon M, Taouli B. Magnetic resonance elastography vs. point shear wave ultrasound elastography for the assessment of renal allograft dysfunction. Eur J Radiol 2020; 126:108949. [PMID: 32179424 DOI: 10.1016/j.ejrad.2020.108949] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 03/02/2020] [Accepted: 03/09/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE To investigate the utility of magnetic resonance elastography (MRE) vs. ultrasound (US) point shear wave elastography (pSWE) for the assessment of chronic renal allograft dysfunction, prediction of outcome and determine the correlation with Banff pathology scores. METHODS In this IRB approved prospective study, 27 enrolled patients with functional (n = 15) and chronic dysfunctional (n = 12) renal allografts underwent same day 2D MRE and pSWE. Histogram parameters [including mean, median, standard deviation, kurtosis and skewness] of the magnitude of the complex shear modulus (MRE) and median Young's modulus (pSWE) were measured in the cortex (MRE and pSWE) and combined corticomedullary regions (MRE). Histopathology was available for 16 patients (4 functional, 12 dysfunctional). RESULTS MRE and pSWE stiffness were not significantly different between functional and dysfunctional groups (p range 0.139-0.347). The skewness of MRE corticomedullary stiffness was significantly lower (p = 0.04) in patients with chronic dysfunction and correlated significantly with Banff histopathologic scores (range r=-0.518-0.567, p = 0.035-0.040). MRE cortical and corticomedullary mean stiffness showed strong performance in predicting graft loss/relist (AUC 0.958, p = 0.011 for both). Reliable pSWE measurements were obtained in 13 patients (48 %). pSWE stiffness did not correlate with Banff scores and did not predict outcome. CONCLUSIONS The skewness of MRE corticomedullary stiffness is sensitive to changes in chronic allograft dysfunction, while mean/median MRE renal stiffness and median US stiffness did not differentiate patients with stable function vs those with chronic renal allograft dysfunction. MRE corticomedullary mean stiffness appears to be a predictor of graft loss/relist. pSWE was not found to be a useful method for assessing renal allografts.
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Affiliation(s)
- Paul Kennedy
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, United States
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, United States
| | - Stefanie J Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, United States; Department of Radiology, Weill Cornell Medicine, United States
| | - Sonja Gordic
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, United States; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland
| | - Mark Berger
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, United States
| | - Veronica Delaney
- Division of Renal Medicine, Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, United States
| | - Fadi Salem
- Department of Pathology, Icahn School of Medicine at Mount Sinai, United States
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, United States; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, United States
| | - Madhav Menon
- Division of Renal Medicine, Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, United States
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, United States; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, United States.
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Hectors SJ, Bane O, Stocker D, Carbonell G, Lewis S, Kennedy P, Schiano TD, Thung S, Fischman A, Taouli B. Splenic T 1ρ as a noninvasive biomarker for portal hypertension. J Magn Reson Imaging 2020; 52:787-794. [PMID: 32073207 DOI: 10.1002/jmri.27087] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 01/23/2020] [Accepted: 01/24/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND There is a need for noninvasive methods for the diagnosis and monitoring of portal hypertension (PH). PURPOSE To 1) assess the correlation of liver and spleen T1 and T1ρ measurements with portal pressures in patients with chronic liver disease, and 2) to compare the diagnostic performance of the relaxation parameters with radiological assessment of PH. STUDY TYPE Prospective. SUBJECTS Twenty-five patients (M/F 16/9, mean age 56 years, range 21-78 years) undergoing portal pressure (hepatic venous pressure gradient [HVPG]) measurements. FIELD STRENGTH/SEQUENCE 1.5T abdominal MRI scan, including T1ρ and T1 mapping. ASSESSMENT Liver and spleen T1ρ and T1 , radiological PH score, and (normalized) spleen length were evaluated. STATISTICAL TESTS Spearman correlation of all MRI parameters with HVPG was assessed. The diagnostic performance of the assessed parameters for prediction of PH (HVPG ≥5 mmHg) and clinically significant PH (CSPH, HVPG ≥10 mmHg) was determined by receiver operating characteristic (ROC) analysis. RESULTS The mean HVPG measurement was 7.8 ± 5.3 mmHg (PH, n = 18 [72%] including CSPH, n = 9 [36%]). PH score, (normalized) spleen length and spleen T1ρ significantly correlated with HVPG, with the strongest correlation found for spleen T1ρ (r = 0.613, P = 0.001). Spleen T1ρ was the only parameter that showed significant diagnostic performance for assessment of PH (area under the curve [AUC] 0.817, P = 0.015) and CSPH (AUC = 0.778, P = 0.024). Normalized spleen length also showed significant diagnostic performance for prediction of CSPH, with a slightly lower AUC (= 0.764, P = 0.031). The radiological PH score, T1ρ and T1 of the liver and T1 of the spleen, did not show significant diagnostic performance for assessment of CSPH (P > 0.075). DATA CONCLUSION Spleen T1ρ showed a significant correlation with portal pressure and showed improved diagnostic performance for prediction of CSPH compared to radiological assessment. These initial results need confirmation in a larger cohort. LEVEL OF EVIDENCE 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;52:787-794.
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Affiliation(s)
- Stefanie J Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Institute of Interventional and Diagnostic Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Guillermo Carbonell
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Virgen de la Arrixaca University Clinical Hospital, University of Murcia, Murcia, Spain
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Paul Kennedy
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Thomas D Schiano
- Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Swan Thung
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Aaron Fischman
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Bane O, Mendichovszky IA, Milani B, Dekkers IA, Deux JF, Eckerbom P, Grenier N, Hall ME, Inoue T, Laustsen C, Lerman LO, Liu C, Morrell G, Pedersen M, Pruijm M, Sadowski EA, Seeliger E, Sharma K, Thoeny H, Vermathen P, Wang ZJ, Serafin Z, Zhang JL, Francis ST, Sourbron S, Pohlmann A, Fain SB, Prasad PV. Consensus-based technical recommendations for clinical translation of renal BOLD MRI. MAGMA 2020; 33:199-215. [PMID: 31768797 PMCID: PMC7021747 DOI: 10.1007/s10334-019-00802-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 10/18/2019] [Accepted: 10/22/2019] [Indexed: 01/08/2023]
Abstract
Harmonization of acquisition and analysis protocols is an important step in the validation of BOLD MRI as a renal biomarker. This harmonization initiative provides technical recommendations based on a consensus report with the aim to move towards standardized protocols that facilitate clinical translation and comparison of data across sites. We used a recently published systematic review paper, which included a detailed summary of renal BOLD MRI technical parameters and areas of investigation in its supplementary material, as the starting point in developing the survey questionnaires for seeking consensus. Survey data were collected via the Delphi consensus process from 24 researchers on renal BOLD MRI exam preparation, data acquisition, data analysis, and interpretation. Consensus was defined as ≥ 75% unanimity in response. Among 31 survey questions, 14 achieved consensus resolution, 12 showed clear respondent preference (65-74% agreement), and 5 showed equal (50/50%) split in opinion among respondents. Recommendations for subject preparation, data acquisition, processing and reporting are given based on the survey results and review of the literature. These technical recommendations are aimed towards increased inter-site harmonization, a first step towards standardization of renal BOLD MRI protocols across sites. We expect this to be an iterative process updated dynamically based on progress in the field.
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Affiliation(s)
- Octavia Bane
- BioMedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Iosif A Mendichovszky
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | - Bastien Milani
- Center for BioMedical Imaging, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ilona A Dekkers
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jean-Francois Deux
- Department of Radiology, Groupe Hospitalier Henri Mondor, Créteil, France
| | - Per Eckerbom
- Department of Radiology, Institution for Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Nicolas Grenier
- Department of Radiology, Université de Bordeaux, CHU de Bordeaux, Bordeaux, France
| | - Michael E Hall
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Tsutomu Inoue
- Department of Nephrology, Faculty of Medicine, Saitama Medical University, Saitama, Japan
| | - Christoffer Laustsen
- The MR Research Center Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Lilach O Lerman
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Chunlei Liu
- Electrical Engineering and Computer Science, and Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Glen Morrell
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Michael Pedersen
- Department of Clinical Medicine-Comparative Medicine Lab, Aarhus University Hospital, Aarhus, Denmark
| | - Menno Pruijm
- Nephrology and Hypertension Service, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Elizabeth A Sadowski
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Erdmann Seeliger
- Institute of Physiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Kanishka Sharma
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Harriet Thoeny
- Department of Radiology, Hôpital Cantonal Fribourgois, University of Fribourg, Fribourg, Switzerland
| | - Peter Vermathen
- Departments for BioMedical Research and Radiology, Inselspital, Universitaetspital Bern, Bern, Switzerland
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, CA, USA
| | - Zbigniew Serafin
- Department of Radiology, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
| | - Jeff L Zhang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan T Francis
- Sir Peter Mansfield Centre, University of Notthingham, Notthingham, UK
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Andreas Pohlmann
- Berlin Ultrahigh Field Facility, Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Sean B Fain
- Departments of Biomedical Engineering, Radiology, and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA.
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Song C, Lewis S, Kamath A, Hectors S, Putra J, Kihira S, Bane O, Ahmad J, Babb J, Thung S, Taouli B. Primary sclerosing cholangitis: diagnostic performance of MRI compared to blood tests and clinical scoring systems for the evaluation of histopathological severity of disease. Abdom Radiol (NY) 2020; 45:354-364. [PMID: 31844914 DOI: 10.1007/s00261-019-02366-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE To assess the diagnostic performance of magnetic resonance imaging (MRI) compared to blood tests and clinical scoring systems for the evaluation of histopathologic severity in patients with primary sclerosing cholangitis (PSC). MATERIALS Fifty-one patients (M/F 37/14, mean age 41 years) with PSC who underwent MRI and liver histopathology were included in this IRB-approved retrospective study. Two radiologists independently graded the severity of biliary abnormalities on magnetic resonance cholangiopancreatography (MRCP) using a standardized scoring system, parenchymal enhancement, and diffusion-weighted imaging (DWI) signal. Liver function tests, Mayo Risk score, APRI, FIB-4 Index, MELD, and Child-Pugh scores were recorded. Histopathology was assessed using a modified Nakanuma's scoring system. Correlation and diagnostic performance of MRI scores and blood tests for assessment of PSC histopathologic disease severity were evaluated. RESULTS Findings of cirrhosis and portal hypertension were the only imaging features diagnostic of advanced PSC (stages 3 and 4) with AUC up to 0.90 (p < 0.001) for both observers. Parenchymal enhancement and overall qualitative biliary ductal abnormality identified advanced PSC stage with AUC up to 0.767 (p = 0.002) only for one observer. There was weak correlation between the overall qualitative biliary ductal abnormality on MRCP and histopathologic stage (r = 0.36, p = 0.01) for one observer. FIB-4 index, Child-Pugh, MELD, Mayo Risk, APRI, and alkaline phosphatase demonstrated good to excellent performance for advanced PSC stage (AUCs 0.672-0.915, p < 0.045). CONCLUSIONS MRI findings of cirrhosis/portal hypertension, blood tests, and clinical scoring systems had high performance for advanced histopathologic PSC stage diagnosis, while the severity of biliary abnormalities on MRI did not.
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Dekkers IA, de Boer A, Sharma K, Cox EF, Lamb HJ, Buckley DL, Bane O, Morris DM, Prasad PV, Semple SIK, Gillis KA, Hockings P, Buchanan C, Wolf M, Laustsen C, Leiner T, Haddock B, Hoogduin JM, Pullens P, Sourbron S, Francis S. Consensus-based technical recommendations for clinical translation of renal T1 and T2 mapping MRI. MAGMA 2020; 33:163-176. [PMID: 31758418 PMCID: PMC7021750 DOI: 10.1007/s10334-019-00797-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 10/31/2019] [Accepted: 11/04/2019] [Indexed: 02/07/2023]
Abstract
To develop technical recommendations on the acquisition and post-processing of renal longitudinal (T1) and transverse (T2) relaxation time mapping. A multidisciplinary panel consisting of 18 experts in the field of renal T1 and T2 mapping participated in a consensus project, which was initiated by the European Cooperation in Science and Technology Action PARENCHIMA CA16103. Consensus recommendations were formulated using a two-step modified Delphi method. The first survey consisted of 56 items on T1 mapping, of which 4 reached the pre-defined consensus threshold of 75% or higher. The second survey was expanded to include both T1 and T2 mapping, and consisted of 54 items of which 32 reached consensus. Recommendations based were formulated on hardware, patient preparation, acquisition, analysis and reporting. Consensus-based technical recommendations for renal T1 and T2 mapping were formulated. However, there was considerable lack of consensus for renal T1 and particularly renal T2 mapping, to some extent surprising considering the long history of relaxometry in MRI, highlighting key knowledge gaps that require further work. This paper should be regarded as a first step in a long-term evidence-based iterative process towards ever increasing harmonization of scan protocols across sites, to ultimately facilitate clinical implementation.
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Affiliation(s)
- Ilona A Dekkers
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anneloes de Boer
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kaniska Sharma
- Department of Biomedical Imaging Sciences, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Eleanor F Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Hildo J Lamb
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - David L Buckley
- Department of Biomedical Imaging Sciences, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Octavia Bane
- Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David M Morris
- Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA
| | - Scott I K Semple
- Centre for Cardiovascular Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
| | - Keith A Gillis
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Paul Hockings
- Antaros Medical, Mölndal, Sweden
- MedTech West, Chalmers University of Technology, Gothenburg, Sweden
| | - Charlotte Buchanan
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Marcos Wolf
- Center for Medical Physics and Biomedical Engineering, MR-Centre of Excellence, Medical University of Vienna, Vienna, Austria
| | - Christoffer Laustsen
- Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark
| | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Bryan Haddock
- Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen University Hospital, Glostrup, Denmark
| | - Johannes M Hoogduin
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Pim Pullens
- Department of Radiology, University Hospital Ghent, Ghent, Belgium
- Ghent Institute of Functional and Metabolic Imaging, Ghent University, Ghent, Belgium
| | - Steven Sourbron
- Department of Biomedical Imaging Sciences, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Susan Francis
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
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Gordic S, Bane O, Kihira S, Peti S, Hectors S, Torres J, Cho J, Colombel JF, Taouli B. Evaluation of ileal Crohn's disease response to TNF antagonists: Validation of MR enterography for assessing response. Initial results. Eur J Radiol Open 2020; 7:100217. [PMID: 33102636 PMCID: PMC7569403 DOI: 10.1016/j.ejro.2020.01.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 01/17/2020] [Indexed: 12/26/2022] Open
Abstract
MaRIA and Clermont scores, ΔMaRIA and ΔClermont were all significantly different in patients with/without mucosal healing. MaRIA and Clermont scores, wall thickness and ΔMaRIA detect response to TNF antagonists in ileal Crohn’s disease. There is a potential role of baseline MRE in stratifying patients who could profit from therapy with TNF antagonists.
Purpose To assess the value of MRI obtained before and after treatment in detecting mucosal healing in patients with ileal Crohn’s disease (CD) treated with anti-TNF drugs. Methods In this IRB approved retrospective study, 24 patients (M/F 11/13, age 34.0 ± 12.5 years, age range 19–55 years) with ileal CD who underwent anti-TNF treatment, with pre- and post-treatment MRI (mean delay between MRIs 92 ± 57 weeks) were included. All patients underwent routine MR enterography (MRE), which included diffusion-weighted imaging (DWI). Two readers evaluated qualitative features (wall thickness, presence of edema and length of involvement) in consensus and one reader measured the following quantitative variables: relative contrast enhancement (RCE) and apparent diffusion coefficient (ADC) to derive the MaRIA and Clermont scores at baseline, post-treatment and their changes (ΔMaRIA, ΔClermont). Ileocolonoscopy results were used as the reference standard. Data was evaluated using Mann-Whitney U test and receiver operating characteristics analysis to assess the utility of the measures for the detection of mucosal healing. Results Twenty-four ileal segments were assessed in 24 patients. Nine patients showed mucosal healing while 15 had no mucosal healing on post-treatment endoscopy. Pre-treatment Clermont score and wall thickness and post-treatment MaRIA and Clermont scores, wall thickness, edema, length of involvement as well as ΔMaRIA and ΔClermont were all significantly different in patients with and without mucosal healing (p-range: 0.001-0.041) while MaRIA pre-treatment and ADC pre- and post-treatment were not. Pre-treatment Clermont score as well as post-treatment MaRIA and Clermont scores, wall thickness and ΔMaRIA were all significantly predictive of detection of mucosal healing (AUC 0.813-0.912; p = 0.003-0.024) after anti-TNF treatment. Conclusion Pre-treatment Clermont score as well as post-treatment MaRIA and Clermont scores, wall thickness and ΔMaRIA are significantly predictive of response to anti-TNF drugs in ileal Crohn’s disease. These results need to be verified in a larger study.
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Affiliation(s)
- Sonja Gordic
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shingo Kihira
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven Peti
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefanie Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joana Torres
- Department of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Judy Cho
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jean-Frederic Colombel
- Department of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Nery F, Buchanan CE, Harteveld AA, Odudu A, Bane O, Cox EF, Derlin K, Gach HM, Golay X, Gutberlet M, Laustsen C, Ljimani A, Madhuranthakam AJ, Pedrosa I, Prasad PV, Robson PM, Sharma K, Sourbron S, Taso M, Thomas DL, Wang DJJ, Zhang JL, Alsop DC, Fain SB, Francis ST, Fernández-Seara MA. Consensus-based technical recommendations for clinical translation of renal ASL MRI. MAGMA 2019. [PMID: 31833014 DOI: 10.1007/s10334‐019‐00800‐z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVES This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. METHODS An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. RESULTS Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. DISCUSSION This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding.
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Affiliation(s)
- Fabio Nery
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Charlotte E Buchanan
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Anita A Harteveld
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Aghogho Odudu
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Octavia Bane
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eleanor F Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Katja Derlin
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - H Michael Gach
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcel Gutberlet
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - Christoffer Laustsen
- MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Alexandra Ljimani
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ananth J Madhuranthakam
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ivan Pedrosa
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA
| | - Philip M Robson
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kanishka Sharma
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Danny J J Wang
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Jeff L Zhang
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - David C Alsop
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Sean B Fain
- Departments of Medical Physics, Radiology, and Biomedical Engineering, University of Wisconsin, Madison, Madison, USA
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
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32
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Nery F, Buchanan CE, Harteveld AA, Odudu A, Bane O, Cox EF, Derlin K, Gach HM, Golay X, Gutberlet M, Laustsen C, Ljimani A, Madhuranthakam AJ, Pedrosa I, Prasad PV, Robson PM, Sharma K, Sourbron S, Taso M, Thomas DL, Wang DJJ, Zhang JL, Alsop DC, Fain SB, Francis ST, Fernández-Seara MA. Consensus-based technical recommendations for clinical translation of renal ASL MRI. MAGMA 2019; 33:141-161. [PMID: 31833014 PMCID: PMC7021752 DOI: 10.1007/s10334-019-00800-z] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 11/08/2019] [Accepted: 11/11/2019] [Indexed: 12/14/2022]
Abstract
Objectives This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. Methods An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. Results Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. Discussion This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding. Electronic supplementary material The online version of this article (10.1007/s10334-019-00800-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Fabio Nery
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Charlotte E Buchanan
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Anita A Harteveld
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Aghogho Odudu
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Octavia Bane
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eleanor F Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Katja Derlin
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - H Michael Gach
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcel Gutberlet
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - Christoffer Laustsen
- MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Alexandra Ljimani
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ananth J Madhuranthakam
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ivan Pedrosa
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA
| | - Philip M Robson
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kanishka Sharma
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Danny J J Wang
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Jeff L Zhang
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - David C Alsop
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Sean B Fain
- Departments of Medical Physics, Radiology, and Biomedical Engineering, University of Wisconsin, Madison, Madison, USA
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
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Bane O, Mendichovszky IA, Milani B, Dekkers IA, Deux JF, Eckerbom P, Grenier N, Hall ME, Inoue T, Laustsen C, Lerman LO, Liu C, Morrell G, Pedersen M, Pruijm M, Sadowski EA, Seeliger E, Sharma K, Thoeny H, Vermathen P, Wang ZJ, Serafin Z, Zhang JL, Francis ST, Sourbron S, Pohlmann A, Fain SB, Prasad PV. Consensus-based technical recommendations for clinical translation of renal BOLD MRI. MAGMA 2019. [PMID: 31768797 DOI: 10.1007/s10334‐019‐00802‐x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Harmonization of acquisition and analysis protocols is an important step in the validation of BOLD MRI as a renal biomarker. This harmonization initiative provides technical recommendations based on a consensus report with the aim to move towards standardized protocols that facilitate clinical translation and comparison of data across sites. We used a recently published systematic review paper, which included a detailed summary of renal BOLD MRI technical parameters and areas of investigation in its supplementary material, as the starting point in developing the survey questionnaires for seeking consensus. Survey data were collected via the Delphi consensus process from 24 researchers on renal BOLD MRI exam preparation, data acquisition, data analysis, and interpretation. Consensus was defined as ≥ 75% unanimity in response. Among 31 survey questions, 14 achieved consensus resolution, 12 showed clear respondent preference (65-74% agreement), and 5 showed equal (50/50%) split in opinion among respondents. Recommendations for subject preparation, data acquisition, processing and reporting are given based on the survey results and review of the literature. These technical recommendations are aimed towards increased inter-site harmonization, a first step towards standardization of renal BOLD MRI protocols across sites. We expect this to be an iterative process updated dynamically based on progress in the field.
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Affiliation(s)
- Octavia Bane
- BioMedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Iosif A Mendichovszky
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | - Bastien Milani
- Center for BioMedical Imaging, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ilona A Dekkers
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jean-Francois Deux
- Department of Radiology, Groupe Hospitalier Henri Mondor, Créteil, France
| | - Per Eckerbom
- Department of Radiology, Institution for Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Nicolas Grenier
- Department of Radiology, Université de Bordeaux, CHU de Bordeaux, Bordeaux, France
| | - Michael E Hall
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Tsutomu Inoue
- Department of Nephrology, Faculty of Medicine, Saitama Medical University, Saitama, Japan
| | - Christoffer Laustsen
- The MR Research Center Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Lilach O Lerman
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Chunlei Liu
- Electrical Engineering and Computer Science, and Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Glen Morrell
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Michael Pedersen
- Department of Clinical Medicine-Comparative Medicine Lab, Aarhus University Hospital, Aarhus, Denmark
| | - Menno Pruijm
- Nephrology and Hypertension Service, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Elizabeth A Sadowski
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Erdmann Seeliger
- Institute of Physiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Kanishka Sharma
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Harriet Thoeny
- Department of Radiology, Hôpital Cantonal Fribourgois, University of Fribourg, Fribourg, Switzerland
| | - Peter Vermathen
- Departments for BioMedical Research and Radiology, Inselspital, Universitaetspital Bern, Bern, Switzerland
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, CA, USA
| | - Zbigniew Serafin
- Department of Radiology, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
| | - Jeff L Zhang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan T Francis
- Sir Peter Mansfield Centre, University of Notthingham, Notthingham, UK
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Andreas Pohlmann
- Berlin Ultrahigh Field Facility, Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Sean B Fain
- Departments of Biomedical Engineering, Radiology, and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA.
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Dekkers IA, de Boer A, Sharma K, Cox EF, Lamb HJ, Buckley DL, Bane O, Morris DM, Prasad PV, Semple SIK, Gillis KA, Hockings P, Buchanan C, Wolf M, Laustsen C, Leiner T, Haddock B, Hoogduin JM, Pullens P, Sourbron S, Francis S. Consensus-based technical recommendations for clinical translation of renal T1 and T2 mapping MRI. MAGMA 2019. [PMID: 31758418 DOI: 10.1007/s10334‐019‐00797‐5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
To develop technical recommendations on the acquisition and post-processing of renal longitudinal (T1) and transverse (T2) relaxation time mapping. A multidisciplinary panel consisting of 18 experts in the field of renal T1 and T2 mapping participated in a consensus project, which was initiated by the European Cooperation in Science and Technology Action PARENCHIMA CA16103. Consensus recommendations were formulated using a two-step modified Delphi method. The first survey consisted of 56 items on T1 mapping, of which 4 reached the pre-defined consensus threshold of 75% or higher. The second survey was expanded to include both T1 and T2 mapping, and consisted of 54 items of which 32 reached consensus. Recommendations based were formulated on hardware, patient preparation, acquisition, analysis and reporting. Consensus-based technical recommendations for renal T1 and T2 mapping were formulated. However, there was considerable lack of consensus for renal T1 and particularly renal T2 mapping, to some extent surprising considering the long history of relaxometry in MRI, highlighting key knowledge gaps that require further work. This paper should be regarded as a first step in a long-term evidence-based iterative process towards ever increasing harmonization of scan protocols across sites, to ultimately facilitate clinical implementation.
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Affiliation(s)
- Ilona A Dekkers
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anneloes de Boer
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kaniska Sharma
- Department of Biomedical Imaging Sciences, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Eleanor F Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Hildo J Lamb
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - David L Buckley
- Department of Biomedical Imaging Sciences, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Octavia Bane
- Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David M Morris
- Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA
| | - Scott I K Semple
- Centre for Cardiovascular Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
| | - Keith A Gillis
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Paul Hockings
- Antaros Medical, Mölndal, Sweden.,MedTech West, Chalmers University of Technology, Gothenburg, Sweden
| | - Charlotte Buchanan
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Marcos Wolf
- Center for Medical Physics and Biomedical Engineering, MR-Centre of Excellence, Medical University of Vienna, Vienna, Austria
| | - Christoffer Laustsen
- Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark
| | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Bryan Haddock
- Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen University Hospital, Glostrup, Denmark
| | - Johannes M Hoogduin
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Pim Pullens
- Department of Radiology, University Hospital Ghent, Ghent, Belgium.,Ghent Institute of Functional and Metabolic Imaging, Ghent University, Ghent, Belgium
| | - Steven Sourbron
- Department of Biomedical Imaging Sciences, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Susan Francis
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
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35
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Ljimani A, Caroli A, Laustsen C, Francis S, Mendichovszky IA, Bane O, Nery F, Sharma K, Pohlmann A, Dekkers IA, Vallee JP, Derlin K, Notohamiprodjo M, Lim RP, Palmucci S, Serai SD, Periquito J, Wang ZJ, Froeling M, Thoeny HC, Prasad P, Schneider M, Niendorf T, Pullens P, Sourbron S, Sigmund EE. Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI. MAGMA 2019; 33:177-195. [PMID: 31676990 PMCID: PMC7021760 DOI: 10.1007/s10334-019-00790-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 10/17/2019] [Accepted: 10/19/2019] [Indexed: 12/13/2022]
Abstract
Objectives Standardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexponential DWI, IVIM and DTI, as well as associated MRI biomarkers (ADC, D, D*, f, FA and MD) to aid ongoing international efforts on methodological harmonization. Materials and methods Reported DWI biomarkers from 194 prior renal DWI studies were extracted and Pearson correlations between diffusion biomarkers and protocol parameters were computed. Based on the literature review, surveys were designed for the consensus building. Survey data were collected via Delphi consensus process on renal DWI preparation, acquisition, analysis, and reporting. Consensus was defined as ≥ 75% agreement. Results Correlations were observed between reported diffusion biomarkers and protocol parameters. Out of 87 survey questions, 57 achieved consensus resolution, while many of the remaining questions were resolved by preference (65–74% agreement). Summary of the literature and survey data as well as recommendations for the preparation, acquisition, processing and reporting of renal DWI were provided. Discussion The consensus-based technical recommendations for renal DWI aim to facilitate inter-site harmonization and increase clinical impact of the technique on a larger scale by setting a framework for acquisition protocols for future renal DWI studies. We anticipate an iterative process with continuous updating of the recommendations according to progress in the field. Electronic supplementary material The online version of this article (10.1007/s10334-019-00790-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Alexandra Ljimani
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
| | - Anna Caroli
- Department of Biomedical Engineering, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy
| | - Christoffer Laustsen
- MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Susan Francis
- Sir Peter Mansfield Imaging Centre, University Park, University of Nottingham, Nottingham, NG7 2RD, UK
| | | | - Octavia Bane
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Fabio Nery
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Kanishka Sharma
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Andreas Pohlmann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, 13125, Berlin, Germany
| | - Ilona A Dekkers
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jean-Paul Vallee
- Department of Diagnostic, Geneva University Hospital and University of Geneva, 1211, Geneva-14, Switzerland
| | - Katja Derlin
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - Mike Notohamiprodjo
- Die Radiologie, Munich, Germany.,Department of Radiology, University Hospital Tuebingen, Tübingen, Germany
| | - Ruth P Lim
- Department of Radiology, Austin Health, The University of Melbourne, Melbourne, Australia
| | - Stefano Palmucci
- Department of Medical Surgical Sciences and Advanced Technologies, Radiology I Unit, University Hospital "Policlinico-Vittorio Emanuele", University of Catania, Catania, Italy
| | - Suraj D Serai
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joao Periquito
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, 13125, Berlin, Germany
| | - Zhen Jane Wang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Martijn Froeling
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Harriet C Thoeny
- Department of Radiology, Hôpital Cantonal Fribourgois (HFR), University of Fribourg, 1708, Fribourg, Switzerland
| | - Pottumarthi Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA
| | - Moritz Schneider
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.,Comprehensive Pneumology Center, German Center for Lung Research, Munich, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, 13125, Berlin, Germany
| | - Pim Pullens
- Ghent Institute for Functional and Metabolic Imaging, Ghent University, Ghent, Belgium.,Department of Radiology, University Hospital Ghent, Ghent, Belgium
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Eric E Sigmund
- Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), NYU Langone Health, New York, NY, USA
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36
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Bane O, Hectors SJ, Gordic S, Kennedy P, Wagner M, Weiss A, Khaim R, Yi Z, Zhang W, Delaney V, Salem F, He C, Menon MC, Lewis S, Taouli B. Multiparametric magnetic resonance imaging shows promising results to assess renal transplant dysfunction with fibrosis. Kidney Int 2019; 97:414-420. [PMID: 31874802 DOI: 10.1016/j.kint.2019.09.030] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 07/31/2019] [Accepted: 09/26/2019] [Indexed: 12/28/2022]
Abstract
Here we assessed the diagnostic value of a quantitative multiparametric magnetic resonance imaging (mpMRI) protocol for evaluation of renal allograft dysfunction with fibrosis. Twenty-seven renal transplant patients, including 15 with stable functional allografts (eGFR mean 71.5 ml/min/1.73m2), and 12 with chronic dysfunction/established fibrosis (eGFR mean 30.1 ml/min/1.73m2), were enrolled in this prospective single-center study. Sixteen of the patients had renal biopsy (mean 150 days) before the MRI. All patients underwent mpMRI at 1.5T including intravoxel-incoherent motion diffusion-weighted imaging, diffusion tensor imaging, blood oxygen level dependent (BOLD R2*) and T1 quantification. True diffusion D, pseudodiffusion D*, perfusion fraction PF, apparent diffusion coefficient (ADC), fractional anisotropy (FA), R2* and T1 were calculated for cortex and medulla. ΔT1 was calculated as (100x(T1 Cortex-T1 Medulla)/T1 Cortex). Test-retest repeatability and inter-observer reproducibility were assessed in four and ten patients, respectively. mpMRI parameters had substantial test-retest and interobserver repeatability (coefficient of variation under 15%), except for medullary PF and D* (coefficient of variation over 25%). Cortical ADC, D, medullary ADC and ΔT1 were all significantly decreased, while cortical T1 was significantly elevated in fibrotic allografts. Cortical T1 showed positive correlation to the Banff fibrosis and tubular atrophy scores. The combination of ΔT1 and cortical ADC had excellent cross-validated diagnostic performance for detection of chronic dysfunction with fibrosis. Cortical ADC and T1 had good performance for predicting eGFR decline at 18 months (4 or more ml/min/1.73m2/year). Thus, the combination of cortical ADC and T1 measurements shows promising results for the non-invasive assessment of renal allograft histology and outcomes.
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Affiliation(s)
- Octavia Bane
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Stefanie J Hectors
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Sonja Gordic
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Radiology, University Hospital Zürich, Zürich, Switzerland
| | - Paul Kennedy
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mathilde Wagner
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Amanda Weiss
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Rafael Khaim
- Division of Nephrology and Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Zhengzi Yi
- Division of Nephrology and Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Weijia Zhang
- Division of Nephrology and Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Veronica Delaney
- Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Fadi Salem
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Cijiang He
- Division of Nephrology and Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Madhav C Menon
- Division of Nephrology and Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Sara Lewis
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
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Hectors SJ, Bane O, Kennedy P, El Salem F, Menon M, Segall M, Khaim R, Delaney V, Lewis S, Taouli B. T 1ρ mapping for assessment of renal allograft fibrosis. J Magn Reson Imaging 2019; 50:1085-1091. [PMID: 30666744 DOI: 10.1002/jmri.26656] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Revised: 01/02/2019] [Accepted: 01/03/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND There is an unmet need for noninvasive methods to diagnose and stage renal allograft fibrosis. PURPOSE To investigate the utility of T1ρ measured with MRI for the assessment of fibrosis in renal allografts. STUDY TYPE Institutional Review Board (IRB)-approved prospective. SUBJECTS Fifteen patients with stable functional allograft (M/F 9/6, mean age 56 years) and 12 patients with allograft dysfunction and established fibrosis (M/F 6/6, mean age 51 years). FIELD STRENGTH/SEQUENCE T1ρ imaging at 1.5T using a custom-developed sequence. ASSESSMENT Average T1ρ in the cortex and medulla was quantified and T1ρ repeatability (expressed by the coefficient of variation [CV]) was measured in four patients. STATISTICAL TESTS Differences in T1ρ values between the 2 groups were assessed using Mann-Whitney U-tests. Diagnostic performance of T1ρ for differentiation between functional and fibrotic allografts was evaluated using receiver operating characteristic (ROC) analysis. Spearman correlations of T1ρ with Masson's trichrome-stained fractions and serum estimated glomerular filtration rate (eGFR) were assessed. RESULTS Higher T1ρ repeatability was found for cortex compared with medulla (mean CV T1ρ cortex 7.4%, medulla 13.3%). T1ρ values were significantly higher in the cortex of fibrotic vs. functional allografts (111.8 ± 17.2 msec vs. 99.0 ± 11.0 msec, P = 0.027), while there was no difference in medullary T1ρ values (122.6 ± 20.8 msec vs. 124.3 ± 20.8 msec, P = 0.789). Cortical T1ρ significantly correlated with Masson's trichrome-stained fractions (r = 0.515, P = 0.044) and eGFR (r = -0.546, P = 0.004), and demonstrated an area under the curve (AUC) of 0.77 for differentiating between functional and fibrotic allografts (sensitivity and specificity of 75.0% and 86.7%, using threshold of 106.9 msec). DATA CONCLUSION Our preliminary results suggest that T1ρ is a potential imaging biomarker of renal allograft fibrosis. These results should be verified in a larger study. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1085-1091.
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Affiliation(s)
- Stefanie J Hectors
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Paul Kennedy
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Fadi El Salem
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Madhav Menon
- Division of Renal Medicine, Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Maxwell Segall
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Rafael Khaim
- Division of Renal Medicine, Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Veronica Delaney
- Division of Renal Medicine, Recanati Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Sara Lewis
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Bane O, Peti S, Wagner M, Hectors S, Dyvorne H, Markl M, Taouli B. Hemodynamic measurements with an abdominal 4D flow MRI sequence with spiral sampling and compressed sensing in patients with chronic liver disease. J Magn Reson Imaging 2018; 49:994-1005. [PMID: 30318674 DOI: 10.1002/jmri.26305] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 07/30/2018] [Accepted: 07/31/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND The test-retest/interobserver repeatability and diagnostic value of 4D flow MRI in liver disease is underreported. PURPOSE To determine the reproducibility/repeatability of flow quantification in abdominal vessels using a spiral 4D flow MRI sequence; to assess the value of 4D flow parameters in diagnosing cirrhosis and degree of portal hypertension. STUDY TYPE Prospective. SUBJECTS Fifty-two patients with chronic liver disease. FIELD STRENGTH/SEQUENCE 1.5T/spiral 4D flow acquired in one breath-hold. ASSESSMENT Thirteen abdominal vessels were identified and segmented by two independent observers to measure maximum and time-averaged through-plane velocity, net flow, and vessel cross-section area. Interobserver agreement and test-retest repeatability were evaluated in 15 and 4 cases, respectively. Prediction of the presence and severity of cirrhosis and portal hypertension was assessed using 4D flow parameters. STATISTICAL TESTS Cohen's kappa coefficient, coefficient of variation (CV), Bland-Altman, Mann-Whitney tests, logistic regression. RESULTS For all vessels combined, measurements showed acceptable agreement between observers, with Cohen's kappa = 0.70 (P < 0.001), CV < 21%, Bland-Altman bias <5%, but high limits of agreement ([-75%,75%]). Test-retest repeatability was excellent in large vessels (CV = 1-15%, bias = 1-25%, Bland-Altman limits of agreement [BALA] = [4%,150%]), and poor in small vessels (CV = 7-130%, bias = 10-200%, BALA = [8%,190%]). Average velocity in the right hepatic vein and average area of the splenic vein were higher in cirrhosis (P = 0.027/0.0039). Flow in the middle hepatic vein strongly correlated with Child-Pugh score (ρ = 0.84, P = 0.0238), while flow in the splenic vein (ρ = 0.43, P = 0.032), time-average (ρ = 0.46, P = 0.02) and peak velocity in the superior mesenteric vein (ρ = 0.45, P = 0.032), and peak velocity in the infrarenal IVC (ρ = 0.39, P = 0.032) positively correlated with an imaging-based portal hypertension score. Average area of the splenic vein predicted cirrhosis (P = 0.019; area under the curve AUC [95% confidence interval, CI] = 0.87 [0.71,1.00]) and clinically significant portal hypertension (P = 0.042; AUC [95% CI] = 0.78 [0.57-0.99]). DATA CONCLUSION Spiral 4D flow allows comprehensive assessment of abdominal vessels in one breath-hold, with substantial interobserver reproducibility, but variable test-retest repeatability. 4D flow may potentially reflect vascular changes due to cirrhosis and portal hypertension. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:994-1005.
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Affiliation(s)
- Octavia Bane
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Steven Peti
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mathilde Wagner
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Groupe Hospitalier Pitié Salpêtrière, Paris, France
| | - Stefanie Hectors
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Hadrien Dyvorne
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Catalyzer, Guilford, Connecticut, USA
| | - Michael Markl
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA
| | - Bachir Taouli
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Hectors SJ, Gordic S, Semaan S, Bane O, Hirten R, Jia X, Colombel JF, Taouli B. Diffusion and perfusion MRI quantification in ileal Crohn's disease. Eur Radiol 2018; 29:993-1002. [PMID: 30019143 DOI: 10.1007/s00330-018-5627-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 06/12/2018] [Accepted: 06/21/2018] [Indexed: 02/06/2023]
Abstract
OBJECTIVES To quantify intravoxel incoherent motion (IVIM)-DWI and dynamic contrast-enhanced (DCE)-MRI parameters in normal and abnormal ileal segments in Crohn's disease (CD) patients and to assess the association of these parameters with clinical and MRI-based measurements of CD activity. METHODS In this prospective study, 27 CD patients (M/F 18/9, mean age 42 years) underwent MR enterography, including IVIM-DWI and DCE-MRI. IVIM-DWI and DCE-MRI parameters were quantified in normal and abnormal small bowel segments, the latter identified by the presence of inflammatory changes. MRI parameter differences between normal and abnormal bowel were tested using Wilcoxon signed-rank tests. IVIM-DWI and DCE-MRI parameters were correlated with clinical data (C-reactive protein, Harvey-Bradshaw Index), conventional MRI parameters (wall thickness, length of involvement) and MRI activity scores (MaRIA, Clermont). Diagnostic performance of (combined) parameters for differentiation between normal and abnormal bowel was determined using ROC analysis. RESULTS The DCE-MRI parameters peak concentration Cpeak, upslope, area-under-the-curve at 60s (AUC60), Ktrans and ve were significantly increased (p<0.023), while IVIM-DWI parameters perfusion fraction (PF) and ADC were significantly decreased (p<0.001) in abnormal bowel segments. None of the DCE-MRI and IVIM-DWI parameters correlated with clinical parameters (p>0.105). DCE-MRI parameters exhibited multiple significant correlations with wall thickness (Cpeak, upslope, AUC60, Ktrans; r range 0.431-0.664, p<0.025) and MaRIA/Clermont scores (Cpeak, AUC60, Ktrans; r range 0.441-0.617, p<0.021). Combined Ktrans+ve+PF+ADC showed highest AUC (0.963) for differentiation between normal and abnormal bowel, while ADC performed best for individual parameters (AUC=0.800). CONCLUSIONS DCE-MRI and IVIM-DWI, particularly when used in combination, are promising for non-invasive evaluation of small bowel CD. KEY POINTS • IVIM-DWI and DCE-MRI parameters were significantly different between normal and abnormal bowel segments in CD patients. • DCE-MRI parameters showed a significant association with wall thickness and MRI activity scores. • Combination of IVIM-DWI and DCE-MRI parameters led to the highest diagnostic performance for differentiation between normal and abnormal bowel segments, while ADC showed the highest diagnostic performance of individual parameters.
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Affiliation(s)
- Stefanie J Hectors
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonja Gordic
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Sahar Semaan
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Hirten
- IBD Center, Division of Gastroenterology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xiaoyu Jia
- Department of Population Health Science and Policy, Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jean-Frederic Colombel
- IBD Center, Division of Gastroenterology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Bane O, Hectors S, Wagner M, Arlinghaus LL, Aryal M, Cao Y, Chenevert T, Fennessy F, Huang W, Hylton N, Kalpathy-Cramer J, Keenan K, Malyarenko D, Mulkern R, Newitt D, Russek SE, Stupic KF, Tudorica A, Wilmes L, Yankeelov TE, Yen YF, Boss M, Taouli B. Accuracy, repeatability, and interplatform reproducibility of T 1 quantification methods used for DCE-MRI: Results from a multicenter phantom study. Magn Reson Med 2018; 79:2564-2575. [PMID: 28913930 PMCID: PMC5821553 DOI: 10.1002/mrm.26903] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2017] [Revised: 08/14/2017] [Accepted: 08/16/2017] [Indexed: 02/05/2023]
Abstract
PURPOSE To determine the in vitro accuracy, test-retest repeatability, and interplatform reproducibility of T1 quantification protocols used for dynamic contrast-enhanced MRI at 1.5 and 3 T. METHODS A T1 phantom with 14 samples was imaged at eight centers with a common inversion-recovery spin-echo (IR-SE) protocol and a variable flip angle (VFA) protocol using seven flip angles, as well as site-specific protocols (VFA with different flip angles, variable repetition time, proton density, and Look-Locker inversion recovery). Factors influencing the accuracy (deviation from reference NMR T1 measurements) and repeatability were assessed using general linear mixed models. Interplatform reproducibility was assessed using coefficients of variation. RESULTS For the common IR-SE protocol, accuracy (median error across platforms = 1.4-5.5%) was influenced predominantly by T1 sample (P < 10-6 ), whereas test-retest repeatability (median error = 0.2-8.3%) was influenced by the scanner (P < 10-6 ). For the common VFA protocol, accuracy (median error = 5.7-32.2%) was influenced by field strength (P = 0.006), whereas repeatability (median error = 0.7-25.8%) was influenced by the scanner (P < 0.0001). Interplatform reproducibility with the common VFA was lower at 3 T than 1.5 T (P = 0.004), and lower than that of the common IR-SE protocol (coefficient of variation 1.5T: VFA/IR-SE = 11.13%/8.21%, P = 0.028; 3 T: VFA/IR-SE = 22.87%/5.46%, P = 0.001). Among the site-specific protocols, Look-Locker inversion recovery and VFA (2-3 flip angles) protocols showed the best accuracy and repeatability (errors < 15%). CONCLUSIONS The VFA protocols with 2 to 3 flip angles optimized for different applications achieved acceptable balance of extensive spatial coverage, accuracy, and repeatability in T1 quantification (errors < 15%). Further optimization in terms of flip-angle choice for each tissue application, and the use of B1 correction, are needed to improve the robustness of VFA protocols for T1 mapping. Magn Reson Med 79:2564-2575, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai,Radiology, Icahn School of Medicine at Mount Sinai
| | - Stefanie Hectors
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai,Radiology, Icahn School of Medicine at Mount Sinai
| | - Mathilde Wagner
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai,Radiology, Icahn School of Medicine at Mount Sinai
| | | | | | - Yue Cao
- Radiation Oncology, University of Michigan
| | | | | | - Wei Huang
- Advanced Imaging Research Center, Knight Cancer Institute, Oregon Health and Science University
| | - Nola Hylton
- Radiology, University of California San Francisco
| | | | | | | | | | - David Newitt
- Radiology, University of California San Francisco
| | | | | | | | - Lisa Wilmes
- Radiology, University of California San Francisco
| | | | - Yi-Fei Yen
- Radiology, Massachusetts General Hospital
| | | | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai,Radiology, Icahn School of Medicine at Mount Sinai
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Wagner M, Hectors S, Bane O, Gordic S, Kennedy P, Besa C, Schiano TD, Thung S, Fischman A, Taouli B. Noninvasive prediction of portal pressure with MR elastography and DCE-MRI of the liver and spleen: Preliminary results. J Magn Reson Imaging 2018; 48:1091-1103. [PMID: 29638020 DOI: 10.1002/jmri.26026] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 03/09/2018] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Portal hypertension (PH), defined by hepatic venous pressure gradient (HVPG) ≥5 mmHg and clinically significant PH, defined by HVPG ≥10 mmHg, are complications of chronic liver disease. PURPOSE To assess the diagnostic performance of MR elastography (MRE) and dynamic contrast-enhanced MRI (DCE-MRI) of the liver and spleen for the prediction of PH and clinically significant PH, in comparison with a qualitative PH imaging scoring system. STUDY TYPE IRB-approved prospective study. POPULATION In all, 34 patients with chronic liver disease who underwent HVPG measurement. FIELD STRENGTH/SEQUENCE 1.5/3T examination including 2D-GRE MRE (n = 33) and DCE-MRI of the liver/spleen (n = 28). ASSESSMENT Liver and spleen stiffness were calculated from elastogram maps. DCE-MRI was analyzed using model-free parameters and pharmacokinetic modeling. Two observers calculated qualitative PH imaging scores based on routine images. STATISTICAL TESTS Imaging parameters were correlated with HVPG. Receiver operating characteristic (ROC) analysis was performed for prediction of PH and clinically significant PH. RESULTS There were significant correlations between DCE-MRI parameters (liver time-to-peak, r = 0.517 / P = 0.006, liver distribution volume, r = 0.494 / P = 0.009, liver upslope, r = -0.567 / P = 0.002), liver stiffness (r = 0.478 / P = 0.016), PH imaging score (r = 0.441 / P = 0.009), and HVPG. ROC analysis provided significant area under the ROC (AUROCs) for PH (liver upslope 0.765, liver stiffness 0.809, spleen volume/diameter 0.746-0.731, PH imaging score 0.756) and for clinically significant PH (liver and spleen perfusion parameters 0.733-0.776, liver stiffness 0.742, PH imaging score 0.742). The ratio of liver stiffness to liver upslope had the highest AUROC for diagnosing PH (0.903) and clinically significant PH (0.785). DATA CONCLUSION These preliminary results suggest that the combination of liver stiffness and perfusion metrics provide excellent accuracy for diagnosing PH, and fair accuracy for clinically significant PH. Combined MRE and DCE-MRI outperformed qualitative imaging scores for prediction of PH. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1091-1103.
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Affiliation(s)
- Mathilde Wagner
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Sorbonne Universités, CNRS, INSERM, LIB, Department of Radiology, Hôpital Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Stefanie Hectors
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Sonja Gordic
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Paul Kennedy
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Cecilia Besa
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Thomas D Schiano
- Department of Medicine, Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Swan Thung
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Aaron Fischman
- Department of Radiology, Section of Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Bane O, Wagner M, Zhang JL, Dyvorne HA, Orton M, Rusinek H, Taouli B. Assessment of renal function using intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI. J Magn Reson Imaging 2016; 44:317-26. [PMID: 26855407 PMCID: PMC4946973 DOI: 10.1002/jmri.25171] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Accepted: 01/13/2016] [Indexed: 01/10/2023] Open
Abstract
PURPOSE To assess the correlation between each of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in renal parenchyma with renal function, in a cohort of patients with chronic liver disease. MATERIALS AND METHODS Thirty patients with liver disease underwent abdominal MRI at 1.5T, including a coronal respiratory-triggered IVIM-DWI sequence and a coronal 3D FLASH DCE-MRI acquisition. Diffusion signals in the renal cortex and medulla were fitted to the IVIM model to estimate the diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (PF). The apparent diffusion coefficient (ADC) was calculated using all b-values. The glomerular filtration rate (GFR), cortical and medullary renal plasma flow (RPF), mean transit times (MTT) of vascular and tubular compartments and the whole kidney, were calculated from DCE-MRI data by fitting to a three-compartment model. The estimated GFR (eGFR) was calculated from serum creatinine measured 30 ± 27 days of MRI. RESULTS ADC, PF, and RPF were significantly higher in renal cortex vs. medulla (P < 10(-5) ). DCE-MRI GFR significantly correlated with, but underestimated, eGFR (Spearman's r/P = 0.49/0.01). IVIM-DWI parameters were not significantly correlated with eGFR. DCE-MRI GFR correlated weakly with D (cortex, r/P = 0.3/0.03; medulla r/P = 0.27/0.05) and ADC (cortex r/P = 0.28/0.04; medulla r/P = 0.34/0.01). Weak correlations were observed for pooled cortical and medullar RPF with PF (r/P = 0.32/10(-3) ) and with ADC (r/P = 0.29/0.0025). Significant negative correlations were observed for vascular MTT with cortical D* (r/P = -0.38/0.004) and D*×PF (r/P = -0.34/0.01). CONCLUSION The weak correlations between renal IVIM and DCE-MRI perfusion parameters imply that these functional measures could be complementary. J. Magn. Reson. Imaging 2016;44:317-326.
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Affiliation(s)
- Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Mathilde Wagner
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jeff L. Zhang
- Departments of Radiology and Biomedical Engineering, University of Utah, Salt Lake City, UT
| | - Hadrien A. Dyvorne
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Matthew Orton
- Division of Radiotherapy and Imaging, Institute of Cancer Research, Sutton, Surrey, UK
| | - Henry Rusinek
- Departments of Radiology and Biomedical Engineering, New York University, New York, NY
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY
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Dyvorne HA, Jajamovich GH, Bane O, Fiel MI, Chou H, Schiano TD, Dieterich D, Babb JS, Friedman SL, Taouli B. Prospective comparison of magnetic resonance imaging to transient elastography and serum markers for liver fibrosis detection. Liver Int 2016; 36:659-66. [PMID: 26744140 PMCID: PMC4842106 DOI: 10.1111/liv.13058] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 12/24/2015] [Indexed: 12/18/2022]
Abstract
BACKGROUND & AIMS Establishing accurate non-invasive methods of liver fibrosis quantification remains a major unmet need. Here, we assessed the diagnostic value of a multiparametric magnetic resonance imaging (MRI) protocol including diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI and magnetic resonance elastography (MRE) in comparison with transient elastography (TE) and blood tests [including ELF (Enhanced Liver Fibrosis) and APRI] for liver fibrosis detection. METHODS In this single centre cross-sectional study, we prospectively enrolled 60 subjects with liver disease who underwent multiparametric MRI (DWI, DCE-MRI and MRE), TE and blood tests. Correlation was assessed between non-invasive modalities and histopathologic findings including stage, grade and collagen content, while accounting for covariates such as age, sex, BMI, HCV status and MRI-derived fat and iron content. ROC curve analysis evaluated the performance of each technique for detection of moderate-to-advanced liver fibrosis (F2-F4) and advanced fibrosis (F3-F4). RESULTS Magnetic resonance elastography provided the strongest correlation with fibrosis stage (r = 0.66, P < 0.001), inflammation grade (r = 0.52, P < 0.001) and collagen content (r = 0.53, P = 0.036). For detection of moderate-to-advanced fibrosis (F2-F4), AUCs were 0.78, 0.82, 0.72, 0.79, 0.71 for MRE, TE, DCE-MRI, DWI and APRI, respectively. For detection of advanced fibrosis (F3-F4), AUCs were 0.94, 0.77, 0.79, 0.79 and 0.70, respectively. CONCLUSIONS Magnetic resonance elastography provides the highest correlation with histopathologic markers and yields high diagnostic performance for detection of advanced liver fibrosis and cirrhosis, compared to DWI, DCE-MRI, TE and serum markers.
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Affiliation(s)
- Hadrien A. Dyvorne
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - Guido H. Jajamovich
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - M. Isabel Fiel
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - Hsin Chou
- Department of Medicine, Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - Thomas D. Schiano
- Department of Medicine, Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - Douglas Dieterich
- Department of Medicine, Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - James S. Babb
- Department of Radiology, New York University Langone Medical Center, New York, NY
| | - Scott L. Friedman
- Department of Medicine, Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, One Gustave Levy Place, Box 1234, New York, NY 10029 USA
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Hectors SJ, Wagner M, Besa C, Bane O, Dyvorne HA, Fiel MI, Zhu H, Donovan M, Taouli B. Intravoxel incoherent motion diffusion-weighted imaging of hepatocellular carcinoma: Is there a correlation with flow and perfusion metrics obtained with dynamic contrast-enhanced MRI? J Magn Reson Imaging 2016; 44:856-64. [PMID: 26919327 DOI: 10.1002/jmri.25194] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 01/28/2016] [Accepted: 01/30/2016] [Indexed: 12/31/2022] Open
Abstract
PURPOSE To assess the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in hepatocellular carcinoma (HCC) and liver parenchyma. MATERIALS AND METHODS Twenty-five patients with HCC (M/F 23/2, mean age 58 years) underwent abdominal MRI at 1.5 or 3.0T, including IVIM-DWI (with 16 b-values) and DCE-MRI (3D FLASH sequence, mean temporal resolution of 2.3 sec). IVIM-DWI parameters (pseudodiffusion coefficient, D*, diffusion coefficient, D, and perfusion fraction, PF) were quantified in HCC lesions and liver parenchyma using a Bayesian fitting algorithm. DCE-MRI parameters (arterial flow, Fa , portal flow, Fp , total flow, Ft , mean transit time, MTT, distribution volume, DV, and arterial fraction, ART) were quantified using a dual-input single-compartment model. Correlations between IVIM-DWI and DCE-MRI parameters were assessed using a Spearman correlation test. RESULTS Thirty-three HCC lesions (average size 5.0 ± 3.6 cm) were analyzed. D, D*, and PF were all significantly lower in HCC vs. liver (P < 0.05). Significantly higher Fa and ART and lower Fp were observed in HCC vs. liver (P < 0.001). Significant moderate to strong negative correlations were observed between ART and D* (r = -0.443, P = 0.028), ART and PF (r = -0.536, P = 0.006), ART and PFxD* (r = -0.655, P < 0.001), Fa and PF (r = 0.455, P = 0.023), and Fa and PFxD* (r = -0.475, P = 0.018) in liver parenchyma. There was no significant correlation between IVIM-DWI and DCE-MRI metrics in HCC lesions. CONCLUSION IVIM-DWI and DCE-MRI provide nonredundant information in HCC, while they correlate in liver parenchyma. These findings may be secondary to predominant portal inflow in the liver and tortuous vasculature and tissue heterogeneity in tumors. J. MAGN. RESON. IMAGING 2016;44:856-864.
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Affiliation(s)
- Stefanie J Hectors
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mathilde Wagner
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Cecilia Besa
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Hadrien A Dyvorne
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - M Isabel Fiel
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Hongfa Zhu
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Michael Donovan
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA. .,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
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Chatterjee N, Bane O, Spottiswoode BS, Carr JC, Carroll T. Measurement of myocardial blood volume and water exchange using ferumoxytol. J Cardiovasc Magn Reson 2015. [PMCID: PMC4328585 DOI: 10.1186/1532-429x-17-s1-p253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Chatterjee N, Bane O, Spottiswoode BS, Carr JC, Carroll T. Measurement of myocardial blood volume and water exchange using ferumoxytol. J Cardiovasc Magn Reson 2015. [PMCID: PMC4328902 DOI: 10.1186/1532-429x-17-s1-w11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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47
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Yasar TK, Wagner M, Bane O, Besa C, Babb JS, Kannengiesser S, Fung M, Ehman RL, Taouli B. Interplatform reproducibility of liver and spleen stiffness measured with MR elastography. J Magn Reson Imaging 2015; 43:1064-72. [PMID: 26469708 DOI: 10.1002/jmri.25077] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Accepted: 09/29/2015] [Indexed: 12/27/2022] Open
Abstract
PURPOSE To assess interplatform reproducibility of liver stiffness (LS) and spleen stiffness (SS) measured with magnetic resonance elastography (MRE) based on a 2D gradient echo (GRE) sequence. MATERIALS AND METHODS This prospective Health Insurance Portability and Accountability Act (HIPAA)-compliant and Institutional Review Board (IRB)-approved study involved 12 subjects (five healthy volunteers and seven patients with liver disease). A multislice 2D-GRE-based MRE sequence was performed using two systems from different vendors (3.0T GE and 1.5T Siemens) on the same day. Two independent observers measured LS and SS on confidence maps. Bland-Altman analysis (with coefficient of reproducibility, CR), coefficient of variability (CV), and intraclass correlation (ICC) were used to analyze interplatform, intra- and interobserver variability. Human data were validated using a gelatin-based phantom. RESULTS There was excellent reproducibility of phantom stiffness measurement (CV 4.4%). Mean LS values were 3.44-3.48 kPa and 3.62-3.63 kPa, and mean SS values were 7.54-7.91 kPa and 8.40-8.85 kPa at 3.0T and 1.5T for observers 1 and 2, respectively. The mean CVs between platforms were 9.2%-11.5% and 13.1%-14.4% for LS and SS, respectively, for observers 1 and 2. There was excellent interplatform reproducibility (ICC >0.88 and CR <36.2%) for both LS and SS, and excellent intra- and interobserver reproducibility (intraobserver: ICC >0.99, CV <2.1%, CR <6.6%; interobserver: ICC >0.97, CV and CR <16%). CONCLUSION This study demonstrates that 2D-GRE MRE provides platform- and observer-independent LS and SS measurements.
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Affiliation(s)
- Temel Kaya Yasar
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mathilde Wagner
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Cecilia Besa
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - James S Babb
- Department of Radiology, New York University, New York, New York, USA
| | | | - Maggie Fung
- GE Healthcare, MR Applications & Workflow, New York, New York, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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48
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Bane O, Besa C, Wagner M, Oesingmann N, Zhu H, Fiel MI, Taouli B. Feasibility and reproducibility of BOLD and TOLD measurements in the liver with oxygen and carbogen gas challenge in healthy volunteers and patients with hepatocellular carcinoma. J Magn Reson Imaging 2015; 43:866-76. [PMID: 26417669 DOI: 10.1002/jmri.25051] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 09/02/2015] [Indexed: 12/28/2022] Open
Abstract
PURPOSE To quantify baseline relaxation rates R2* and R1 in the abdomen, their changes after respiratory challenges, and their reproducibility in healthy volunteers and patients with hepatocellular carcinoma (HCC) at 1.5T and 3.0T. MATERIALS AND METHODS R2* measurements were acquired in the liver in 8 volunteers and 27 patients with 34 HCCs using multiecho T2* at baseline and after respiratory challenges with 100% oxygen (O2 ) and carbogen (CB = 95%O2 /5%CO2 ). R1 was measured at 1.5T in one volunteer and 21 patients with 23 HCCs. Test-retest coefficient of variation (CV) was assessed in 10 subjects. Intra- and interobserver variability of R2* and R1 measurements was assessed in 12 and 10 patients, respectively. Parameters for HCC, liver, and muscle were compared between baseline and after gas challenges. RESULTS We observed that R2* and R1 imaging of HCCs with O2 and CB is feasible and reproducible (test-retest CV R2*<15%/R1 <5%; intra- and interobserver intraclass correlation coefficient R2*>0.88/R1 >0.7 and CV R2*<7%/R1 <3% at 1.5T). R2* measurements were observed to be less reproducible at 3.0T (CV<35%). There was a statistically significant decrease in R2* values in HCC before and after O2 (P = 0.02) and increase in R1 after O2 (P = 0.004). CB had no significant effect (P R2* = 0.47/R1 = 0.278). CONCLUSION R2* measurements in HCC and liver parenchyma are more reproducible at 1.5T than at 3.0T, and with O2 than with CB challenge. We observed a decrease in R2* and an increase in R1 of HCCs from baseline in response to O2 challenge, as expected with increased tissue and blood oxygenation.
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Affiliation(s)
- Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Cecilia Besa
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mathilde Wagner
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Hongfa Zhu
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Maria Isabel Fiel
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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49
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Bane O, Shah SJ, Cuttica MJ, Collins JD, Selvaraj S, Chatterjee NR, Guetter C, Carr JC, Carroll TJ. A non-invasive assessment of cardiopulmonary hemodynamics with MRI in pulmonary hypertension. Magn Reson Imaging 2015; 33:1224-1235. [PMID: 26283577 DOI: 10.1016/j.mri.2015.08.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Revised: 08/04/2015] [Accepted: 08/08/2015] [Indexed: 11/29/2022]
Abstract
PURPOSE We propose a method for non-invasive quantification of hemodynamic changes in the pulmonary arteries resulting from pulmonary hypertension (PH). METHODS Using a two-element Windkessel model, and input parameters derived from standard MRI evaluation of flow, cardiac function and valvular motion, we derive: pulmonary artery compliance (C), mean pulmonary artery pressure (mPAP), pulmonary vascular resistance (PVR), pulmonary capillary wedge pressure (PCWP), time-averaged intra-pulmonary pressure waveforms and pulmonary artery pressures (systolic (sPAP) and diastolic (dPAP)). MRI results were compared directly to reference standard values from right heart catheterization (RHC) obtained in a series of patients with suspected pulmonary hypertension (PH). RESULTS In 7 patients with suspected PH undergoing RHC, MRI and echocardiography, there was no statistically significant difference (p<0.05) between parameters measured by MRI and RHC. Using standard clinical cutoffs to define PH (mPAP>25mmHg), MRI was able to correctly identify all patients as having pulmonary hypertension, and to correctly distinguish between pulmonary arterial (mPAP>25mmHg, PCWP<15mmHg) and venous hypertension (mPAP>25mmHg, PCWP>15mmHg) in 5 of 7 cases. CONCLUSIONS We have developed a mathematical model capable of quantifying physiological parameters that reflect the severity of PH.
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Affiliation(s)
- Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai Hospital, New York, NY; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Sanjiv J Shah
- Division of Cardiology, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Michael J Cuttica
- Division of Pulmonary and Critical Care, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Jeremy D Collins
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Senthil Selvaraj
- Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Neil R Chatterjee
- Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL; Feinberg School of Medicine, Northwestern University, Chicago, IL
| | | | - James C Carr
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Timothy J Carroll
- Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL.
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50
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Satkunasingham J, Besa C, Bane O, Shah A, de Oliveira A, Gilson WD, Kannengiesser S, Taouli B. Liver fat quantification: Comparison of dual-echo and triple-echo chemical shift MRI to MR spectroscopy. Eur J Radiol 2015; 84:1452-1458. [PMID: 26047820 DOI: 10.1016/j.ejrad.2015.05.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2014] [Revised: 04/29/2015] [Accepted: 05/02/2015] [Indexed: 12/20/2022]
Abstract
PURPOSE To assess the diagnostic value of MRI using dual-echo (2PD) and triple-echo (3PD) chemical shift imaging for liver fat quantification against multi-echo T2 corrected MR spectroscopy (MRS) used as the reference standard, and examine the effect of T2(*) imaging on accuracy of MRI for fat quantification. MATERIALS AND METHODS Patients who underwent 1.5T liver MRI that incorporated 2PD, 3PD, multi-echo T2(*) and MRS were included in this IRB approved prospective study. Regions of interest were placed in the liver to measure fat fraction (FF) with 2PD and 3PD and compared with MRS-FF. A random subset of 25 patients with a wide range of MRS-FF was analyzed with an advanced FF calculation method, to prove concordance with the 3PD. The statistical analysis included correlation stratified according to T2(*), Bland-Altman analysis, and calculation of diagnostic accuracy for detection of MRS-FF>6.25%. RESULTS 220 MRI studies were identified in 217 patients (mean BMI 28.0±5.6). 57/217 (26.2%) patients demonstrated liver steatosis (MRS-FF>6.25%). Bland-Altman analysis revealed strong agreement between 3PD and MRS (mean±1.96 SD: -0.5%±4.6%) and weaker agreement between 2PD and MRS (4.7%±16.0%). Sensitivity of 3PD for diagnosing FF> 6.25% was higher than that of 2PD. 3PD-FF showed minor discrepancies (coefficient of variation <10%) from FF measured with the advanced method. CONCLUSION Our large series study validates the use of 3PD chemical shift sequence for detection of liver fat in the clinical environment, even in the presence of T2(*) shortening.
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Affiliation(s)
- Janakan Satkunasingham
- Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States; Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States
| | - Cecilia Besa
- Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States; Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States
| | - Octavia Bane
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States
| | - Ami Shah
- Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States
| | | | | | | | - Bachir Taouli
- Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States; Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029, United States.
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