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Young AM, Garver KA, Gulani V. Positive Leadership within Breast Imaging: Impact on Burnout, Intent to Leave, and Engagement. Radiology 2024; 311:e232329. [PMID: 38742975 DOI: 10.1148/radiol.232329] [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 High rates of provider burnout and turnover, as well as staffing shortages, are creating crises within radiology departments. Identifying ways to support health care workers, such as the Positively Energizing Leadership program, is important during these ongoing crises. Purpose To identify the relationship between leadership behaviors and workplace climate and health care worker outcomes (ie, burnout, intent to leave, and engagement) and to determine whether the positive leadership program could improve workplace climate and health care worker outcomes. Materials and Methods This prospective study involved two parts. First, a web-based survey was administered to faculty and staff in a breast imaging unit of a large academic medical center in February 2021 to identify relationships between leadership behaviors and workplace climate and health care worker outcomes. Second, a web-based survey was administered in February 2023, following the implementation of a positive leadership program, to determine improvement in engagement and reduction of burnout and intent to leave since 2021. Multiple regression, the Sobel test, Pearson correlation, and the t test were used, with a conservative significance level of P < .001. Results The sample consisted of 88 respondents (response rate, 95%) in 2021 and 85 respondents (response rate, 92%) in 2023. Leadership communication was associated with a positive workplace climate (β = 0.76, P < .001) and a positive workplace climate was associated with improved engagement (β = 0.53, P < .001), reduction in burnout (β = -0.42, P < .001), and reduction in intent to leave (β = -0.49, P < .001). Following a 2-year positive leadership program, improved perceptions were observed for leadership communication (pretest mean, 4.59 ± 1.51 [SD]; posttest mean, 5.80 ± 1.01; t = 5.97, P < .001), workplace climate (pretest mean, 5.09 ± 1.43; posttest mean, 5.77 ± 1.11; t = 3.35, P < .001), and engagement (pretest mean, 5.27 ± 1.20, posttest mean, 5.68 ± 0.96; t = 2.50, P < .01), with a reduction in burnout (pretest mean, 2.69 ± 0.94; posttest mean, 2.18 ± 0.74; t = 3.50, P < .001) and intent to leave (pretest mean, 3.12 ± 2.23; posttest mean, 2.56 ± 1.84; t = 1.78, P < .05). Conclusion After implementation of a positive leadership program in a radiology department breast imaging unit, burnout and intention to leave decreased among health care workers, while engagement increased. © RSNA, 2024 See also the editorial by Thrall in this issue.
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Affiliation(s)
- Amy M Young
- From the Ross School of Business, University of Michigan, 701 Tappan St, Room R3480, Ann Arbor, MI 48109-1382 (A.M.Y.); and Department of Radiology, Michigan Medicine, Ann Arbor, Mich (A.M.Y., K.A.G., V.G.)
| | - Kimberly A Garver
- From the Ross School of Business, University of Michigan, 701 Tappan St, Room R3480, Ann Arbor, MI 48109-1382 (A.M.Y.); and Department of Radiology, Michigan Medicine, Ann Arbor, Mich (A.M.Y., K.A.G., V.G.)
| | - Vikas Gulani
- From the Ross School of Business, University of Michigan, 701 Tappan St, Room R3480, Ann Arbor, MI 48109-1382 (A.M.Y.); and Department of Radiology, Michigan Medicine, Ann Arbor, Mich (A.M.Y., K.A.G., V.G.)
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2
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Ramachandran A, Hussain HK, Gulani V, Kelsey L, Mendiratta-Lala M, Richardson J, Masotti M, Dudek N, Morehouse J, Panagis KR, Wright K, Seiberlich N. Abdominal MRI on a Commercial 0.55T System: Initial Evaluation and Comparison to Higher Field Strengths. Acad Radiol 2024:S1076-6332(24)00018-7. [PMID: 38320946 DOI: 10.1016/j.acra.2024.01.018] [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: 10/17/2023] [Revised: 01/09/2024] [Accepted: 01/09/2024] [Indexed: 02/08/2024]
Abstract
RATIONALE AND OBJECTIVES This study aims to assess the quality of abdominal MR images acquired on a commercial 0.55T scanner and compare these images with those acquired on conventional 1.5T/3T scanners in both healthy subjects and patients. MATERIALS AND METHODS Fifteen healthy subjects and 52 patients underwent abdominal Magnetic Resonance Imaging at 0.55T. Images were also collected in healthy subjects at 1.5T, and comparison 1.5/3T images identified for 28 of the 52 patients. Image quality was rated by two radiologists on a 4-point Likert scale. Readers were asked whether they could answer the clinical question for patient studies. Wilcoxon signed-rank test was used to test for significant differences in image ratings and acquisition times, and inter-reader reliability was computed. RESULTS The overall image quality of all sequences at 0.55T were rated as acceptable in healthy subjects. Sequences were modified to improve signal-to-noise ratio and reduce artifacts and deployed for clinical use; 52 patients were enrolled in this study. Radiologists were able to answer the clinical question in 52 (reader 1) and 46 (reader 2) of the patient cases. Average image quality was considered to be diagnostic (>3) for all sequences except arterial phase FS 3D T1w gradient echo (GRE) and 3D magnetic resonance cholangiopancreatography for one reader. In comparison to higher field images, significantly lower scores were given to 0.55T IP 2D GRE and arterial phase FS 3D T1w GRE, and significantly higher scores to diffusion-weighted echo planar imaging at 0.55T; other sequences were equivalent. The average scan time at 0.55T was 54 ± 10 minutes vs 36 ± 11 minutes at higher field strengths (P < .001). CONCLUSION Diagnostic-quality abdominal MR images can be obtained on a commercial 0.55T scanner at a longer overall acquisition time compared to higher field systems, although some sequences may benefit from additional optimization.
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Affiliation(s)
| | - Hero K Hussain
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | - Lauren Kelsey
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | | | - Jacob Richardson
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | - Maria Masotti
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Nancy Dudek
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | - Joel Morehouse
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | | | - Katherine Wright
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109.
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Ramachandran A, Hussain H, Seiberlich N, Gulani V. Perfusion MR Imaging of Liver: Principles and Clinical Applications. Magn Reson Imaging Clin N Am 2024; 32:151-160. [PMID: 38007277 DOI: 10.1016/j.mric.2023.09.003] [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: 11/27/2023]
Abstract
Perfusion imaging techniques provide quantitative characterization of tissue microvasculature. Perfusion MR of liver is particularly challenging because of dual afferent flow, need for large organ high-resolution coverage, and significant movement with respiration. The most common MR technique used for quantifying liver perfusion is dynamic contrast-enhanced MR imaging. Here, the authors describe the various perfusion MR models of the liver, the basic concepts behind implementing a perfusion acquisition, and clinical results that have been obtained using these models.
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Affiliation(s)
- Anupama Ramachandran
- Brigham and Women's Hospital, Harvard University, Boston, MA, USA; Department of Radiology, University of Michigan, AnnArbor, MI, USA
| | - Hero Hussain
- Department of Radiology, University of Michigan, AnnArbor, MI, USA
| | | | - Vikas Gulani
- Department of Radiology, University of Michigan, AnnArbor, MI, USA.
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Yun H, Kim J, Gandhe A, Nelson B, Hu JC, Gulani V, Margolis D, Schackman BR, Jalali A. Cost-Effectiveness of Annual Prostate MRI and Potential MRI-Guided Biopsy After Prostate-Specific Antigen Test Results. JAMA Netw Open 2023; 6:e2344856. [PMID: 38019516 PMCID: PMC10687655 DOI: 10.1001/jamanetworkopen.2023.44856] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 10/13/2023] [Indexed: 11/30/2023] Open
Abstract
Importance Magnetic resonance imaging (MRI) and potential MRI-guided biopsy enable enhanced identification of clinically significant prostate cancer. Despite proven efficacy, MRI and potential MRI-guided biopsy remain costly, and there is limited evidence regarding the cost-effectiveness of this approach in general and for different prostate-specific antigen (PSA) strata. Objective To examine the cost-effectiveness of integrating annual MRI and potential MRI-guided biopsy as part of clinical decision-making for men after being screened for prostate cancer compared with standard biopsy. Design, Setting, and Participants Using a decision analytic Markov cohort model, an economic evaluation was conducted projecting outcomes over 10 years for a hypothetical cohort of 65-year-old men in the US with 4 different PSA strata (<2.5 ng/mL, 2.5-4.0 ng/mL, 4.1-10.0 ng/mL, >10 ng/mL) identified by screening through Monte Carlo microsimulation with 10 000 trials. Model inputs for probabilities, costs in 2020 US dollars, and quality-adjusted life-years (QALYs) were from the literature and expert consultation. The model was specifically designed to reflect the US health care system, adopting a federal payer perspective (ie, Medicare). Exposures Magnetic resonance imaging with potential MRI-guided biopsy and standard biopsy. Main Outcomes and Measures Incremental cost-effectiveness ratios (ICERs) using a willingness-to-pay threshold of $100 000 per QALY was estimated. One-way and probabilistic sensitivity analyses were performed. Results For the 3 PSA strata of 2.5 ng/mL or greater, the MRI and potential MRI-guided biopsy strategy was cost-effective compared with standard biopsy (PSA 2.5-4.0 ng/mL: base-case ICER, $21 131/QALY; PSA 4.1-10.0 ng/mL: base-case ICER, $12 336/QALY; PSA >10.0 ng/mL: base-case ICER, $6000/QALY). Results varied depending on the diagnostic accuracy of MRI and potential MRI-guided biopsy. Results of probabilistic sensitivity analyses showed that the MRI and potential MRI-guided biopsy strategy was cost-effective at the willingness-to-pay threshold of $100 000 per QALY in a range between 76% and 81% of simulations for each of the 3 PSA strata of 2.5 ng/mL or more. Conclusions and Relevance This economic evaluation of a hypothetical cohort suggests that an annual MRI and potential MRI-guided biopsy was a cost-effective option from a US federal payer perspective compared with standard biopsy for newly eligible male Medicare beneficiaries with a serum PSA level of 2.5 ng/mL or more.
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Affiliation(s)
- Hyunkyung Yun
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York
- Department of Health Services, Policy & Practice, School of Public Health, Brown University, Providence, Rhode Island
| | - Jin Kim
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York
| | - Aishwarya Gandhe
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York
| | - Brianna Nelson
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York
| | - Jim C. Hu
- Department of Urology, Weill Cornell Medicine, Cornell University, New York, New York
| | - Vikas Gulani
- Department of Radiology, University of Michigan Health System, Ann Arbor
| | - Daniel Margolis
- Department of Radiology, Weill Cornell Medicine, Cornell University, New York, New York
| | - Bruce R. Schackman
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York
| | - Ali Jalali
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York
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Ontaneda D, Gulani V, Deshmane A, Shah A, Guruprakash DK, Jiang Y, Ma D, Fisher E, Rudick RA, Raza P, Kilbane M, Cohen JA, Sakaie K, Lowe MJ, Griswold MA, Nakamura K. Magnetic resonance fingerprinting in multiple sclerosis. Mult Scler Relat Disord 2023; 79:105024. [PMID: 37783196 DOI: 10.1016/j.msard.2023.105024] [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: 02/06/2023] [Revised: 08/15/2023] [Accepted: 09/23/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND In this cross sectional study, we used MRF to investigate tissue properties of normal-appearing white matter, gray matter, and lesions in relapsing remitting MS (n = 21), secondary progressive MS (n = 16) and healthy controls (n = 9). A FISP-based MRF sequence was used for acquisition, imaging time 5 min 15 s. MRF T1 and T2 relaxation times were measured from lesional tissue, normal-appearing frontal white matter, corpus callous, thalamus, and caudate. Differences between healthy controls and MS were examined using ANCOVA adjusted for age and sex. Spearman rank correlations were assessed between T1 and T2 relaxation times and clinical measures. OBJECTIVES To examine brain T1 and T2 values using magnetic resonance fingerprinting (MRF) in healthy controls and MS. METHODS The subjects included 21 relapsing-remitting (RR) MS, 16 secondary progressive (SP) MS, and 9 age- and sex-matched HC without manifest neurological disease participating in a longitudinal MRI study. A 3T/ FISP-based MRF sequence was acquired. Regions of interest were drawn for lesions and normal appearing white matter. ANCOVA adjusted for age and sex were used to compare the groups with significance set at 0.05. RESULTS A step-wise increase in T1 and T2 relaxation times was found between healthy controls, relapsing remitting MS, and secondary progressive MS. Significant differences were found in T1 and T2 between MS and healthy controls in the frontal normal-appearing white matter, corpus callosum, and thalamus (p < 0.04 for all). Significant differences in T1 and T2 between RR and SPMS were found in the frontal normal-appearing white matter and T2 lesions (p < 0.02 for all). T1 relaxation from the frontal normal-appearing white matter correlated with the Expanded Disability Status Scale [ρ = 0.62, p < 0.001], timed 25 foot walk (ρ = 0.45, p = 0.01), 9 hole peg test (ρ = 0.62, p < 0.001), and paced auditory serial addition test (ρ = -0.4, p = 0.01). CONCLUSION These results suggest that MRF may be a clinically feasible quantitative approach for characterizing tissue damage in MS.
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Affiliation(s)
- Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, United States.
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Michigan, United States
| | - Anagha Deshmane
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Amisha Shah
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, United States
| | - Deepti K Guruprakash
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, United States
| | - Yun Jiang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, United States; Department of Radiology, University of Michigan, Ann Arbor, United States
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, United States
| | - Elizabeth Fisher
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, United States
| | - Richard A Rudick
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, United States
| | - Praneeta Raza
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, United States
| | - Meghan Kilbane
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, United States
| | - Jeffrey A Cohen
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, United States
| | - Ken Sakaie
- Imaging Institute, Cleveland Clinic, Cleveland, United States
| | - Mark J Lowe
- Imaging Institute, Cleveland Clinic, Cleveland, United States
| | - Mark A Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, United States
| | - Kunio Nakamura
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, United States
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Sun D, Hadjiiski L, Gormley J, Chan HP, Caoili EM, Cohan RH, Alva A, Gulani V, Zhou C. Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors. Cancers (Basel) 2023; 15:4372. [PMID: 37686647 PMCID: PMC10486459 DOI: 10.3390/cancers15174372] [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: 07/20/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/10/2023] Open
Abstract
Accurate survival prediction for bladder cancer patients who have undergone radical cystectomy can improve their treatment management. However, the existing predictive models do not take advantage of both clinical and radiological imaging data. This study aimed to fill this gap by developing an approach that leverages the strengths of clinical (C), radiomics (R), and deep-learning (D) descriptors to improve survival prediction. The dataset comprised 163 patients, including clinical, histopathological information, and CT urography scans. The data were divided by patient into training, validation, and test sets. We analyzed the clinical data by a nomogram and the image data by radiomics and deep-learning models. The descriptors were input into a BPNN model for survival prediction. The AUCs on the test set were (C): 0.82 ± 0.06, (R): 0.73 ± 0.07, (D): 0.71 ± 0.07, (CR): 0.86 ± 0.05, (CD): 0.86 ± 0.05, and (CRD): 0.87 ± 0.05. The predictions based on D and CRD descriptors showed a significant difference (p = 0.007). For Kaplan-Meier survival analysis, the deceased and alive groups were stratified successfully by C (p < 0.001) and CRD (p < 0.001), with CRD predicting the alive group more accurately. The results highlight the potential of combining C, R, and D descriptors to accurately predict the survival of bladder cancer patients after cystectomy.
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Affiliation(s)
- Di Sun
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
| | - Lubomir Hadjiiski
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
| | - John Gormley
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
| | - Heang-Ping Chan
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
| | - Elaine M. Caoili
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
| | - Richard H. Cohan
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
| | - Ajjai Alva
- Department of Internal Medicine-Hematology/Oncology, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
| | - Chuan Zhou
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (L.H.); (J.G.); (H.-P.C.); (E.M.C.); (R.H.C.); (V.G.); (C.Z.)
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Lavrova A, Mishra S, Richardson J, Masotti M, Kurokawa R, Kurokawa M, Itriago-Leon P, Gulani V, McCracken B, Wright K, Hussain HK, Moritani T, Seiberlich N. Quality assessment of routine brain imaging at 0.55 T: initial experience in a clinical workflow. NMR Biomed 2023:e5017. [PMID: 37654047 DOI: 10.1002/nbm.5017] [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] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 06/20/2023] [Accepted: 07/16/2023] [Indexed: 09/02/2023]
Abstract
The purpose of this study was to assess the quality of clinical brain imaging in healthy subjects and patients on an FDA-approved commercial 0.55 T MRI scanner, and to provide information about the feasibility of using this scanner in a clinical workflow. In this IRB-approved study, brain examinations on the scanner were prospectively performed in 10 healthy subjects (February-April 2022) and retrospectively derived from 44 patients (February-July 2022). Images collected using the following pulse sequences were available for assessment: axial DWI (diffusion-weighted imaging), apparent diffusion coefficient maps, 2D axial fluid-attenuated inversion recovery images, axial susceptibility-weighted images (both magnitude and phase), sagittal T1 -weighted (T1w) Sampling Perfection with Application Optimized Contrast images, sagittal T1w MPRAGE (magnetization prepared rapid gradient echo) with contrast enhancement, axial T1w turbo spin echo (TSE) with and without contrast enhancement, and axial T2 -weighted TSE. Two readers retrospectively and independently evaluated image quality and specific anatomical features in a blinded fashion on a four-point Likert scale, with a score of 1 being unacceptable and 4 being excellent, and determined the ability to answer the clinical question in patients. For each category of image sequences, the mean, standard deviation, and percentage of unacceptable quality images (<2) were calculated. Acceptable (rating ≥ 2) image quality was achieved at 0.55 T in all sequences for patients and 85% of the sequences for healthy subjects. Radiologists were able to answer the clinical question in all patients scanned. In total, 50% of the sequences used in patients and about 60% of the sequences used in healthy subjects exhibited good (rating ≥ 3) image quality. Based on these findings, we conclude that diagnostic quality clinical brain images can be successfully collected on this commercial 0.55 T scanner, indicating that the routine brain imaging protocol may be deployed on this system in the clinical workflow.
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Affiliation(s)
- Anna Lavrova
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Shruti Mishra
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jacob Richardson
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Maria Masotti
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Ryo Kurokawa
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Mariko Kurokawa
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Brendan McCracken
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Katherine Wright
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Hero K Hussain
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Toshio Moritani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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Gaur S, Panda A, Fajardo JE, Hamilton J, Jiang Y, Gulani V. Magnetic Resonance Fingerprinting: A Review of Clinical Applications. Invest Radiol 2023; 58:561-577. [PMID: 37026802 PMCID: PMC10330487 DOI: 10.1097/rli.0000000000000975] [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: 04/08/2023]
Abstract
ABSTRACT Magnetic resonance fingerprinting (MRF) is an approach to quantitative magnetic resonance imaging that allows for efficient simultaneous measurements of multiple tissue properties, which are then used to create accurate and reproducible quantitative maps of these properties. As the technique has gained popularity, the extent of preclinical and clinical applications has vastly increased. The goal of this review is to provide an overview of currently investigated preclinical and clinical applications of MRF, as well as future directions. Topics covered include MRF in neuroimaging, neurovascular, prostate, liver, kidney, breast, abdominal quantitative imaging, cardiac, and musculoskeletal applications.
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Affiliation(s)
- Sonia Gaur
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
| | - Ananya Panda
- All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | | | - Jesse Hamilton
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
| | - Yun Jiang
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
| | - Vikas Gulani
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
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Young AM, Garver KA, Gulani V. From a Culture of Incivility to Virtuousness: A Call to Elevate Workplace Behaviors in Radiology. AJR Am J Roentgenol 2023; 220:604-605. [PMID: 36129225 DOI: 10.2214/ajr.22.28212] [Citation(s) in RCA: 1] [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] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Radiology has been identified as a subspecialty with exceptionally high rates of incivility among colleagues. Such behaviors are detrimental to the well-being, productivity, and retention of health care practitioners and to the quality of patient care. Addressing incivility has become imperative given current and anticipated staff shortages, yet research from positive organizational scholarship suggests a greater opportunity to be had. Going forward, we need not only to address incivility but also to build purpose-driven, compassionate, and supportive workplaces.
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Affiliation(s)
- Amy M Young
- Ross School of Business, University of Michigan, 701 Tappan St, Ann Arbor, MI 48109
- Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, MI
| | - Kimberly A Garver
- Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, MI
| | - Vikas Gulani
- Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, MI
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10
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Anazodo UC, Ng JJ, Ehiogu B, Obungoloch J, Fatade A, Mutsaerts HJMM, Secca MF, Diop M, Opadele A, Alexander DC, Dada MO, Ogbole G, Nunes R, Figueiredo P, Figini M, Aribisala B, Awojoyogbe BO, Aduluwa H, Sprenger C, Wagner R, Olakunle A, Romeo D, Sun Y, Fezeu F, Orunmuyi AT, Geethanath S, Gulani V, Nganga EC, Adeleke S, Ntobeuko N, Minja FJ, Webb AG, Asllani I, Dako F. A framework for advancing sustainable magnetic resonance imaging access in Africa. NMR Biomed 2023; 36:e4846. [PMID: 36259628 DOI: 10.1002/nbm.4846] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 10/03/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
Magnetic resonance imaging (MRI) technology has profoundly transformed current healthcare systems globally, owing to advances in hardware and software research innovations. Despite these advances, MRI remains largely inaccessible to clinicians, patients, and researchers in low-resource areas, such as Africa. The rapidly growing burden of noncommunicable diseases in Africa underscores the importance of improving access to MRI equipment as well as training and research opportunities on the continent. The Consortium for Advancement of MRI Education and Research in Africa (CAMERA) is a network of African biomedical imaging experts and global partners, implementing novel strategies to advance MRI access and research in Africa. Upon its inception in 2019, CAMERA sets out to identify challenges to MRI usage and provide a framework for addressing MRI needs in the region. To this end, CAMERA conducted a needs assessment survey (NAS) and a series of symposia at international MRI society meetings over a 2-year period. The 68-question NAS was distributed to MRI users in Africa and was completed by 157 clinicians and scientists from across Sub-Saharan Africa (SSA). On average, the number of MRI scanners per million people remained at less than one, of which 39% were obsolete low-field systems but still in use to meet daily clinical needs. The feasibility of coupling stable energy supplies from various sources has contributed to the growing number of higher-field (1.5 T) MRI scanners in the region. However, these systems are underutilized, with only 8% of facilities reporting clinical scans of 15 or more patients per day, per scanner. The most frequently reported MRI scans were neurological and musculoskeletal. The CAMERA NAS combined with the World Health Organization and International Atomic Energy Agency data provides the most up-to-date data on MRI density in Africa and offers a unique insight into Africa's MRI needs. Reported gaps in training, maintenance, and research capacity indicate ongoing challenges in providing sustainable high-value MRI access in SSA. Findings from the NAS and focused discussions at international MRI society meetings provided the basis for the framework presented here for advancing MRI capacity in SSA. While these findings pertain to SSA, the framework provides a model for advancing imaging needs in other low-resource settings.
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Affiliation(s)
- Udunna C Anazodo
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jinggang J Ng
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Boaz Ehiogu
- Lawson Health Research Institute, London, Ontario, Canada
| | | | | | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | | | - Mamadou Diop
- Lawson Health Research Institute, London, Ontario, Canada
- Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Abayomi Opadele
- Molecular and Cellular Dynamics Research, Graduate School of Biomedical Science and Engineering, Hokkaido University, Hokkaido, Japan
| | | | - Michael O Dada
- Department of Physics, Federal University of Technology, Minna, Niger State, Nigeria
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Ibadan, Nigeria
| | - Rita Nunes
- Department of Bioengineering, Instituto Superior, Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Patricia Figueiredo
- Department of Bioengineering, Instituto Superior, Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Matteo Figini
- Department of Computer Science, University College London, London, UK
| | | | - Bamidele O Awojoyogbe
- Department of Physics, Federal University of Technology, Minna, Niger State, Nigeria
| | | | - Christian Sprenger
- Department of Anesthesiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Rachel Wagner
- Mbarara University of Science and Technology, Mbarara, Uganda
- Department of Medical Biophysics, Western University, London, Ontario, Canada
| | | | - Dominic Romeo
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Yusha Sun
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Francis Fezeu
- Neurosurgery & Neurology, BRAIN Global, Salisbury, Maryland, USA
| | - Akintunde T Orunmuyi
- Department of Nuclear Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria
| | - Sairam Geethanath
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Sola Adeleke
- Department of Oncology, Guy's & St Thomas' Hospital, London, UK
| | - Ntusi Ntobeuko
- Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Frank J Minja
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Andrew G Webb
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Iris Asllani
- Department of Neuroscience, University of Sussex, Brighton, UK
- Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, New York, USA
| | - Farouk Dako
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- RAD-AID International, Chevy Chase, Maryland, USA
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11
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Tippareddy C, Onyewadume L, Sloan AE, Wang GM, Patil NT, Hu S, Barnholtz-Sloan JS, Boyacıoğlu R, Gulani V, Sunshine J, Griswold M, Ma D, Badve C. Novel 3D magnetic resonance fingerprinting radiomics in adult brain tumors: a feasibility study. Eur Radiol 2023; 33:836-844. [PMID: 35999374 DOI: 10.1007/s00330-022-09067-w] [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: 03/11/2022] [Revised: 06/16/2022] [Accepted: 07/27/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVES To test the feasibility of using 3D MRF maps with radiomics analysis and machine learning in the characterization of adult brain intra-axial neoplasms. METHODS 3D MRF acquisition was performed on 78 patients with newly diagnosed brain tumors including 33 glioblastomas (grade IV), 6 grade III gliomas, 12 grade II gliomas, and 27 patients with brain metastases. Regions of enhancing tumor, non-enhancing tumor, and peritumoral edema were segmented and radiomics analysis with gray-level co-occurrence matrices and gray-level run-length matrices was performed. Statistical analysis was performed to identify features capable of differentiating tumors based on type, grade, and isocitrate dehydrogenase (IDH1) status. Receiver operating curve analysis was performed and the area under the curve (AUC) was calculated for tumor classification and grading. For gliomas, Kaplan-Meier analysis for overall survival was performed using MRF T1 features from enhancing tumor region. RESULTS Multiple MRF T1 and T2 features from enhancing tumor region were capable of differentiating glioblastomas from brain metastases. Although no differences were identified between grade 2 and grade 3 gliomas, differentiation between grade 2 and grade 4 gliomas as well as between grade 3 and grade 4 gliomas was achieved. MRF radiomics features were also able to differentiate IDH1 mutant from the wild-type gliomas. Radiomics T1 features for enhancing tumor region in gliomas correlated to overall survival (p < 0.05). CONCLUSION Radiomics analysis of 3D MRF maps allows differentiating glioblastomas from metastases and is capable of differentiating glioblastomas from metastases and characterizing gliomas based on grade, IDH1 status, and survival. KEY POINTS • 3D MRF data analysis using radiomics offers novel tissue characterization of brain tumors. • 3D MRF with radiomics offers glioma characterization based on grade, IDH1 status, and overall patient survival.
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Affiliation(s)
- Charit Tippareddy
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, 11100 Euclid Ave, Cleveland, OH, 44106, USA
| | - Louisa Onyewadume
- Department of Neurosurgery, West Virginia University Health Sciences Center, Morgantown, WV, USA
| | - Andrew E Sloan
- Departments of Neurosurgery and Pathology, Seidman Cancer Center and Case Comprehensive Cancer Center, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Gi-Ming Wang
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Research and Education Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Nirav T Patil
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Siyuan Hu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Jill S Barnholtz-Sloan
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, MD, USA
- Trans-Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Rasim Boyacıoğlu
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, 11100 Euclid Ave, Cleveland, OH, 44106, USA
| | - Vikas Gulani
- Department of Radiology, Michigan Institute of Imaging Technology and Translation, Michigan Medicine, Ann Arbor, MI, USA
| | - Jeffrey Sunshine
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, 11100 Euclid Ave, Cleveland, OH, 44106, USA
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, 11100 Euclid Ave, Cleveland, OH, 44106, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Dan Ma
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, 11100 Euclid Ave, Cleveland, OH, 44106, USA
| | - Chaitra Badve
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, 11100 Euclid Ave, Cleveland, OH, 44106, USA.
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12
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Lo W, Bittencourt LK, Panda A, Jiang Y, Tokuda J, Seethamraju R, Tempany‐Afdhal C, Obmann V, Wright K, Griswold M, Seiberlich N, Gulani V. Multicenter Repeatability and Reproducibility of MR Fingerprinting in Phantoms and in Prostatic Tissue. Magn Reson Med 2022; 88:1818-1827. [PMID: 35713379 PMCID: PMC9469467 DOI: 10.1002/mrm.29264] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [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: 10/10/2021] [Revised: 02/15/2022] [Accepted: 03/22/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE To evaluate multicenter repeatability and reproducibility of T1 and T2 maps generated using MR fingerprinting (MRF) in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and in prostatic tissues. METHODS MRF experiments were performed on 5 different 3 Tesla MRI scanners at 3 different institutions: University Hospitals Cleveland Medical Center (Cleveland, OH), Brigham and Women's Hospital (Boston, MA) in the United States, and Diagnosticos da America (Rio de Janeiro, RJ) in Brazil. Raw MRF data were reconstructed using a Gadgetron-based MRF online reconstruction pipeline to yield quantitative T1 and T2 maps. The repeatability of T1 and T2 values over 6 measurements in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom was assessed to demonstrate intrascanner variation. The reproducibility between the 4 clinical scanners was assessed to demonstrate interscanner variation. The same-day test-retest normal prostate mean T1 and T2 values from peripheral zone and transitional zone were also compared using the intraclass correlation coefficient and Bland-Altman analysis. RESULTS The intrascanner variation of values measured using MRF was less than 2% for T1 and 4.7% for T2 for relaxation values, within the range of 307.7 to 2360 ms for T1 and 19.1 to 248.5 ms for T2 . Interscanner measurements showed that the T1 variation was less than 4.9%, and T2 variation was less than 8.1% between multicenter scanners. Both T1 and T2 values in in vivo prostatic tissue demonstrated high test-retest reliability (intraclass correlation coefficient > 0.92) and strong linear correlation (R2 > 0.840). CONCLUSION Prostate MRF measurements of T1 and T2 are repeatable and reproducible between MRI scanners at different centers on different continents for the above measurement ranges.
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Affiliation(s)
- Wei‐Ching Lo
- Department of Biomedical EngineeringCase Western Reserve UniversityClevelandOhio
- Siemens Medical Solutions IncBostonMassachusetts
| | - Leonardo Kayat Bittencourt
- Department of RadiologyUniversity Hospital and Case Western Reserve UniversityClevelandOhio
- DASA companyRio de JaneiroRJBrazil
| | - Ananya Panda
- Department of RadiologyMayo ClinicRochesterMinnesota
| | - Yun Jiang
- Department of RadiologyUniversity of MichiganAnn ArborMichigan
| | - Junichi Tokuda
- Department of Radiology, Harvard Medical SchoolHarvard UniversityBostonMassachusetts
- Department of RadiologyBrigham and Women's HospitalBostonMassachusetts
| | | | - Clare Tempany‐Afdhal
- Department of Radiology, Harvard Medical SchoolHarvard UniversityBostonMassachusetts
- Department of RadiologyBrigham and Women's HospitalBostonMassachusetts
| | - Verena Obmann
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital BernUniversity of BernBerneSwitzerland
| | | | - Mark Griswold
- Department of Biomedical EngineeringCase Western Reserve UniversityClevelandOhio
- Department of RadiologyUniversity Hospital and Case Western Reserve UniversityClevelandOhio
| | | | - Vikas Gulani
- Department of RadiologyUniversity of MichiganAnn ArborMichigan
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13
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Lo WC, Panda A, Jiang Y, Ahad J, Gulani V, Seiberlich N. MR fingerprinting of the prostate. MAGMA 2022; 35:557-571. [PMID: 35419668 DOI: 10.1007/s10334-022-01012-8] [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] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 03/21/2022] [Accepted: 03/24/2022] [Indexed: 06/03/2023]
Abstract
Multiparametric magnetic resonance imaging (mpMRI) has been adopted as the key tool for detection, localization, characterization, and risk stratification of patients suspected to have prostate cancer. Despite advantages over systematic biopsy, the interpretation of prostate mpMRI has limitations including a steep learning curve, leading to considerable interobserver variation. There is growing interest in clinical translation of quantitative imaging techniques for more objective lesion assessment. However, traditional mapping techniques are slow, precluding their use in the clinic. Magnetic resonance fingerprinting (MRF) is an efficient approach for quantitative maps of multiple tissue properties simultaneously. The T1 and T2 values obtained with MRF have been validated with phantom studies as well as in normal volunteers and patients. Studies have shown that MRF-derived T1 and T2 along with ADC values are all significant independent predictors in the differentiation between normal prostate tissue and prostate cancer, and hold promise in differentiating low and intermediate/high-grade cancers. This review seeks to introduce the basics of the prostate MRF technique, discuss the potential applications of prostate MRF for the characterization of prostate cancer, and describes ongoing areas of research.
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Affiliation(s)
- Wei-Ching Lo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Ananya Panda
- Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, MN, 55905, USA
| | - Yun Jiang
- Department of Radiology, University of Michigan, University of Michigan Health System, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5030, USA
| | - James Ahad
- Case Western Reserve University, Cleveland, OH, USA
| | - Vikas Gulani
- Department of Radiology, University of Michigan, University of Michigan Health System, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5030, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, University of Michigan Health System, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5030, USA.
- Case Western Reserve University, Cleveland, OH, USA.
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14
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Collins JD, Rowley H, Leiner T, Reeder S, Hood M, Dekkers I, Tha K, Gulani V, Kopanoglu E. Magnetic Resonance Imaging During a Pandemic: Recommendations by the ISMRM Safety Committee. J Magn Reson Imaging 2021; 55:1322-1339. [PMID: 34927776 DOI: 10.1002/jmri.28006] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 11/15/2021] [Accepted: 11/16/2021] [Indexed: 01/23/2023] Open
Abstract
The COVID-19 pandemic highlighted the challenges delivering face-to-face patient care across healthcare systems. In particular the COVID-19 pandemic challenged the imaging community to provide timely access to essential diagnostic imaging modalities while ensuring appropriate safeguards were in place for both patients and personnel. With increasing vaccine availability and greater prevalence of vaccination in communities worldwide we are finally emerging on the other side of the COVID-19 pandemic. As we learned from our institutional and healthcare system responses to the pandemic, maintaining timely access to MR imaging is essential. Radiologists and other imaging providers partnered with their referring providers to ensure that timely access to advanced MR imaging was maintained. On behalf of the International Magnetic Resonance in Medicine (ISMRM) Safety Committee, this white paper is intended to serve as a guide for radiology departments, imaging centers, and other imaging specialists who perform MR imaging to refer to as we prepare for the next pandemic. Lessons learned including strategies to triage and prioritize MR imaging research during a pandemic are discussed. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
| | - Howard Rowley
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - Tim Leiner
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Scott Reeder
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - Maureen Hood
- Department of Radiology, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
| | - Ilona Dekkers
- Department of Radiology, Leids University Medical Center, Leiden, The Netherlands
| | - Khin Tha
- Global Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Sapporo, Japan
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Emre Kopanoglu
- CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
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15
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Franson D, Dupuis A, Gulani V, Griswold M, Seiberlich N. A System for Real-Time, Online Mixed-Reality Visualization of Cardiac Magnetic Resonance Images. J Imaging 2021; 7:jimaging7120274. [PMID: 34940741 PMCID: PMC8709155 DOI: 10.3390/jimaging7120274] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/07/2021] [Accepted: 12/09/2021] [Indexed: 11/16/2022] Open
Abstract
Image-guided cardiovascular interventions are rapidly evolving procedures that necessitate imaging systems capable of rapid data acquisition and low-latency image reconstruction and visualization. Compared to alternative modalities, Magnetic Resonance Imaging (MRI) is attractive for guidance in complex interventional settings thanks to excellent soft tissue contrast and large fields-of-view without exposure to ionizing radiation. However, most clinically deployed MRI sequences and visualization pipelines exhibit poor latency characteristics, and spatial integration of complex anatomy and device orientation can be challenging on conventional 2D displays. This work demonstrates a proof-of-concept system linking real-time cardiac MR image acquisition, online low-latency reconstruction, and a stereoscopic display to support further development in real-time MR-guided intervention. Data are acquired using an undersampled, radial trajectory and reconstructed via parallelized through-time radial generalized autocalibrating partially parallel acquisition (GRAPPA) implemented on graphics processing units. Images are rendered for display in a stereoscopic mixed-reality head-mounted display. The system is successfully tested by imaging standard cardiac views in healthy volunteers. Datasets comprised of one slice (46 ms), two slices (92 ms), and three slices (138 ms) are collected, with the acquisition time of each listed in parentheses. Images are displayed with latencies of 42 ms/frame or less for all three conditions. Volumetric data are acquired at one volume per heartbeat with acquisition times of 467 ms and 588 ms when 8 and 12 partitions are acquired, respectively. Volumes are displayed with a latency of 286 ms or less. The faster-than-acquisition latencies for both planar and volumetric display enable real-time 3D visualization of the heart.
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Affiliation(s)
- Dominique Franson
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA;
- Correspondence: (D.F.); (A.D.)
| | - Andrew Dupuis
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA;
- Correspondence: (D.F.); (A.D.)
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (V.G.); (N.S.)
| | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA;
- Department of Radiology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; (V.G.); (N.S.)
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16
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Shiradkar R, Panda A, Leo P, Janowczyk A, Farre X, Janaki N, Li L, Pahwa S, Mahran A, Buzzy C, Fu P, Elliott R, MacLennan G, Ponsky L, Gulani V, Madabhushi A. Correction to: T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology. Eur Radiol 2020; 31:2644. [PMID: 32945970 DOI: 10.1007/s00330-020-07285-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Rakesh Shiradkar
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA.
| | - Ananya Panda
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Patrick Leo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Andrew Janowczyk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Xavier Farre
- Department of Public Health, Public Health Agency of Catalonia, Lleida, Catalonia, Spain
| | - Nafiseh Janaki
- Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lin Li
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Shivani Pahwa
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Amr Mahran
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Christina Buzzy
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Pingfu Fu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Robin Elliott
- Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Gregory MacLennan
- Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Lee Ponsky
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Vikas Gulani
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Anant Madabhushi
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
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17
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Vigen KK, Reeder SB, Hood MN, Steckner M, Leiner T, Dombroski DA, Gulani V. Recommendations for Imaging Patients With Cardiac Implantable Electronic Devices (CIEDs). J Magn Reson Imaging 2020; 53:1311-1317. [PMID: 32808391 DOI: 10.1002/jmri.27320] [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: 05/26/2020] [Revised: 07/21/2020] [Accepted: 07/22/2020] [Indexed: 11/08/2022] Open
Abstract
Historically, the presence of cardiac implantable electronic devices (CIEDs), including pacemakers and implantable cardioverter defibrillators (ICDs), was widely considered an absolute contraindication to magnetic resonance imaging (MRI). The recent development of CIEDs with MR Conditional labeling, as well as encouraging results from retrospective studies and a prospective trial on the safety of MRI performed in patients with CIEDs without MR Conditional labeling, have led to a reevaluation of this practice. The purpose of this report is to provide a concise summary of recent developments, including practical guidelines that an institution could adopt for radiologists who choose to image patients with CIEDs that do not have MR Conditional labeling. This report was written on behalf of and approved by the International Society for Magnetic Resonance in Medicine (ISMRM) Safety Committee. LEVEL OF EVIDENCE: 3. TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Karl K Vigen
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Scott B Reeder
- Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Maureen N Hood
- Department of Radiology & Radiological Sciences, Uniformed Services University, Bethesda, Maryland, USA
| | | | - Tim Leiner
- Department of Radiology, Utrecht University Medical Center, Utrecht, The Netherlands
| | - David A Dombroski
- Department of Radiology, University of Rochester Medical Center, Rochester, New York, USA
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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18
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Ghodasara S, Chen Y, Pahwa S, Griswold MA, Seiberlich N, Wright KL, Gulani V. Quantifying Perfusion Properties with DCE-MRI Using a Dictionary Matching Approach. Sci Rep 2020; 10:10210. [PMID: 32576843 PMCID: PMC7311534 DOI: 10.1038/s41598-020-66985-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 05/25/2020] [Indexed: 12/18/2022] Open
Abstract
Perfusion properties can be estimated from pharmacokinetic models applied to DCE-MRI data using curve fitting algorithms; however, these suffer from drawbacks including the local minimum problem and substantial computational time. Here, a dictionary matching approach is proposed as an alternative. Curve fitting and dictionary matching were applied to simulated data using the dual-input single-compartment model with known perfusion property values and 5 in vivo DCE-MRI datasets. In simulation at SNR 60 dB, the dictionary estimate had a mean percent error of 0.4-1.0% for arterial fraction, 0.5-1.4% for distribution volume, and 0.0% for mean transit time. The curve fitting estimate had a mean percent error of 1.1-2.1% for arterial fraction, 0.5-1.3% for distribution volume, and 0.2-1.8% for mean transit time. In vivo, dictionary matching and curve fitting showed no statistically significant differences in any of the perfusion property measurements in any of the 10 ROIs between the methods. In vivo, the dictionary method performed over 140-fold faster than curve fitting, obtaining whole volume perfusion maps in just over 10 s. This study establishes the feasibility of using a dictionary matching approach as a new and faster way of estimating perfusion properties from pharmacokinetic models in DCE-MRI.
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Affiliation(s)
- Satyam Ghodasara
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yong Chen
- Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Shivani Pahwa
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Mark A Griswold
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Katherine L Wright
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
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McGivney DF, Boyacioğlu R, Jiang Y, Poorman ME, Seiberlich N, Gulani V, Keenan KE, Griswold MA, Ma D. Magnetic resonance fingerprinting review part 2: Technique and directions. J Magn Reson Imaging 2020; 51:993-1007. [PMID: 31347226 PMCID: PMC6980890 DOI: 10.1002/jmri.26877] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [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: 04/30/2019] [Revised: 07/05/2019] [Accepted: 07/05/2019] [Indexed: 12/12/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) is a general framework to quantify multiple MR-sensitive tissue properties with a single acquisition. There have been numerous advances in MRF in the years since its inception. In this work we highlight some of the recent technical developments in MRF, focusing on sequence optimization, modifications for reconstruction and pattern matching, new methods for partial volume analysis, and applications of machine and deep learning. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:993-1007.
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Affiliation(s)
- Debra F. McGivney
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Rasim Boyacioğlu
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Megan E. Poorman
- Department of Physics, University of Colorado Boulder, Boulder, Colorado, USA
- Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Kathryn E. Keenan
- Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Mark A. Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
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Hamilton JI, Pahwa S, Adedigba J, Frankel S, O'Connor G, Thomas R, Walker JR, Killinc O, Lo WC, Batesole J, Margevicius S, Griswold M, Rajagopalan S, Gulani V, Seiberlich N. Simultaneous Mapping of T 1 and T 2 Using Cardiac Magnetic Resonance Fingerprinting in a Cohort of Healthy Subjects at 1.5T. J Magn Reson Imaging 2020; 52:1044-1052. [PMID: 32222092 DOI: 10.1002/jmri.27155] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 03/13/2020] [Accepted: 03/13/2020] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Cardiac MR fingerprinting (cMRF) is a novel technique for simultaneous T1 and T2 mapping. PURPOSE To compare T1 /T2 measurements, repeatability, and map quality between cMRF and standard mapping techniques in healthy subjects. STUDY TYPE Prospective. POPULATION In all, 58 subjects (ages 18-60). FIELD STRENGTH/SEQUENCE: cMRF, modified Look-Locker inversion recovery (MOLLI), and T2 -prepared balanced steady-state free precession (bSSFP) at 1.5T. ASSESSMENT T1 /T2 values were measured in 16 myocardial segments at apical, medial, and basal slice positions. Test-retest and intrareader repeatability were assessed for the medial slice. cMRF and conventional mapping sequences were compared using ordinal and two alternative forced choice (2AFC) ratings. STATISTICAL TESTS Paired t-tests, Bland-Altman analyses, intraclass correlation coefficient (ICC), linear regression, one-way analysis of variance (ANOVA), and binomial tests. RESULTS Average T1 measurements were: basal 1007.4±96.5 msec (cMRF), 990.0±45.3 msec (MOLLI); medial 995.0±101.7 msec (cMRF), 995.6±59.7 msec (MOLLI); apical 1006.6±111.2 msec (cMRF); and 981.6±87.6 msec (MOLLI). Average T2 measurements were: basal 40.9±7.0 msec (cMRF), 46.1±3.5 msec (bSSFP); medial 41.0±6.4 msec (cMRF), 47.4±4.1 msec (bSSFP); apical 43.5±6.7 msec (cMRF), 48.0±4.0 msec (bSSFP). A statistically significant bias (cMRF T1 larger than MOLLI T1 ) was observed in basal (17.4 msec) and apical (25.0 msec) slices. For T2 , a statistically significant bias (cMRF lower than bSSFP) was observed for basal (-5.2 msec), medial (-6.3 msec), and apical (-4.5 msec) slices. Precision was lower for cMRF-the average of the standard deviation measured within each slice was 102 msec for cMRF vs. 61 msec for MOLLI T1 , and 6.4 msec for cMRF vs. 4.0 msec for bSSFP T2 . cMRF and conventional techniques had similar test-retest repeatability as quantified by ICC (0.87 cMRF vs. 0.84 MOLLI for T1 ; 0.85 cMRF vs. 0.85 bSSFP for T2 ). In the ordinal image quality comparison, cMRF maps scored higher than conventional sequences for both T1 (all five features) and T2 (four features). DATA CONCLUSION This work reports on myocardial T1 /T2 measurements in healthy subjects using cMRF and standard mapping sequences. cMRF had slightly lower precision, similar test-retest and intrareader repeatability, and higher scores for map quality. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;52:1044-1052.
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Affiliation(s)
- Jesse I Hamilton
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Shivani Pahwa
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Joseph Adedigba
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Samuel Frankel
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Gregory O'Connor
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Rahul Thomas
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Jonathan R Walker
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Ozden Killinc
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Wei-Ching Lo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Joshua Batesole
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Seunghee Margevicius
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Sanjay Rajagopalan
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Division of Cardiovascular Medicine, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
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21
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Jordan D, Gulani V. Editorial on "ACR Guidance Document on MR Safe Practices: Updates and Critical Information 2019". J Magn Reson Imaging 2020; 51:339-340. [DOI: 10.1002/jmri.26990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Accepted: 10/22/2019] [Indexed: 11/10/2022] Open
Affiliation(s)
- David Jordan
- From the Department of Radiology University Hospitals Cleveland Medical Center Cleveland Ohio USA
| | - Vikas Gulani
- Department of Radiology University of Michigan Ann Arbor Michigan USA
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Gulani V, Seiberlich N. Quantitative MRI: Rationale and Challenges. ACTA ACUST UNITED AC 2020. [DOI: 10.1016/b978-0-12-817057-1.00001-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
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23
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Panda A, Obmann VC, Lo WC, Margevicius S, Jiang Y, Schluchter M, Patel IJ, Nakamoto D, Badve C, Griswold MA, Jaeger I, Ponsky LE, Gulani V. MR Fingerprinting and ADC Mapping for Characterization of Lesions in the Transition Zone of the Prostate Gland. Radiology 2019; 292:685-694. [PMID: 31335285 PMCID: PMC6716564 DOI: 10.1148/radiol.2019181705] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 05/11/2019] [Accepted: 06/13/2019] [Indexed: 11/11/2022]
Abstract
BackgroundPreliminary studies have shown that MR fingerprinting-based relaxometry combined with apparent diffusion coefficient (ADC) mapping can be used to differentiate normal peripheral zone from prostate cancer and prostatitis. The utility of relaxometry and ADC mapping for the transition zone (TZ) is unknown.PurposeTo evaluate the utility of MR fingerprinting combined with ADC mapping for characterizing TZ lesions.Materials and MethodsTZ lesions that were suspicious for cancer in men who underwent MRI with T2-weighted imaging and ADC mapping (b values, 50-1400 sec/mm2), MR fingerprinting with steady-state free precession, and targeted biopsy (60 in-gantry and 15 cognitive targeting) between September 2014 and August 2018 in a single university hospital were retrospectively analyzed. Two radiologists blinded to Prostate Imaging Reporting and Data System (PI-RADS) scores and pathologic diagnosis drew regions of interest on cancer-suspicious lesions and contralateral visually normal TZs (NTZs) on MR fingerprinting and ADC maps. Linear mixed models compared two-reader means of T1, T2, and ADC. Generalized estimating equations logistic regression analysis was used to evaluate both MR fingerprinting and ADC in differentiating NTZ, cancers and noncancers, clinically significant (Gleason score ≥ 7) cancers from clinically insignificant lesions (noncancers and Gleason 6 cancers), and characterizing PI-RADS version 2 category 3 lesions.ResultsIn 67 men (mean age, 66 years ± 8 [standard deviation]) with 75 lesions, targeted biopsy revealed 37 cancers (six PI-RADS category 3 cancers and 31 PI-RADS category 4 or 5 cancers) and 38 noncancers (31 PI-RADS category 3 lesions and seven PI-RADS category 4 or 5 lesions). The T1, T2, and ADC of NTZ (1800 msec ± 150, 65 msec ± 22, and [1.13 ± 0.19] × 10-3 mm2/sec, respectively) were higher than those in cancers (1450 msec ± 110, 36 msec ± 11, and [0.57 ± 0.13] × 10-3 mm2/sec, respectively; P < .001 for all). The T1, T2, and ADC in cancers were lower than those in noncancers (1620 msec ± 120, 47 msec ± 16, and [0.82 ± 0.13] × 10-3 mm2/sec, respectively; P = .001 for T1 and ADC and P = .03 for T2). The area under the receiver operating characteristic curve (AUC) for T1 plus ADC was 0.94 for separation. T1 and ADC in clinically significant cancers (1440 msec ± 140 and [0.58 ± 0.14] × 10-3 mm2/sec, respectively) were lower than those in clinically insignificant lesions (1580 msec ± 120 and [0.75 ± 0.17] × 10-3 mm2/sec, respectively; P = .001 for all). The AUC for T1 plus ADC was 0.81 for separation. Within PI-RADS category 3 lesions, T1 and ADC of cancers (1430 msec ± 220 and [0.60 ± 0.17] × 10-3 mm2/sec, respectively) were lower than those of noncancers (1630 msec ± 120 and [0.81 ± 0.13] × 10-3 mm2/sec, respectively; P = .006 for T1 and P = .004 for ADC). The AUC for T1 was 0.79 for differentiating category 3 lesions.ConclusionMR fingerprinting-based relaxometry combined with apparent diffusion coefficient mapping may improve transition zone lesion characterization.© RSNA, 2019Online supplemental material is available for this article.
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Affiliation(s)
- Ananya Panda
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Verena C. Obmann
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Wei-Ching Lo
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Seunghee Margevicius
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Yun Jiang
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Mark Schluchter
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Indravadan J. Patel
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Dean Nakamoto
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Chaitra Badve
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Mark A. Griswold
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Irina Jaeger
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Lee E. Ponsky
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Vikas Gulani
- From the Department of Radiology, Mayo Clinic, Rochester, Minn (A.P.); Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (V.C.O.); Departments of Biomedical Engineering (W.C.L., M.A.G.), Epidemiology and Biostatistics (S.M., M.S.), and Radiology (Y.J., C.B., M.A.G., V.G.), Case Western Reserve University, Cleveland, Ohio; Department of Radiology, University of Michigan, UH B1 G503, 1500 E. Medical Center Drive, SPC 5030, Ann Arbor, MI 48109-5030 (Y.J., V.G.); Department of Radiology, Mayo Clinic, Phoenix, Az (I.J.P.); Departments of Radiology (I.J.P., D.N., C.B., M.A.G.) and Urology (I.J., L.E.P.), University Hospitals Cleveland Medical Center, Cleveland, Ohio
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Panda A, O’Connor G, Lo WC, Jiang Y, Margevicius S, Schluchter M, Ponsky LE, Gulani V. Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping. Invest Radiol 2019; 54:485-493. [PMID: 30985480 PMCID: PMC6602844 DOI: 10.1097/rli.0000000000000569] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [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: 01/08/2023]
Abstract
OBJECTIVE This study aims for targeted biopsy validation of magnetic resonance fingerprinting (MRF) and diffusion mapping for characterizing peripheral zone (PZ) prostate cancer and noncancers. MATERIALS AND METHODS One hundred four PZ lesions in 85 patients who underwent magnetic resonance imaging were retrospectively analyzed with apparent diffusion coefficient (ADC) mapping, MRF, and targeted biopsy (cognitive or in-gantry). A radiologist blinded to pathology drew regions of interest on targeted lesions and visually normal peripheral zone on MRF and ADC maps. Mean T1, T2, and ADC were analyzed using linear mixed models. Generalized estimating equations logistic regression analyses were used to evaluate T1 and T2 relaxometry combined with ADC in differentiating pathologic groups. RESULTS Targeted biopsy revealed 63 cancers (low-grade cancer/Gleason score 6 = 10, clinically significant cancer/Gleason score ≥7 = 53), 15 prostatitis, and 26 negative biopsies. Prostate cancer T1, T2, and ADC (mean ± SD, 1660 ± 270 milliseconds, 56 ± 20 milliseconds, 0.70 × 10 ± 0.24 × 10 mm/s) were significantly lower than prostatitis (mean ± SD, 1730 ± 350 milliseconds, 77 ± 36 milliseconds, 1.00 × 10 ± 0.30 × 10 mm/s) and negative biopsies (mean ± SD, 1810 ± 250 milliseconds, 71 ± 37 milliseconds, 1.00 × 10 ± 0.33 × 10 mm/s). For cancer versus prostatitis, ADC was sensitive and T2 specific with comparable area under curve (AUC; (AUCT2 = 0.71, AUCADC = 0.79, difference between AUCs not significant P = 0.37). T1 + ADC (AUCT1 + ADC = 0.83) provided the best separation between cancer and negative biopsies. Low-grade cancer T2 and ADC (mean ± SD, 75 ± 29 milliseconds, 0.96 × 10 ± 0.34 × 10 mm/s) were significantly higher than clinically significant cancers (mean ± SD, 52 ± 16 milliseconds, 0.65 ± 0.18 × 10 mm/s), and T2 + ADC (AUCT2 + ADC = 0.91) provided the best separation. CONCLUSIONS T1 and T2 relaxometry combined with ADC mapping may be useful for quantitative characterization of prostate cancer grades and differentiating cancer from noncancers for PZ lesions seen on T2-weighted images.
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Affiliation(s)
- Ananya Panda
- Department of Radiology, Mayo Clinic, Rochester, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Gregory O’Connor
- Department of Case Western University School of Medicine, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Wei-Ching Lo
- Department of Biomedical Engineering, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Seunghee Margevicius
- Department of Epidemiology and Biostatistics, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Mark Schluchter
- Department of Epidemiology and Biostatistics, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Lee E. Ponsky
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Case Western University School of Medicine, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
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Poorman ME, Martin MN, Ma D, McGivney DF, Gulani V, Griswold MA, Keenan KE. Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations. J Magn Reson Imaging 2019; 51:675-692. [PMID: 31264748 DOI: 10.1002/jmri.26836] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [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: 03/30/2019] [Accepted: 05/31/2019] [Indexed: 12/11/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) is a powerful quantitative MRI technique capable of acquiring multiple property maps simultaneously in a short timeframe. The MRF framework has been adapted to a wide variety of clinical applications, but faces challenges in technical development, and to date has only demonstrated repeatability and reproducibility in small studies. In this review, we discuss the current implementations of MRF and their use in a clinical setting. Based on this analysis, we highlight areas of need that must be addressed before MRF can be fully adopted into the clinic and make recommendations to the MRF community on standardization and validation strategies of MRF techniques. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:675-692.
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Affiliation(s)
- Megan E. Poorman
- Department of PhysicsUniversity of Colorado Boulder Boulder Colorado USA
- Physical Measurement LaboratoryNational Institute of Standards and Technology Boulder Colorado USA
| | - Michele N. Martin
- Physical Measurement LaboratoryNational Institute of Standards and Technology Boulder Colorado USA
| | - Dan Ma
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Debra F. McGivney
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Vikas Gulani
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Mark A. Griswold
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Kathryn E. Keenan
- Physical Measurement LaboratoryNational Institute of Standards and Technology Boulder Colorado USA
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Körzdörfer G, Kirsch R, Liu K, Pfeuffer J, Hensel B, Jiang Y, Ma D, Gratz M, Bär P, Bogner W, Springer E, Lima Cardoso P, Umutlu L, Trattnig S, Griswold M, Gulani V, Nittka M. Reproducibility and Repeatability of MR Fingerprinting Relaxometry in the Human Brain. Radiology 2019; 292:429-437. [PMID: 31210615 DOI: 10.1148/radiol.2019182360] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Only sparse literature investigates the reproducibility and repeatability of relaxometry methods in MRI. However, statistical data on reproducibility and repeatability of any quantitative method is essential for clinical application. Purpose To evaluate the reproducibility and repeatability of two-dimensional fast imaging with steady-state free precession MR fingerprinting in vivo in human brains. Materials and Methods Two-dimensional section-selective MR fingerprinting based on a steady-state free precession sequence with an external radiofrequency transmit field, or B1+, correction was used to generate T1 and T2 maps. This prospective study was conducted between July 2017 and January 2018 with 10 scanners from a single manufacturer, including different models, at four different sites. T1 and T2 relaxation times and their variation across scanners (reproducibility) as well as across repetitions on a scanner (repeatability) were analyzed. The relative deviations of T1 and T2 to the average (95% confidence interval) were calculated for several brain compartments. Results Ten healthy volunteers (mean age ± standard deviation, 28.5 years ± 6.9; eight men, two women) participated in this study. Reproducibility and repeatability of T1 and T2 measures in the human brain varied across brain compartments (1.8%-20.9%) and were higher in solid tissues than in the cerebrospinal fluid. T1 measures in solid tissue brain compartments were more stable compared with T2 measures. The half-widths of the confidence intervals for relative deviations were 3.4% for mean T1 and 8.0% for mean T2 values across scanners. Intrascanner repeatability half-widths of the confidence intervals for relative deviations were in the range of 2.0%-3.1% for T1 and 3.1%-7.9% for T2. Conclusion This study provides values on reproducibility and repeatability of T1 and T2 relaxometry measured with fast imaging with steady-state free precession MR fingerprinting in brain tissues of healthy volunteers. Reproducibility and repeatability are considerably higher in solid brain compartments than in cerebrospinal fluid and are higher for T1 than for T2. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Barkhof and Parker in this issue.
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Affiliation(s)
- Gregor Körzdörfer
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Rainer Kirsch
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Kecheng Liu
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Josef Pfeuffer
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Bernhard Hensel
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Yun Jiang
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Dan Ma
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Marcel Gratz
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Peter Bär
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Wolfgang Bogner
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Elisabeth Springer
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Pedro Lima Cardoso
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Lale Umutlu
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Siegfried Trattnig
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Mark Griswold
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Vikas Gulani
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Mathias Nittka
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
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Cavallo AU, Liu Y, Patterson A, Al-Kindi S, Hamilton J, Gilkeson R, Gulani V, Seiberlich N, Rajagopalan S. CMR Fingerprinting for Myocardial T1, T2, and ECV Quantification in Patients With Nonischemic Cardiomyopathy. JACC Cardiovasc Imaging 2019; 12:1584-1585. [PMID: 31103583 DOI: 10.1016/j.jcmg.2019.01.034] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 12/11/2018] [Accepted: 01/16/2019] [Indexed: 12/01/2022]
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Mahran A, Mishra K, Bukavina L, Schumacher F, Quian A, Buzzy C, Nguyen CT, Gulani V, Ponsky LE. Observed racial disparity in the negative predictive value of multi-parametric MRI for the diagnosis for prostate cancer. Int Urol Nephrol 2019; 51:1343-1348. [DOI: 10.1007/s11255-019-02158-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 04/20/2019] [Indexed: 12/31/2022]
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Deshmane A, McGivney DF, Ma D, Jiang Y, Badve C, Gulani V, Seiberlich N, Griswold MA. Partial volume mapping using magnetic resonance fingerprinting. NMR Biomed 2019; 32:e4082. [PMID: 30821878 DOI: 10.1002/nbm.4082] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 01/21/2019] [Accepted: 01/23/2019] [Indexed: 06/09/2023]
Abstract
Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that maps multiple tissue properties through pseudorandom signal excitation and dictionary-based reconstruction. The aim of this study is to estimate and validate partial volumes from MRF signal evolutions (PV-MRF), and to characterize possible sources of error. Partial volume model inversion (pseudoinverse) and dictionary-matching approaches to calculate brain tissue fractions (cerebrospinal fluid, gray matter, white matter) were compared in a numerical phantom and seven healthy subjects scanned at 3 T. Results were validated by comparison with ground truth in simulations and ROI analysis in vivo. Simulations investigated tissue fraction errors arising from noise, undersampling artifacts, and model errors. An expanded partial volume model was investigated in a brain tumor patient. PV-MRF with dictionary matching is robust to noise, and estimated tissue fractions are sensitive to model errors. A 6% error in pure tissue T1 resulted in average absolute tissue fraction error of 4% or less. A partial volume model within these accuracy limits could be semi-automatically constructed in vivo using k-means clustering of MRF-mapped relaxation times. Dictionary-based PV-MRF robustly identifies pure white matter, gray matter and cerebrospinal fluid, and partial volumes in subcortical structures. PV-MRF could also estimate partial volumes of solid tumor and peritumoral edema. We conclude that PV-MRF can attribute subtle changes in relaxation times to altered tissue composition, allowing for quantification of specific tissues which occupy a fraction of a voxel.
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Affiliation(s)
- Anagha Deshmane
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | | | - Dan Ma
- Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Yun Jiang
- Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Chaitra Badve
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Vikas Gulani
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Nicole Seiberlich
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Mark A Griswold
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
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Panda A, Chen Y, Ropella-Panagis K, Ghodasara S, Stopchinski M, Seyfried N, Wright K, Seiberlich N, Griswold M, Gulani V. Repeatability and reproducibility of 3D MR fingerprinting relaxometry measurements in normal breast tissue. J Magn Reson Imaging 2019; 50:1133-1143. [PMID: 30892807 DOI: 10.1002/jmri.26717] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [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: 12/03/2018] [Revised: 02/27/2019] [Accepted: 02/28/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The 3D breast magnetic resonance fingerprinting (MRF) technique enables T1 and T2 mapping in breast tissues. Combined repeatability and reproducibility studies on breast T1 and T2 relaxometry are lacking. PURPOSE To assess test-retest and two-visit repeatability and interscanner reproducibility of the 3D breast MRF technique in a single-institution setting. STUDY TYPE Prospective. SUBJECTS Eighteen women (median age 29 years, range, 22-33 years) underwent Visit 1 scans on scanner 1. Ten of these women underwent test-retest scan repositioning after a 10-minute interval. Thirteen women had Visit 2 scans within 7-15 days in same menstrual cycle. The remaining five women had Visit 2 scans in the same menstrual phase in next menstrual cycle. Five women were also scanned on scanner 2 at both visits for interscanner reproducibility. FIELD STRENGTH/SEQUENCE Two 3T MR scanners with the 3D breast MRF technique. ASSESSMENT T1 and T2 MRF maps of both breasts. STATISTICAL TESTS Mean T1 and T2 values for normal fibroglandular tissues were quantified at all scans. For variability, between and within-subjects coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability was assessed with Bland-Altman analysis and coefficient of repeatability (CR). Reproducibility was assessed with interscanner coefficient of variation (CoV) and Wilcoxon signed-rank test. RESULTS The bCV at test-retest scans was 9-12% for T1 , 7-17% for T2 , wCV was <4% for T1 , and <7% for T2 . For two visits in same menstrual cycle, bCV was 10-15% for T1 , 13-17% for T2 , wCV was <7% for T1 and <5% for T2 . For two visits in the same menstrual phase, bCV was 6-14% for T1 , 15-18% for T2 , wCV was <7% for T1 , and <9% for T2 . For test-retest scans, CR for T1 and T2 were 130 msec and 11 msec. For two visit scans, CR was <290 msec for T1 and 10-14 msec for T2 . Interscanner CoV was 3.3-3.6% for T1 and 5.1-6.6% for T2 , with no differences between interscanner measurements (P = 1.00 for T1 , P = 0.344 for T2 ). DATA CONCLUSION 3D breast MRF measurements are repeatable across scan timings and scanners and may be useful in clinical applications in breast imaging. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1133-1143.
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Affiliation(s)
- Ananya Panda
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Yong Chen
- Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, USA.,Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, North Carolina, USA
| | | | - Satyam Ghodasara
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Marcie Stopchinski
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Nicole Seyfried
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Katherine Wright
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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Abstract
Magnetic Resonance Imaging (MRI) can be used to assess anatomical structure, and its sensitivity to a variety of tissue properties enables superb contrast between tissues as well as the ability to characterize these tissues. However, despite vast potential for quantitative and functional evaluation, MRI is typically used qualitatively, in which the underlying tissue properties are not measured, and thus the brightness of each pixel is not quantitatively meaningful. Positron Emission Tomography (PET) is an inherently quantitative imaging modality that interrogates functional activity within a tissue, probed by a molecule of interest coupled with an appropriate tracer. These modalities can complement one another to provide clinical information regarding both structure and function, but there are still technical and practical hurdles in the way of the integrated use of both modalities. Recent advances in MRI have moved the field in an increasingly quantitative direction, which is complementary to PET, and could also potentially help solve some of the challenges in PET/MR. Magnetic Resonance Fingerprinting (MRF) is a recently described MRI-based technique which can efficiently and simultaneously quantitatively map several tissue properties in a single exam. Here, the basic principles behind the quantitative approach of MRF are laid out, and the potential implications for combined PET/MR are discussed.
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Affiliation(s)
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106 USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, OH 44106 USA
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de Blank P, Badve C, Gold DR, Stearns D, Sunshine J, Dastmalchian S, Tomei K, Sloan AE, Barnholtz-Sloan JS, Lane A, Griswold M, Gulani V, Ma D. Magnetic Resonance Fingerprinting to Characterize Childhood and Young Adult Brain Tumors. Pediatr Neurosurg 2019; 54:310-318. [PMID: 31416081 DOI: 10.1159/000501696] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [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: 03/26/2019] [Accepted: 06/23/2019] [Indexed: 11/19/2022]
Abstract
OBJECT Magnetic resonance fingerprinting (MRF) allows rapid, simultaneous mapping of T1 and T2 relaxation times and may be an important diagnostic tool to measure tissue characteristics in pediatric brain tumors. We examined children and young adults with primary brain tumors to determine whether MRF can discriminate tumor from normal-appearing white matter and distinguish tumor grade. METHODS MRF was performed in 23 patients (14 children and 9 young adults) with brain tumors (19 low-grade glioma, 4 high-grade tumors). T1 and T2 values were recorded in regions of solid tumor (ST), peritumoral white matter (PWM), and contralateral white matter (CWM). Nonparametric tests were used for comparison between groups and regions. RESULTS Median scan time for MRF and a sequence for tumor localization was 11 min. MRF-derived T1 and T2 values distinguished ST from CWM (T1: 1,444 ± 254 ms vs. 938 ± 96 ms, p = 0.0002; T2: 61 ± 22 ms vs. 38 ± 9 ms, p = 0.0003) and separated high-grade tumors from low-grade tumors (T1: 1,863 ± 70 ms vs. 1,355 ± 187 ms, p = 0.007; T2: 90 ± 13 ms vs. 56 ± 19 ms, p = 0.013). PWM was distinct from CWM (T1: 1,261 ± 359 ms vs. 933 ± 104 ms, p = 0.0008; T2: 65 ± 51 ms vs. 38 ± 8 ms, p = 0.008), as well as from tumor (T1: 1,261 ± 371 ms vs. 1,462 ± 248 ms, p = 0.047). CONCLUSIONS MRF is a fast sequence that can rapidly distinguish important tissue components in pediatric brain tumor patients. MRF-derived T1 and T2 distinguished tumor from normal-appearing white matter, differentiated tumor grade, and found abnormalities in peritumoral regions. MRF may be useful for rapid quantitative measurement of tissue characteristics and distinguish tumor grade in children and young adults with brain tumors.
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Affiliation(s)
- Peter de Blank
- Department of Pediatrics, University of Cincinnati and the Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA,
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, Ohio, USA
| | - Deborah Rukin Gold
- Department of Neurology, University Hospitals Cleveland, Cleveland, Ohio, USA
| | - Duncan Stearns
- Department of Pediatrics, University Hospitals Cleveland, Cleveland, Ohio, USA
| | - Jeffrey Sunshine
- Department of Radiology, University Hospitals Cleveland, Cleveland, Ohio, USA
| | - Sara Dastmalchian
- Department of Radiology, University Hospitals Cleveland, Cleveland, Ohio, USA
| | - Krystal Tomei
- Department of Neurosurgery, University Hospitals Cleveland, Cleveland, Ohio, USA
| | - Andrew E Sloan
- Department of Neurosurgery, University Hospitals Cleveland, Cleveland, Ohio, USA.,Case Comprehensive Cancer Center, Cleveland, Ohio, USA
| | - Jill S Barnholtz-Sloan
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.,Case Comprehensive Cancer Center, Cleveland, Ohio, USA
| | - Adam Lane
- Department of Pediatrics, University of Cincinnati and the Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, University Hospitals Cleveland, Cleveland, Ohio, USA
| | - Dan Ma
- Department of Radiology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
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Ma D, Jones SE, Deshmane A, Sakaie K, Pierre EY, Larvie M, McGivney D, Blümcke I, Krishnan B, Lowe M, Gulani V, Najm I, Griswold MA, Wang ZI. Development of high-resolution 3D MR fingerprinting for detection and characterization of epileptic lesions. J Magn Reson Imaging 2018; 49:1333-1346. [DOI: 10.1002/jmri.26319] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 08/10/2018] [Accepted: 08/10/2018] [Indexed: 12/25/2022] Open
Affiliation(s)
- Dan Ma
- Radiology; Case Western Reserve University; Cleveland Ohio USA
| | | | - Anagha Deshmane
- Magnetic Resonance Center; Max Planck Institute for Biological Cybernetics; Tuebingen Germany
| | - Ken Sakaie
- Imaging Institute, Cleveland Clinic; Cleveland Ohio USA
| | - Eric Y. Pierre
- Florey Institute of Neuroscience and Mental Health; Melbourne Australia
| | - Mykol Larvie
- Imaging Institute, Cleveland Clinic; Cleveland Ohio USA
| | - Debra McGivney
- Radiology; Case Western Reserve University; Cleveland Ohio USA
| | - Ingmar Blümcke
- Epilepsy Center; Cleveland Clinic; Cleveland Ohio USA
- Institute of Neuropathology, University Hospitals Erlangen; Erlangen Germany
| | - Balu Krishnan
- Epilepsy Center; Cleveland Clinic; Cleveland Ohio USA
| | - Mark Lowe
- Imaging Institute, Cleveland Clinic; Cleveland Ohio USA
| | - Vikas Gulani
- Radiology; Case Western Reserve University; Cleveland Ohio USA
| | - Imad Najm
- Epilepsy Center; Cleveland Clinic; Cleveland Ohio USA
| | | | - Z. Irene Wang
- Epilepsy Center; Cleveland Clinic; Cleveland Ohio USA
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Obmann VC, Pahwa S, Tabayayong W, Jiang Y, O'Connor G, Dastmalchian S, Lu J, Shah S, Herrmann KA, Paspulati R, MacLennan G, Ponsky L, Abouassaly R, Gulani V. Diagnostic Accuracy of a Rapid Biparametric MRI Protocol for Detection of Histologically Proven Prostate Cancer. Urology 2018; 122:133-138. [PMID: 30201301 PMCID: PMC6295224 DOI: 10.1016/j.urology.2018.08.032] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [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: 07/16/2018] [Revised: 08/20/2018] [Accepted: 08/22/2018] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To evaluate the performance of a rapid, low cost, noncontrast MRI examination as a secondary screening tool in detection of clinically significant prostate cancer. METHODS In this prospective single institution study, 129 patients with elevated prostate-specific antigen levels or abnormal digital rectal examination findings underwent MRI with an abbreviated biparamatric MRI protocol consisting of high-resolution axial T2- and diffusion-weighted images. Index lesions were classified according to modified Prostate Imaging - Reporting and Data System (mPI-RADS) version 2.0. All patients underwent standard transrectal ultrasound-guided biopsy after MRI with the urologist being blinded to MRI results. Subsequently, all patients with suspicious lesions (mPI-RADS 3, 4, or 5) underwent cognitively guided targeted biopsy after discussion of MRI results with the urologist. Sensitivity and negative predictive value for identification of clinically significant prostate cancer (Gleason score 3+4 and above) were determined. RESULTS Rapid biparametric MRI discovered 176 lesions identified in 129 patients. Rapid MRI detected clinically significant cancers with a sensitivity of 95.1% with a negative predictive value of 95.1% and positive predictive value of 53.2%, leading to a change in management in 10.8% of the patients. False negative rate of biparametric (bp) MRI was 4.7%. CONCLUSION We found that a bp-MRI examination can detect clinically significant lesions and changed patient management in 10.8% of the patients. A rapid MRI protocol can be used as a useful secondary screening tool in men presenting with suspicion of prostate cancer.
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Affiliation(s)
- Verena C Obmann
- Department of Radiology, Case Western Reserve University, Cleveland, OH; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Shivani Pahwa
- Department of Radiology, Case Western Reserve University, Cleveland, OH; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - William Tabayayong
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Gregory O'Connor
- School of Medicine, Case Western Reserve University, Cleveland, OH
| | - Sara Dastmalchian
- Department of Radiology, Case Western Reserve University, Cleveland, OH; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - John Lu
- School of Medicine, Case Western Reserve University, Cleveland, OH
| | - Soham Shah
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Karin A Herrmann
- Department of Radiology, Case Western Reserve University, Cleveland, OH; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Raj Paspulati
- Department of Radiology, Case Western Reserve University, Cleveland, OH; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Gregory MacLennan
- Department of Urology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH; Department of Pathology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Lee Ponsky
- Department of Urology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Robert Abouassaly
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, OH; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH; Department of Urology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH.
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35
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Lo WC, Chen Y, Jiang Y, Hamilton J, Grimm R, Griswold M, Gulani V, Seiberlich N. Realistic 4D MRI abdominal phantom for the evaluation and comparison of acquisition and reconstruction techniques. Magn Reson Med 2018; 81:1863-1875. [PMID: 30394573 DOI: 10.1002/mrm.27545] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [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: 05/18/2018] [Revised: 07/24/2018] [Accepted: 08/30/2018] [Indexed: 12/22/2022]
Abstract
PURPOSE This work presents a 4D numerical abdominal phantom, which includes T1 and T2 relaxation times, proton density fat fraction, perfusion, and diffusion, as well as respiratory motion for the evaluation and comparison of acquisition and reconstruction techniques. METHODS The 3D anatomical mesh models were non-rigidly scaled and shifted by respiratory motion derived from an in vivo scan. A time series of voxelized 3D abdominal phantom images were obtained with contrast determined by the tissue properties and pulse sequence parameters. Two example simulations: (1) 3D T1 mapping under breath-hold and free-breathing acquisition conditions and (2) two different reconstruction techniques for accelerated 3D dynamic contrast-enhanced MRI, are presented. The source codes can be found at https://github.com/SeiberlichLab/Abdominal_MR_Phantom. RESULTS The proposed 4D abdominal phantom can successfully simulate images and MRI data with nonrigid respiratory motion and specific contrast settings and data sampling schemes. In example 1, the use of a numerical 4D abdominal phantom was demonstrated to aid in the comparison between different approaches for volumetric T1 mapping. In example 2, the average arterial fraction over the healthy hepatic parenchyma as calculated with spiral generalized autocalibrating partial parallel acquisition was closer to that from the fully sampled data than the arterial fraction from conjugate gradient sensitivity encoding, although both are elevated compared to the gold-standard reference. CONCLUSION This realistic abdominal MR phantom can be used to simulate different pulse sequences and data sampling schemes for the comparison of acquisition and reconstruction methods under controlled conditions that are impossible or prohibitively difficult to perform in vivo.
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Affiliation(s)
- Wei-Ching Lo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Yong Chen
- Department of Radiology, UH Cleveland Medical Center, Cleveland, Ohio
| | - Yun Jiang
- Department of Radiology, UH Cleveland Medical Center, Cleveland, Ohio
| | - Jesse Hamilton
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | | | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, UH Cleveland Medical Center, Cleveland, Ohio
| | - Vikas Gulani
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, UH Cleveland Medical Center, Cleveland, Ohio
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, UH Cleveland Medical Center, Cleveland, Ohio
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Hamilton JI, Jiang Y, Ma D, Lo WC, Gulani V, Griswold M, Seiberlich N. Investigating and reducing the effects of confounding factors for robust T 1 and T 2 mapping with cardiac MR fingerprinting. Magn Reson Imaging 2018; 53:40-51. [PMID: 29964183 PMCID: PMC7755105 DOI: 10.1016/j.mri.2018.06.018] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 06/26/2018] [Accepted: 06/27/2018] [Indexed: 01/04/2023]
Abstract
This study aims to improve the accuracy and consistency of T1 and T2 measurements using cardiac MR Fingerprinting (cMRF) by investigating and accounting for the effects of confounding factors including slice profile, inversion and T2 preparation pulse efficiency, and B1+. The goal is to understand how measurements with different pulse sequences are affected by these factors. This can be used to determine which factors must be taken into account for accurate measurements, and which may be mitigated by the selection of an appropriate pulse sequence. Simulations were performed using a numerical cardiac phantom to assess the accuracy of over 600 cMRF sequences with different flip angles, TRs, and preparation pulses. A subset of sequences, including one with the lowest errors in T1 and T2 maps, was used in subsequent analyses. Errors due to non-ideal slice profile, preparation pulse efficiency, and B1+ were quantified in Bloch simulations. Corrections for these effects were included in the dictionary generation and demonstrated in phantom and in vivo cardiac imaging at 3 T. Neglecting to model slice profile and preparation pulse efficiency led to underestimated T1 and overestimated T2 for most cMRF sequences. Sequences with smaller maximum flip angles were less affected by slice profile and B1+. Simulating all corrections in the dictionary improved the accuracy of T1 and T2 phantom measurements, regardless of acquisition pattern. More consistent myocardial T1 and T2 values were measured using different sequences after corrections. Based on these results, a pulse sequence which is minimally affected by confounding factors can be selected, and the appropriate residual corrections included for robust T1 and T2 mapping.
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Affiliation(s)
- Jesse I Hamilton
- Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
| | - Yun Jiang
- Dept. of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
| | - Dan Ma
- Dept. of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
| | - Wei-Ching Lo
- Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
| | - Vikas Gulani
- Dept. of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
| | - Mark Griswold
- Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Dept. of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
| | - Nicole Seiberlich
- Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Dept. of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
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37
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Chen Y, Panda A, Pahwa S, Hamilton JI, Dastmalchian S, McGivney DF, Ma D, Batesole J, Seiberlich N, Griswold MA, Plecha D, Gulani V. Three-dimensional MR Fingerprinting for Quantitative Breast Imaging. Radiology 2018; 290:33-40. [PMID: 30375925 DOI: 10.1148/radiol.2018180836] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Purpose To develop a fast three-dimensional method for simultaneous T1 and T2 quantification for breast imaging by using MR fingerprinting. Materials and Methods In this prospective study, variable flip angles and magnetization preparation modules were applied to acquire MR fingerprinting data for each partition of a three-dimensional data set. A fast postprocessing method was implemented by using singular value decomposition. The proposed technique was first validated in phantoms and then applied to 15 healthy female participants (mean age, 24.2 years ± 5.1 [standard deviation]; range, 18-35 years) and 14 female participants with breast cancer (mean age, 55.4 years ± 8.8; range, 39-66 years) between March 2016 and April 2018. The sensitivity of the method to B1 field inhomogeneity was also evaluated by using the Bloch-Siegert method. Results Phantom results showed that accurate and volumetric T1 and T2 quantification was achieved by using the proposed technique. The acquisition time for three-dimensional quantitative maps with a spatial resolution of 1.6 × 1.6 × 3 mm3 was approximately 6 minutes. For healthy participants, averaged T1 and T2 relaxation times for fibroglandular tissues at 3.0 T were 1256 msec ± 171 and 46 msec ± 7, respectively. Compared with normal breast tissues, higher T2 relaxation time (68 msec ± 13) was observed in invasive ductal carcinoma (P < .001), whereas no statistical difference was found in T1 relaxation time (1183 msec ± 256; P = .37). Conclusion A method was developed for breast imaging by using the MR fingerprinting technique, which allows simultaneous and volumetric quantification of T1 and T2 relaxation times for breast tissues. © RSNA, 2018 Online supplemental material is available for this article.
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Affiliation(s)
- Yong Chen
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Ananya Panda
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Shivani Pahwa
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Jesse I Hamilton
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Sara Dastmalchian
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Debra F McGivney
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Dan Ma
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Joshua Batesole
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Nicole Seiberlich
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Mark A Griswold
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Donna Plecha
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Vikas Gulani
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
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38
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Körzdörfer G, Jiang Y, Speier P, Pang J, Ma D, Pfeuffer J, Hensel B, Gulani V, Griswold M, Nittka M. Magnetic resonance field fingerprinting. Magn Reson Med 2018; 81:2347-2359. [PMID: 30320925 DOI: 10.1002/mrm.27558] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 09/12/2018] [Accepted: 09/14/2018] [Indexed: 12/17/2022]
Abstract
PURPOSE To develop and evaluate the magnetic resonance field fingerprinting method that simultaneously generates T1 , T2 , B0 , and B 1 + maps from a single continuous measurement. METHODS An encoding pattern was designed to integrate true fast imaging with steady-state precession (TrueFISP), fast imaging with steady-state precession (FISP), and fast low-angle shot (FLASH) sequence segments with varying flip angles, radio frequency (RF) phases, TEs, and gradient moments in a continuous acquisition. A multistep matching process was introduced that includes steps for integrated spiral deblurring and the correction of intravoxel phase dispersion. The method was evaluated in phantoms as well as in vivo studies in brain and lower abdomen. RESULTS Simultaneous measurement of T1 , T2 , B0 , and B 1 + is achieved with T1 and T2 subsequently being less afflicted by B0 and B 1 + variations. Phantom results demonstrate the stability of generated parameter maps. Higher undersampling factors and spatial resolution can be achieved with the proposed method as compared with solely FISP-based magnetic resonance fingerprinting. High-resolution B0 maps can potentially be further used as diagnostic information. CONCLUSION The proposed magnetic resonance field fingerprinting method can estimate T1 , T2 , B0 , and B 1 + maps accurately in phantoms, in the brain, and in the lower abdomen.
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Affiliation(s)
- Gregor Körzdörfer
- Siemens Healthcare GmbH, Erlangen, Germany.,Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | | | - Jianing Pang
- Siemens Medical Solutions USA, Chicago, Illinois
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | | | - Bernhard Hensel
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
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39
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Bipin Mehta B, Coppo S, Frances McGivney D, Ian Hamilton J, Chen Y, Jiang Y, Ma D, Seiberlich N, Gulani V, Alan Griswold M. Magnetic resonance fingerprinting: a technical review. Magn Reson Med 2018; 81:25-46. [PMID: 30277265 DOI: 10.1002/mrm.27403] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [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: 08/09/2017] [Revised: 05/01/2018] [Accepted: 05/21/2018] [Indexed: 01/31/2023]
Abstract
Multiparametric quantitative imaging is gaining increasing interest due to its widespread advantages in clinical applications. Magnetic resonance fingerprinting is a recently introduced approach of fast multiparametric quantitative imaging. In this article, magnetic resonance fingerprinting acquisition, dictionary generation, reconstruction, and validation are reviewed.
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Affiliation(s)
- Bhairav Bipin Mehta
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Simone Coppo
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Debra Frances McGivney
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Jesse Ian Hamilton
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Yong Chen
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Yun Jiang
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Dan Ma
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Mark Alan Griswold
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
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40
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van Beek EJR, Kuhl C, Anzai Y, Desmond P, Ehman RL, Gong Q, Gold G, Gulani V, Hall-Craggs M, Leiner T, Lim CCT, Pipe JG, Reeder S, Reinhold C, Smits M, Sodickson DK, Tempany C, Vargas HA, Wang M. Value of MRI in medicine: More than just another test? J Magn Reson Imaging 2018; 49:e14-e25. [PMID: 30145852 DOI: 10.1002/jmri.26211] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [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: 03/19/2018] [Accepted: 05/16/2018] [Indexed: 02/06/2023] Open
Abstract
There is increasing scrutiny from healthcare organizations towards the utility and associated costs of imaging. MRI has traditionally been used as a high-end modality, and although shown extremely important for many types of clinical scenarios, it has been suggested as too expensive by some. This editorial will try and explain how value should be addressed and gives some insights and practical examples of how value of MRI can be increased. It requires a global effort to increase accessibility, value for money, and impact on patient management. We hope this editorial sheds some light and gives some indications of where the field may wish to address some of its research to proactively demonstrate the value of MRI. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;49:e14-e25.
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Affiliation(s)
| | - Christiane Kuhl
- Department of Diagnostic and Interventional Radiology, University of Aachen, Aachen, Germany
| | - Yoshimi Anzai
- Department of Radiology, University of Utah, Salt Lake City, Utah, USA
| | - Patricia Desmond
- Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Garry Gold
- Department of Radiology, Engineering and Orthopaedic Surgery, Stanford University, Stanford, California, USA
| | - Vikas Gulani
- Departments of Radiology, Urology and Biomedical Imaging, Case Western Reserve University, University Hospitals of Cleveland, Cleveland, Ohio, USA
| | - Margaret Hall-Craggs
- Department of Medical Imaging and Radiology, University College Hospital NHS Trust, London, UK
| | - Tim Leiner
- Department of Radiology and Nuclear Medicine, University Medical Centre, Utrecht, The Netherlands
| | - C C Tschoyoson Lim
- Department of Neuroradiology, National Neuroscience Institute and Duke NUS Medical School, Singapore, Singapore
| | - James G Pipe
- Department of Imaging Research, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Scott Reeder
- Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine and Emergency Medicine, University of Madison, Madison, Wisconsin, USA
| | - Caroline Reinhold
- Department of Radiology, McGill University Health Center, Montreal, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Daniel K Sodickson
- Department of Radiology, New York University Langone Health, New York, New York, USA
| | - Clare Tempany
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - H Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, Henan, China
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41
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McGivney D, Deshmane A, Jiang Y, Ma D, Badve C, Sloan A, Gulani V, Griswold M. Bayesian estimation of multicomponent relaxation parameters in magnetic resonance fingerprinting. Magn Reson Med 2018; 80:159-170. [PMID: 29159935 PMCID: PMC5876128 DOI: 10.1002/mrm.27017] [Citation(s) in RCA: 36] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 10/25/2017] [Accepted: 10/27/2017] [Indexed: 11/06/2022]
Abstract
PURPOSE To estimate multiple components within a single voxel in magnetic resonance fingerprinting when the number and types of tissues comprising the voxel are not known a priori. THEORY Multiple tissue components within a single voxel are potentially separable with magnetic resonance fingerprinting as a result of differences in signal evolutions of each component. The Bayesian framework for inverse problems provides a natural and flexible setting for solving this problem when the tissue composition per voxel is unknown. Assuming that only a few entries from the dictionary contribute to a mixed signal, sparsity-promoting priors can be placed upon the solution. METHODS An iterative algorithm is applied to compute the maximum a posteriori estimator of the posterior probability density to determine the magnetic resonance fingerprinting dictionary entries that contribute most significantly to mixed or pure voxels. RESULTS Simulation results show that the algorithm is robust in finding the component tissues of mixed voxels. Preliminary in vivo data confirm this result, and show good agreement in voxels containing pure tissue. CONCLUSIONS The Bayesian framework and algorithm shown provide accurate solutions for the partial-volume problem in magnetic resonance fingerprinting. The flexibility of the method will allow further study into different priors and hyperpriors that can be applied in the model. Magn Reson Med 80:159-170, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Debra McGivney
- Radiology, Case Western Reserve University, Cleveland, OH
| | - Anagha Deshmane
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH
| | - Yun Jiang
- Radiology, Case Western Reserve University, Cleveland, OH
| | - Dan Ma
- Radiology, Case Western Reserve University, Cleveland, OH
| | - Chaitra Badve
- Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Andrew Sloan
- Neurosurgery, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Vikas Gulani
- Radiology, Case Western Reserve University, Cleveland, OH
- Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Mark Griswold
- Radiology, Case Western Reserve University, Cleveland, OH
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH
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42
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Mukkamala A, Elliott RM, Fulton N, Gulani V, Ponsky LE, Autorino R. Inflammatory pseudotumor of kidney: a challenging diagnostic entity. Int Braz J Urol 2018; 44:196-198. [PMID: 28727376 PMCID: PMC5815552 DOI: 10.1590/s1677-5538.ibju.2017.0063] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 04/02/2017] [Indexed: 02/07/2023] Open
Affiliation(s)
| | - Robin M Elliott
- Department of Pathology, University Hospitals Case Medical Center, Cleveland, Ohio, USA
| | - Nicholas Fulton
- Department of Radiology, University Hospitals Case Medical Center, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, University Hospitals Case Medical Center, Cleveland, Ohio, USA
| | - Lee E Ponsky
- Department of Urology, UH Case Medical Center, Cleveland, Ohio, USA
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43
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Chen Y, Lo WC, Hamilton JI, Barkauskas K, Saybasili H, Wright KL, Batesole J, Griswold MA, Gulani V, Seiberlich N. Single breath-hold 3D cardiac T 1 mapping using through-time spiral GRAPPA. NMR Biomed 2018; 31:e3923. [PMID: 29637637 PMCID: PMC5980781 DOI: 10.1002/nbm.3923] [Citation(s) in RCA: 9] [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] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Revised: 02/26/2018] [Accepted: 02/27/2018] [Indexed: 06/08/2023]
Abstract
The quantification of cardiac T1 relaxation time holds great potential for the detection of various cardiac diseases. However, as a result of both cardiac and respiratory motion, only one two-dimensional T1 map can be acquired in one breath-hold with most current techniques, which limits its application for whole heart evaluation in routine clinical practice. In this study, an electrocardiogram (ECG)-triggered three-dimensional Look-Locker method was developed for cardiac T1 measurement. Fast three-dimensional data acquisition was achieved with a spoiled gradient-echo sequence in combination with a stack-of-spirals trajectory and through-time non-Cartesian generalized autocalibrating partially parallel acquisition (GRAPPA) acceleration. The effects of different magnetic resonance parameters on T1 quantification with the proposed technique were first examined by simulating data acquisition and T1 map reconstruction using Bloch equation simulations. Accuracy was evaluated in studies with both phantoms and healthy subjects. These results showed that there was close agreement between the proposed technique and the reference method for a large range of T1 values in phantom experiments. In vivo studies further demonstrated that rapid cardiac T1 mapping for 12 three-dimensional partitions (spatial resolution, 2 × 2 × 8 mm3 ) could be achieved in a single breath-hold of ~12 s. The mean T1 values of myocardial tissue and blood obtained from normal volunteers at 3 T were 1311 ± 66 and 1890 ± 159 ms, respectively. In conclusion, a three-dimensional T1 mapping technique was developed using a non-Cartesian parallel imaging method, which enables fast and accurate T1 mapping of cardiac tissues in a single short breath-hold.
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Affiliation(s)
- Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Wei-Ching Lo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jesse I Hamilton
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Kestutis Barkauskas
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | | | - Katherine L Wright
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Joshua Batesole
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark A Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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44
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Sadeghi Z, Abboud R, Abboud B, Mahran A, Buzzy C, Yang J, Gulani V, Ponsky L. MP77-02 A NEW VERSUS AN OLD NOTION: IS THERE ANY CORRELATION BETWEEN MULTI-PARAMETRIC MRI (MPMRI) PI-RADS (PROSTATE IMAGING-REPORTING AND DATA SYSTEM) SCORE AND PSA (PROSTATE SPECIFIC ANTIGEN) KINETICS? J Urol 2018. [DOI: 10.1016/j.juro.2018.02.2590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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45
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Ma D, Jiang Y, Chen Y, McGivney D, Mehta B, Gulani V, Griswold M. Fast 3D magnetic resonance fingerprinting for a whole-brain coverage. Magn Reson Med 2018; 79:2190-2197. [PMID: 28833436 PMCID: PMC5868964 DOI: 10.1002/mrm.26886] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [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: 04/10/2017] [Revised: 07/19/2017] [Accepted: 08/03/2017] [Indexed: 12/24/2022]
Abstract
PURPOSE The purpose of this study was to accelerate the acquisition and reconstruction time of 3D magnetic resonance fingerprinting scans. METHODS A 3D magnetic resonance fingerprinting scan was accelerated by using a single-shot spiral trajectory with an undersampling factor of 48 in the x-y plane, and an interleaved sampling pattern with an undersampling factor of 3 through plane. Further acceleration came from reducing the waiting time between neighboring partitions. The reconstruction time was accelerated by applying singular value decomposition compression in k-space. Finally, a 3D premeasured B1 map was used to correct for the B1 inhomogeneity. RESULTS The T1 and T2 values of the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI phantom showed a good agreement with the standard values, with an average concordance correlation coefficient of 0.99, and coefficient of variation of 7% in the repeatability scans. The results from in vivo scans also showed high image quality in both transverse and coronal views. CONCLUSIONS This study applied a fast acquisition scheme for a fully quantitative 3D magnetic resonance fingerprinting scan with a total acceleration factor of 144 as compared with the Nyquist rate, such that 3D T1 , T2 , and proton density maps can be acquired with whole-brain coverage at clinical resolution in less than 5 min. Magn Reson Med 79:2190-2197, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Debra McGivney
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Bhairav Mehta
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, OH
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46
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Obmann VC, Chalian M, Mansoori B, Sanchez E, Gulani V. Advantages of time-resolved contrast-enhanced 4D MR angiography in splenic arterial steal syndrome. Clin Imaging 2018; 49:169-173. [PMID: 29558712 DOI: 10.1016/j.clinimag.2018.03.003] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2017] [Revised: 02/01/2018] [Accepted: 03/01/2018] [Indexed: 01/17/2023]
Abstract
Splenic artery steal syndrome (SASS) is a severe complication affecting up to 10% of orthotopic liver transplant (OLT) patients. In this case report, we present a 35-year-old male with OLT secondary to liver failure due to hemochromatosis, who developed SASS. We describe potential application of different imaging techniques for diagnosis of SASS with focus on the value of time-resolved contrast enhanced 4D magnetic resonance angiography (MRA).
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Affiliation(s)
- Verena C Obmann
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, United States; Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital Bern, Bern University Hospital, University of Bern, Bern, Switzerland.
| | - Majid Chalian
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, United States
| | - Bahar Mansoori
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, United States.
| | - Edmund Sanchez
- Division of Hepatobiliary and Transplant Surgery, University Hospitals Cleveland Medical Center Transplant Institute, Cleveland, OH, United States.
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, United States.
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47
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Pahwa S, Liu H, Chen Y, Dastmalchian S, O'Connor G, Lu Z, Badve C, Yu A, Wright K, Chalian H, Rao S, Fu C, Vallines I, Griswold M, Seiberlich N, Zeng M, Gulani V. Quantitative perfusion imaging of neoplastic liver lesions: A multi-institution study. Sci Rep 2018; 8:4990. [PMID: 29563601 PMCID: PMC5862961 DOI: 10.1038/s41598-018-20726-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 01/16/2018] [Indexed: 12/14/2022] Open
Abstract
We describe multi-institutional experience using free-breathing, 3D Spiral GRAPPA-based quantitative perfusion MRI in characterizing neoplastic liver masses. 45 patients (age: 48–72 years) were prospectively recruited at University Hospitals, Cleveland, USA on a 3 Tesla (T) MRI, and at Zhongshan Hospital, Shanghai, China on a 1.5 T MRI. Contrast-enhanced volumetric T1-weighted images were acquired and a dual-input single-compartment model used to derive arterial fraction (AF), distribution volume (DV) and mean transit time (MTT) for the lesions and normal parenchyma. The measurements were compared using two-tailed Student’s t-test, with Bonferroni correction applied for multiple-comparison testing. 28 hepatocellular carcinoma (HCC) and 17 metastatic lesions were evaluated. No significant difference was noted in perfusion parameters of normal liver parenchyma and neoplastic masses at two centers (p = 0.62 for AF, 0.015 for DV, 0.42 for MTT for HCC, p = 0.13 for AF, 0.97 for DV, 0.78 for MTT for metastases). There was statistically significant difference in AF, DV, and MTT of metastases and AF and DV of HCC compared to normal liver parenchyma (p < 0.5/9 = 0.0055). A statistically significant difference was noted in the MTT of metastases compared to hepatocellular carcinoma (p < 0.001*10-5). In conclusion, 3D Spiral-GRAPPA enabled quantitative free-breathing perfusion MRI exam provides robust perfusion parameters.
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Affiliation(s)
- Shivani Pahwa
- Radiology, Case Western Reserve University, Cleveland, OH, United States
| | - Hao Liu
- Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yong Chen
- Radiology, Case Western Reserve University, Cleveland, OH, United States
| | - Sara Dastmalchian
- Radiology, Case Western Reserve University, Cleveland, OH, United States
| | - Gregory O'Connor
- Radiology, Case Western Reserve University, Cleveland, OH, United States
| | - Ziang Lu
- Radiology, Case Western Reserve University, Cleveland, OH, United States
| | - Chaitra Badve
- Radiology, University Hospitals, Cleveland, OH, United States
| | - Alice Yu
- Radiology, Case Western Reserve University, Cleveland, OH, United States
| | - Katherine Wright
- Radiology, Case Western Reserve University, Cleveland, OH, United States
| | - Hamid Chalian
- Radiology, University Hospitals, Cleveland, OH, United States
| | - Shengxiang Rao
- Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Caixia Fu
- Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China
| | | | - Mark Griswold
- Radiology, Case Western Reserve University, Cleveland, OH, United States.,Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Nicole Seiberlich
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Mengsu Zeng
- Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Vikas Gulani
- Radiology, Case Western Reserve University, Cleveland, OH, United States. .,Radiology, University Hospitals, Cleveland, OH, United States.
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48
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Wright KL, Jiang Y, Ma D, Noll DC, Griswold MA, Gulani V, Hernandez-Garcia L. Estimation of perfusion properties with MR Fingerprinting Arterial Spin Labeling. Magn Reson Imaging 2018; 50:68-77. [PMID: 29545215 DOI: 10.1016/j.mri.2018.03.011] [Citation(s) in RCA: 32] [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: 02/19/2018] [Accepted: 03/10/2018] [Indexed: 12/22/2022]
Abstract
In this study, the acquisition of ASL data and quantification of multiple hemodynamic parameters was explored using a Magnetic Resonance Fingerprinting (MRF) approach. A pseudo-continuous ASL labeling scheme was used with pseudo-randomized timings to acquire the MRF ASL data in a 2.5 min acquisition. A large dictionary of MRF ASL signals was generated by combining a wide range of physical and hemodynamic properties with the pseudo-random MRF ASL sequence and a two-compartment model. The acquired signals were matched to the dictionary to provide simultaneous quantification of cerebral blood flow, tissue time-to-peak, cerebral blood volume, arterial time-to-peak, B1, and T1. A study in seven healthy volunteers resulted in the following values across the population in grey matter (mean ± standard deviation): cerebral blood flow of 69.1 ± 6.1 ml/min/100 g, arterial time-to-peak of 1.5 ± 0.1 s, tissue time-to-peak of 1.5 ± 0.1 s, T1 of 1634 ms, cerebral blood volume of 0.0048 ± 0.0005. The CBF measurements were compared to standard pCASL CBF estimates using a one-compartment model, and a Bland-Altman analysis showed good agreement with a minor bias. Repeatability was tested in five volunteers in the same exam session, and no statistical difference was seen. In addition to this validation, the MRF ASL acquisition's sensitivity to the physical and physiological parameters of interest was studied numerically.
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Affiliation(s)
- Katherine L Wright
- Dept. of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH, USA.
| | - Yun Jiang
- Dept. of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH, USA
| | - Dan Ma
- Dept. of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH, USA
| | - Douglas C Noll
- Dept. of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Mark A Griswold
- Dept. of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH, USA; Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Vikas Gulani
- Dept. of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, OH, USA; Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
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Ghodasara S, Pahwa S, Dastmalchian S, Gulani V, Chen Y. Free-Breathing 3D Liver Perfusion Quantification Using a Dual-Input Two-Compartment Model. Sci Rep 2017; 7:17502. [PMID: 29235486 PMCID: PMC5727493 DOI: 10.1038/s41598-017-17753-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Accepted: 11/23/2017] [Indexed: 01/12/2023] Open
Abstract
The purpose of this study is to test the feasibility of applying a dual-input two-compartment liver perfusion model to patients with different pathologies. A total of 7 healthy subjects and 11 patients with focal liver lesions, including 6 patients with metastatic adenocarcinoma and 5 with hepatocellular carcinoma (HCC), were examined. Liver perfusion values were measured from both focal liver lesions and cirrhotic tissues (from the 5 HCC patients). Compared to results from volunteer livers, significantly higher arterial fraction, fractional volume of the interstitial space, and lower permeability-surface area product were observed for metastatic lesions, and significantly higher arterial fraction and lower vascular transit time were observed for HCCs (P < 0.05). Significantly lower arterial fraction and higher vascular transit time, fractional volume of the vascular space, and fractional volume of the interstitial space were observed for metastases in comparison to HCCs (P < 0.05). For cirrhotic livers, a significantly lower total perfusion, lower fractional volume of the vascular space, higher fractional volume of the interstitial space, and lower permeability-surface area product were noted in comparison to volunteer livers (P < 0.05). Our findings support the possibility of using this model with 3D free-breathing acquisitions for lesion and diffuse liver disease characterization.
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Affiliation(s)
- Satyam Ghodasara
- Department of Radiology, Case Western Reserve University, and University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Shivani Pahwa
- Department of Radiology, Case Western Reserve University, and University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Sara Dastmalchian
- Department of Radiology, Case Western Reserve University, and University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, and University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, and University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
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Gulani V, Calamante F, Shellock FG, Kanal E, Reeder SB. Chelated or dechelated gadolinium deposition – Authors' reply. Lancet Neurol 2017; 16:955-956. [DOI: 10.1016/s1474-4422(17)30365-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Accepted: 10/03/2017] [Indexed: 01/27/2023]
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