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Ariyurek C, Koçanaoğulları A, Afacan O, Kurugol S. Motion-compensated image reconstruction for improved kidney function assessment using dynamic contrast-enhanced MRI. NMR IN BIOMEDICINE 2024; 37:e5116. [PMID: 38359842 DOI: 10.1002/nbm.5116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 12/08/2023] [Accepted: 01/15/2024] [Indexed: 02/17/2024]
Abstract
Accurately measuring renal function is crucial for pediatric patients with kidney conditions. Traditional methods have limitations, but dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides a safe and efficient approach for detailed anatomical evaluation and renal function assessment. However, motion artifacts during DCE-MRI can degrade image quality and introduce misalignments, leading to unreliable results. This study introduces a motion-compensated reconstruction technique for DCE-MRI data acquired using golden-angle radial sampling. Our proposed method achieves three key objectives: (1) identifying and removing corrupted data (outliers) using a Gaussian process model fitting with a k -space center navigator, (2) efficiently clustering the data into motion phases and performing interphase registration, and (3) utilizing a novel formulation of motion-compensated radial reconstruction. We applied the proposed motion correction (MoCo) method to DCE-MRI data affected by varying degrees of motion, including both respiratory and bulk motion. We compared the outcomes with those obtained from the conventional radial reconstruction. Our evaluation encompassed assessing the quality of images, concentration curves, and tracer kinetic model fitting, and estimating renal function. The proposed MoCo reconstruction improved the temporal signal-to-noise ratio for all subjects, with a 21.8% increase on average, while total variation values of the aorta, right, and left kidney concentration were improved for each subject, with 32.5%, 41.3%, and 42.9% increases on average, respectively. Furthermore, evaluation of tracer kinetic model fitting indicated that the median standard deviation of the estimated filtration rate (σ F T ), mean normalized root-mean-squared error (nRMSE), and chi-square goodness-of-fit of tracer kinetic model fit were decreased from 0.10 to 0.04, 0.27 to 0.24, and, 0.43 to 0.27, respectively. The proposed MoCo technique enabled more reliable renal function assessment and improved image quality for detailed anatomical evaluation in the case of bulk and respiratory motion during the acquisition of DCE-MRI.
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Affiliation(s)
- Cemre Ariyurek
- Quantitative Intelligent Imaging Lab (QUIN), Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Aziz Koçanaoğulları
- Quantitative Intelligent Imaging Lab (QUIN), Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Onur Afacan
- Quantitative Intelligent Imaging Lab (QUIN), Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Sila Kurugol
- Quantitative Intelligent Imaging Lab (QUIN), Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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Zhong X, Nickel MD, Kannengiesser SAR, Dale BM, Han F, Gao C, Shih SF, Dai Q, Curiel O, Tsao TC, Wu HH, Deshpande V. Accelerated free-breathing liver fat and R 2 * quantification using multi-echo stack-of-radial MRI with motion-resolved multidimensional regularized reconstruction: Initial retrospective evaluation. Magn Reson Med 2024. [PMID: 38650444 DOI: 10.1002/mrm.30117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 02/25/2024] [Accepted: 04/01/2024] [Indexed: 04/25/2024]
Abstract
PURPOSE To improve image quality, mitigate quantification biases and variations for free-breathing liver proton density fat fraction (PDFF) andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ quantification accelerated by radial k-space undersampling. METHODS A free-breathing multi-echo stack-of-radial MRI method was developed with compressed sensing with multidimensional regularization. It was validated in motion phantoms with reference acquisitions without motion and in 11 subjects (6 patients with nonalcoholic fatty liver disease) with reference breath-hold Cartesian acquisitions. Images, PDFF, andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps were reconstructed using different radial view k-space sampling factors and reconstruction settings. Results were compared with reference-standard results using Bland-Altman analysis. Using linear mixed-effects model fitting (p < 0.05 considered significant), mean and SD were evaluated for biases and variations of PDFF andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ , respectively, and coefficient of variation on the first echo image was evaluated as a surrogate for image quality. RESULTS Using the empirically determined optimal sampling factor of 0.25 in the accelerated in vivo protocols, mean differences and limits of agreement for the proposed method were [-0.5; -33.6, 32.7] s-1 forR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and [-1.0%; -5.8%, 3.8%] for PDFF, close to those of a previous self-gating method using fully sampled radial views: [-0.1; -27.1, 27.0] s-1 forR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and [-0.4%; -4.5%, 3.7%] for PDFF. The proposed method had significantly lower coefficient of variation than other methods (p < 0.001). Effective acquisition time of 64 s or 59 s was achieved, compared with 171 s or 153 s for two baseline protocols with different radial views corresponding to sampling factor of 1.0. CONCLUSION This proposed method may allow accelerated free-breathing liver PDFF andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ mapping with reduced biases and variations.
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Affiliation(s)
- Xiaodong Zhong
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Physics and Biology in Medicine Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Samueli School of Engineering, University of California Los Angeles, Los Angeles, California, USA
| | - Marcel D Nickel
- MR Application Predevelopment, Siemens Healthineers AG, Erlangen, Germany
| | | | - Brian M Dale
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Cary, North Carolina, USA
| | - Fei Han
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Los Angeles, California, USA
| | - Chang Gao
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Los Angeles, California, USA
| | - Shu-Fu Shih
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Samueli School of Engineering, University of California Los Angeles, Los Angeles, California, USA
| | - Qing Dai
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Samueli School of Engineering, University of California Los Angeles, Los Angeles, California, USA
| | - Omar Curiel
- Department of Mechanical and Aerospace Engineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Tsu-Chin Tsao
- Department of Mechanical and Aerospace Engineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Holden H Wu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Physics and Biology in Medicine Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Samueli School of Engineering, University of California Los Angeles, Los Angeles, California, USA
| | - Vibhas Deshpande
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Austin, Texas, USA
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Tan Z, Unterberg-Buchwald C, Blumenthal M, Scholand N, Schaten P, Holme C, Wang X, Raddatz D, Uecker M. Free-Breathing Liver Fat, R₂* and B₀ Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-Based Reconstruction. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:1374-1387. [PMID: 37015368 PMCID: PMC10368089 DOI: 10.1109/tmi.2022.3228075] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
This work introduced a stack-of-radial multi-echo asymmetric-echo MRI sequence for free-breathing liver volumetric acquisition. Regularized model-based reconstruction was implemented in Berkeley Advanced Reconstruction Toolbox (BART) to jointly estimate all physical parameter maps (water, fat, R2∗ , and B0 field inhomogeneity maps) and coil sensitivity maps from self-gated k -space data. Specifically, locally low rank and temporal total variation regularization were employed directly on physical parameter maps. The proposed free-breathing radial technique was tested on a water/fat & iron phantom, a young volunteer, and obesity/diabetes/hepatic steatosis patients. Quantitative fat fraction and R2∗ accuracy were confirmed by comparing our technique with the reference breath-hold Cartesian scan. The multi-echo radial sampling sequence achieves fast k -space coverage and is robust to motion. Moreover, the proposed motion-resolved model-based reconstruction allows for free-breathing liver fat and R2∗ quantification in multiple motion states. Overall, our proposed technique offers a convenient tool for non-invasive liver assessment with no breath holding requirement.
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Gao C, Ghodrati V, Shih SF, Wu HH, Liu Y, Nickel MD, Vahle T, Dale B, Sai V, Felker E, Surawech C, Miao Q, Finn JP, Zhong X, Hu P. Undersampling artifact reduction for free-breathing 3D stack-of-radial MRI based on a deep adversarial learning network. Magn Reson Imaging 2023; 95:70-79. [PMID: 36270417 PMCID: PMC10163826 DOI: 10.1016/j.mri.2022.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/06/2022] [Accepted: 10/14/2022] [Indexed: 11/05/2022]
Abstract
PURPOSE Stack-of-radial MRI allows free-breathing abdominal scans, however, it requires relatively long acquisition time. Undersampling reduces scan time but can cause streaking artifacts and degrade image quality. This study developed deep learning networks with adversarial loss and evaluated the performance of reducing streaking artifacts and preserving perceptual image sharpness. METHODS A 3D generative adversarial network (GAN) was developed for reducing streaking artifacts in stack-of-radial abdominal scans. Training and validation datasets were self-gated to 5 respiratory states to reduce motion artifacts and to effectively augment the data. The network used a combination of three loss functions to constrain the anatomy and preserve image quality: adversarial loss, mean-squared-error loss and structural similarity index loss. The performance of the network was investigated for 3-5 times undersampled data from 2 institutions. The performance of the GAN for 5 times accelerated images was compared with a 3D U-Net and evaluated using quantitative NMSE, SSIM and region of interest (ROI) measurements as well as qualitative scores of radiologists. RESULTS The 3D GAN showed similar NMSE (0.0657 vs. 0.0559, p = 0.5217) and significantly higher SSIM (0.841 vs. 0.798, p < 0.0001) compared to U-Net. ROI analysis showed GAN removed streaks in both the background air and the tissue and was not significantly different from the reference mean and variations. Radiologists' scores showed GAN had a significant improvement of 1.6 point (p = 0.004) on a 4-point scale in streaking score while no significant difference in sharpness score compared to the input. CONCLUSION 3D GAN removes streaking artifacts and preserves perceptual image details.
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Affiliation(s)
- Chang Gao
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Inter-Departmental Graduate Program of Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Vahid Ghodrati
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Inter-Departmental Graduate Program of Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Shu-Fu Shih
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Holden H Wu
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Inter-Departmental Graduate Program of Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Yongkai Liu
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Inter-Departmental Graduate Program of Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | | | - Thomas Vahle
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Brian Dale
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Cary, NC, United States
| | - Victor Sai
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Ely Felker
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Chuthaporn Surawech
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Department of Radiology, Division of Diagnostic Radiology, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Qi Miao
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - J Paul Finn
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Inter-Departmental Graduate Program of Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Xiaodong Zhong
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States
| | - Peng Hu
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States; Inter-Departmental Graduate Program of Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States.
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Bhimaniya S, Arora J, Sharma P, Zhang Z, Khanna G. Liver iron quantification in children and young adults: comparison of a volumetric multi-echo 3-D Dixon sequence with conventional 2-D T2* relaxometry. Pediatr Radiol 2022; 52:1476-1483. [PMID: 35384483 DOI: 10.1007/s00247-022-05352-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 02/02/2022] [Accepted: 03/09/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Magnetic resonance imaging (MRI)-based liver iron quantification is the standard of care to guide chelation therapy in children at risk of hemochromatosis. T2* relaxometry is the most widely used technique but requires third-party software for post-processing. Vendor-provided three-dimensional (3-D) multi-echo Dixon techniques are now available that allow inline/automated post-processing. OBJECTIVE The purpose of our study was to evaluate the diagnostic accuracy of a volumetric multi-echo Dixon technique using conventional T2* relaxometry as the reference standard in a pediatric and young adult population. MATERIALS AND METHODS In this retrospective study, we queried the radiology information system to identify all MRIs performed for liver iron quantification from July 2015 to January 2020. All patients had undergone T2* relaxometry on a 1.5-tesla (T) scanner for liver iron concentration (LIC) estimation. In addition, a 3-D multi-echo Dixon was performed using Siemens Healthineers LiverLab (Erlangen, Germany). Two readers independently estimated liver R2* and T2* on the multi-echo Dixon by drawing free-hand regions of interest on the scanner-generated R2* and T2* maps. Conventional T2*-relaxometry-based LIC was the reference standard. We estimated interobserver agreement by concordance correlation coefficient (CCC). We used Bland-Altman analysis and Pearson correlation coefficient (r) to compare LIC by the two methods. RESULTS Fifty-four MRIs on 38 patients (22 females) were available for analysis. Mean patient age was 11.8 years (standard deviation [SD] 5.3 years). Reference standard LIC ranged 1.1-21.1 (median 6.8) mg/g dry weight of liver. The concordance between readers for T2* estimation using 3-D multi-echo Dixon was substantial (CCC 0.99, confidence interval 0.99-1.00). Bland-Altman plot showed that all observations were clustered around the zero bias line if the LIC average was ≤8 mg/g, and r was very strong (reader 1 r=0.93, reader 2 r=0.92, both P-values <0.001). With increasing LIC, there was a pattern of poor agreement on the Bland-Altman plot, with observations crossing the lower limits of agreement, and r was very weak (reader 1 r=0.05, P-value 0.84; reader 2 r=0.17, P-value 0.44). CONCLUSION Vendor-based 3-D multi-echo Dixon allows for excellent interobserver correlation in liver T2* estimation. LIC estimated by this method has a very strong correlation with conventional T2* relaxometry if liver iron overload is mild-moderate (LIC ≤8 mg/g).
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Affiliation(s)
- Sudhir Bhimaniya
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jyoti Arora
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Puneet Sharma
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Zhongwei Zhang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Geetika Khanna
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA.
- Pediatric Radiology, Egleston Hospital, Children's Healthcare of Atlanta, 1405 Clifton Road NE, Radiology Admin Office 1st Floor Tower 2, Atlanta, GA, 30322, USA.
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Rohani SC, Morin CE, Zhong X, Kannengiesser S, Shrestha U, Goode C, Holtrop J, Khan A, Loeffler RB, Hankins JS, Hillenbrand CM, Tipirneni-Sajja A. Hepatic Iron Quantification Using a Free-Breathing 3D Radial Gradient Echo Technique and Validation With a 2D Biopsy-Calibrated R 2* Relaxometry Method. J Magn Reson Imaging 2022; 55:1407-1416. [PMID: 34545639 PMCID: PMC10424632 DOI: 10.1002/jmri.27921] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/31/2021] [Accepted: 09/01/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Hepatic iron content (HIC) is an important parameter for the management of iron overload. Non-invasive HIC assessment is often performed using biopsy-calibrated two-dimensional breath-hold Cartesian gradient echo (2D BH GRE) R2* -MRI. However, breath-holding is not possible in most pediatric patients or those with respiratory problems, and three-dimensional free-breathing radial GRE (3D FB rGRE) has emerged as a viable alternative. PURPOSE To evaluate the performance of a 3D FB rGRE and validate its R2* and fat fraction (FF) quantification with 3D breath-hold Cartesian GRE (3D BH cGRE) and biopsy-calibrated 2D BH GRE across a wide range of HICs. STUDY TYPE Retrospective. SUBJECTS Twenty-nine patients with hepatic iron overload (22 females, median age: 15 [5-25] years). FIELD STRENGTH/SEQUENCE Three-dimensional radial and 2D and 3D Cartesian multi-echo GRE at 1.5 T. ASSESSMENT R2* and FF maps were computed for 3D GREs using a multi-spectral fat model and 2D GRE R2* maps were calculated using a mono-exponential model. Mean R2* and FF values were calculated via whole-liver contouring and T2* -thresholding by three operators. STATISTICAL TESTS Inter- and intra-observer reproducibility was assessed using Bland-Altman and intraclass correlation coefficient (ICC). Linear regression and Bland-Altman analysis were performed to compare R2* and FF values among the three acquisitions. One-way repeated-measures ANOVA and Wilcoxon signed-rank tests, respectively, were used to test for significant differences between R2* and FF values obtained with different acquisitions. Statistical significance was assumed at P < 0.05. RESULTS The mean biases and ICC for inter- and intra-observer reproducibility were close to 0% and >0.99, respectively for both R2* and FF. The 3D FB rGRE R2* and FF values were not significantly different (P > 0.44) and highly correlated (R2 ≥ 0.98) with breath-hold Cartesian GREs, with mean biases ≤ ±2.5% and slopes 0.90-1.12. In non-breath-holding patients, Cartesian GREs showed motion artifacts, whereas 3D FB rGRE exhibited only minimal streaking artifacts. DATA CONCLUSION Free-breathing 3D radial GRE is a viable alternative in non-breath-hold patients for accurate HIC estimation. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Shawyon Chase Rohani
- Department of Biomedical Engineering, The University of Memphis, Memphis, TN, USA
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Cara E. Morin
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Xiaodong Zhong
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Los Angeles, CA, USA
| | | | - Utsav Shrestha
- Department of Biomedical Engineering, The University of Memphis, Memphis, TN, USA
| | - Chris Goode
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Joseph Holtrop
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Ayaz Khan
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Ralf B. Loeffler
- Research Imaging NSW, University of New South Wales, Sydney, Australia
| | - Jane S. Hankins
- Department of Hematology, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | | | - Aaryani Tipirneni-Sajja
- Department of Biomedical Engineering, The University of Memphis, Memphis, TN, USA
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, USA
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Kafali SG, Armstrong T, Shih SF, Kim GJ, Holtrop JL, Venick RS, Ghahremani S, Bolster BD, Hillenbrand CM, Calkins KL, Wu HH. Free-breathing radial magnetic resonance elastography of the liver in children at 3 T: a pilot study. Pediatr Radiol 2022; 52:1314-1325. [PMID: 35366073 PMCID: PMC9192470 DOI: 10.1007/s00247-022-05297-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 12/02/2021] [Accepted: 01/20/2022] [Indexed: 12/17/2022]
Abstract
BACKGROUND Magnetic resonance (MR) elastography of the liver measures hepatic stiffness, which correlates with the histopathological staging of liver fibrosis. Conventional Cartesian gradient-echo (GRE) MR elastography requires breath-holding, which is challenging for children. Non-Cartesian radial free-breathing MR elastography is a potential solution to this problem. OBJECTIVE To investigate radial free-breathing MR elastography for measuring hepatic stiffness in children. MATERIALS AND METHODS In this prospective pilot study, 14 healthy children and 9 children with liver disease were scanned at 3 T using 2-D Cartesian GRE breath-hold MR elastography (22 s/slice) and 2-D radial GRE free-breathing MR elastography (163 s/slice). Each sequence was acquired twice. Agreement in the stiffness measurements was evaluated using Lin's concordance correlation coefficient (CCC) and within-subject mean difference. The repeatability was assessed using the within-subject coefficient of variation and intraclass correlation coefficient (ICC). RESULTS Fourteen healthy children and seven children with liver disease completed the study. Median (±interquartile range) normalized measurable liver areas were 62.6% (±26.4%) and 44.1% (±39.6%) for scan 1, and 60.3% (±21.8%) and 43.9% (±44.2%) for scan 2, for Cartesian and radial techniques, respectively. Hepatic stiffness from the Cartesian and radial techniques had close agreement with CCC of 0.89 and 0.94, and mean difference of 0.03 kPa and -0.01 kPa, for scans 1 and 2. Cartesian and radial techniques achieved similar repeatability with within-subject coefficient of variation=1.9% and 3.4%, and ICC=0.93 and 0.92, respectively. CONCLUSION In this pilot study, radial free-breathing MR elastography was repeatable and in agreement with Cartesian breath-hold MR elastography in children.
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Affiliation(s)
- Sevgi Gokce Kafali
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA 90095 USA ,Department of Bioengineering, University of California Los Angeles, Los Angeles, CA USA
| | - Tess Armstrong
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA 90095 USA
| | - Shu-Fu Shih
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA 90095 USA ,Department of Bioengineering, University of California Los Angeles, Los Angeles, CA USA
| | - Grace J. Kim
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA 90095 USA
| | - Joseph L. Holtrop
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN USA
| | - Robert S. Venick
- Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Shahnaz Ghahremani
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA 90095 USA
| | | | - Claudia M. Hillenbrand
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN USA ,Research Imaging NSW, University of New South Wales, Sydney, Australia
| | - Kara L. Calkins
- Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Holden H. Wu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA 90095 USA ,Department of Bioengineering, University of California Los Angeles, Los Angeles, CA USA
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Armstrong T, Zhong X, Shih SF, Felker E, Lu DS, Dale BM, Wu HH. Free-breathing 3D stack-of-radial MRI quantification of liver fat and R 2* in adults with fatty liver disease. Magn Reson Imaging 2021; 85:141-152. [PMID: 34662702 DOI: 10.1016/j.mri.2021.10.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 10/07/2021] [Accepted: 10/12/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate the agreement, intra-session repeatability, and inter-reader agreement of liver proton-density fat fraction (PDFF) and R2* quantification using free-breathing 3D stack-of-radial MRI, with and without self-gated motion compensation, compared to reference breath-hold techniques in subjects with fatty liver disease (FLD). METHODS In this institutional review board-approved prospective study, thirty-eight adults with FLD and/or iron overload (24 male, 58 ± 12 years) were imaged at 3T using free-breathing stack-of-radial MRI, breath-hold 3D Cartesian MRI, and breath-hold single-voxel MR spectroscopy (SVS). Each sequence was acquired twice in random order. To assess agreement compared to reference breath-hold techniques, the dependency of liver PDFF and/or R2* quantification on the sequence, radial sampling factor, and radial self-gating temporal resolution was assessed by calculating the Bayesian mean difference (MDB) of the posteriors. Intra-session repeatability and inter-reader agreement (two independent readers) were assessed by the coefficient of repeatability (CR) and intraclass correlation coefficient (ICC), respectively. RESULTS Thirty-five participants (21 male, 57 ± 12 years) were included for analysis. Both free-breathing radial MRI techniques (with and without self-gating) achieved ICC ≥ 0.92 for quantifying PDFF and R2*, and quantified PDFF with MDB < 1.2% compared to breath-hold techniques. Free-breathing radial MRI required self-gating to accurately quantify R2* (MDB < 10s-1 with self-gating; MDB < 50s-1 without self-gating). The radial sampling factor affected PDFF and R2* quantification while the radial self-gating temporal resolution only affected R2* quantification. Repeated self-gated free-breathing radial MRI scans achieved CR < 3% and CR < 27 s-1 for PDFF and R2*, respectively. CONCLUSION A free-breathing stack-of-radial MRI technique with self-gating demonstrated agreement, repeatability, and inter-reader agreement compared to reference breath-hold techniques for quantification of liver PDFF and R2* in adults with FLD.
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Affiliation(s)
- Tess Armstrong
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Xiaodong Zhong
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States
| | - Shu-Fu Shih
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Ely Felker
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - David S Lu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Brian M Dale
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Cary, NC, United States
| | - Holden H Wu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States.
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9
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Zhong X, Armstrong T, Gao C, Nickel MD, Han F, Dale BM, Li X, Kafali SG, Hu P, Wu HH, Deshpande V. Accelerated k-space shift calibration for free-breathing stack-of-radial MRI quantification of liver fat and R 2 ∗. Magn Reson Med 2021; 87:281-291. [PMID: 34412158 DOI: 10.1002/mrm.28981] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 07/29/2021] [Accepted: 08/02/2021] [Indexed: 01/08/2023]
Abstract
PURPOSE To develop an accelerated k-space shift calibration method for free-breathing 3D stack-of-radial MRI quantification of liver proton-density fat fraction (PDFF) and R 2 ∗ . METHODS Accelerated k-space shift calibration was developed to partially skip acquisition of k-space shift data in the through-plane direction then interpolate in processing, as well as to reduce the in-plane averages. A multi-echo stack-of-radial sequence with the baseline calibration was evaluated on a phantom versus vendor-provided reference-standard PDFF and R 2 ∗ values at 1.5T, and in 13 healthy subjects and 5 clinical subjects at 3T with respect to reference-standard breath-hold Cartesian acquisitions. PDFF and R 2 ∗ maps were calculated with different calibration acceleration factors offline and compared to reference-standard values using Bland-Altman analysis. Bias and uncertainty were evaluated using normal distribution and Bayesian probability of difference (P < .05 considered significant). RESULTS Bland-Altman plots of phantom and in vivo data showed that substantial acceleration was highly feasible in both through-plane and in-plane directions. Compared to the baseline calibration without acceleration, Bayesian analysis revealed no significant differences on biases and uncertainties of PDFF and R 2 ∗ measurements with all acceleration methods in this study, except the method with through-plane acceleration equaling slices and averages equaling 20 for PDFF and R 2 ∗ (both P < .001) for the phantom. A six-fold reduction in equivalent calibration acquisition time (time saving ≥25 s and ≥80.7%) was achieved using recommended acceleration factors for the in vivo protocols in this study. CONCLUSION This proposed method may allow accelerated calibration for free-breathing stack-of-radial MRI PDFF and R 2 ∗ mapping.
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Affiliation(s)
- Xiaodong Zhong
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Los Angeles, California, USA
| | - Tess Armstrong
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Physics and Biology in Medicine Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Chang Gao
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Physics and Biology in Medicine Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Marcel D Nickel
- MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany
| | - Fei Han
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Los Angeles, California, USA
| | - Brian M Dale
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Cary, North Carolina, USA
| | - Xinzhou Li
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Sevgi G Kafali
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Peng Hu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Physics and Biology in Medicine Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Holden H Wu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Physics and Biology in Medicine Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Vibhas Deshpande
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Austin, Texas, USA
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10
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Duffy PB, Stemmer A, Callahan MJ, Cravero JP, Johnston PR, Warfield SK, Bixby SD. Free-breathing radial stack-of-stars three-dimensional Dixon gradient echo sequence in abdominal magnetic resonance imaging in sedated pediatric patients. Pediatr Radiol 2021; 51:1645-1653. [PMID: 33830291 DOI: 10.1007/s00247-021-05054-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 01/30/2021] [Accepted: 03/16/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND There is a strong need for improvements in motion robust T1-weighted abdominal imaging sequences in children to enable high-quality, free-breathing imaging. OBJECTIVE To compare imaging time and quality of a radial stack-of-stars, free-breathing T1-weighted gradient echo acquisition (volumetric interpolated breath-hold examination [VIBE]) three-dimensional (3-D) Dixon sequence in sedated pediatric patients undergoing abdominal magnetic resonance imaging (MRI) against conventional Cartesian T1-weighed sequences. MATERIALS AND METHODS This study was approved by the institutional review board with informed consent obtained from all subjects. Study subjects included 31 pediatric patients (19 male, 12 female; median age: 5 years; interquartile range: 5 years) undergoing abdominal MRI at 3 tesla with a free-breathing T1-weighted radial stack-of-stars 3-D VIBE Dixon prototype sequence, StarVIBE Dixon (radial technique), between October 2018 and June 2019 with previous abdominal MR imaging using conventional Cartesian T1-weighed imaging (traditional technique). MRI component times were recorded as well as the total number of non-contrast T1-weighted sequences. Two radiologists independently rated images for quality using a scale from 1 to 5 according to the following metrics: overall image quality, hepatic edge sharpness, hepatic vessel clarity and respiratory motion robustness. Scores were compared between the groups. RESULTS Mean T1-weighted imaging times for all subjects were 3.63 min for radial exams and 8.01 min for traditional exams (P<0.001), and total non-contrast imaging time was 32.7 min vs. 43.9 min (P=0.002). Adjusted mean total MRI time for all subjects was 60.2 min for radial exams and 65.7 min for traditional exams (P=0.387). The mean number of non-contrast T1-weighted sequences performed in radial MRI exams was 1.0 compared to 1.9 (range: 0-6) in traditional exams (P<0.001). StarVIBE Dixon outperformed Cartesian methods in all quality metrics. The mean overall image quality (scale 1-5) was 3.95 for radial exams and 3.31 for traditional exams (P<0.001). CONCLUSION Radial stack-of-stars 3-D VIBE Dixon during free-breathing abdominal MRI in pediatric patients offers improved image quality compared to Cartesian T1-weighted imaging techniques with decreased T1-weighted and total non-contrast imaging time. This has important implications for children undergoing sedation for imaging.
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Affiliation(s)
- Patrick B Duffy
- Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., Boston, MA, 02115, USA
| | | | - Michael J Callahan
- Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., Boston, MA, 02115, USA
| | - Joseph P Cravero
- Department of Anesthesiology, Boston Children's Hospital, Boston, MA, USA
| | - Patrick R Johnston
- Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., Boston, MA, 02115, USA
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., Boston, MA, 02115, USA
| | - Sarah D Bixby
- Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., Boston, MA, 02115, USA.
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11
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Li Z, Fu Z, Keerthivasan M, Bilgin A, Johnson K, Galons JP, Vedantham S, Martin DR, Altbach MI. Rapid high-resolution volumetric T 1 mapping using a highly accelerated stack-of-stars Look Locker technique. Magn Reson Imaging 2021; 79:28-37. [PMID: 33722634 PMCID: PMC8107135 DOI: 10.1016/j.mri.2021.03.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 03/03/2021] [Accepted: 03/03/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE To develop a fast volumetric T1 mapping technique. MATERIALS AND METHODS A stack-of-stars (SOS) Look Locker technique based on the acquisition of undersampled radial data (>30× relative to Nyquist) and an efficient multi-slab excitation scheme is presented. A principal-component based reconstruction is used to reconstruct T1 maps. Computer simulations were performed to determine the best choice of partitions per slab and degree of undersampling. The technique was validated in phantoms against reference T1 values measured with a 2D Cartesian inversion-recovery spin-echo technique. The SOS Look Locker technique was tested in brain (n = 4) and prostate (n = 5). Brain T1 mapping was carried out with and without kz acceleration and results between the two approaches were compared. Prostate T1 mapping was compared to standard techniques. A reproducibility study was conducted in brain and prostate. Statistical analyses were performed using linear regression and Bland Altman analysis. RESULTS Phantom T1 values showed excellent correlations between SOS Look Locker and the inversion-recovery spin-echo reference (r2 = 0.9965; p < 0.0001) and between SOS Look Locker with slab-selective and non-slab selective inversion pulses (r2 = 0.9999; p < 0.0001). In vivo results showed that full brain T1 mapping (1 mm3) with kz acceleration is achieved in 4 min 21 s. Full prostate T1 mapping (0.9 × 0.9 × 4 mm3) is achieved in 2 min 43 s. T1 values for brain and prostate were in agreement with literature values. A reproducibility study showed coefficients of variation in the range of 0.18-0.2% (brain) and 0.15-0.18% (prostate). CONCLUSION A rapid volumetric T1 mapping technique was developed. The technique enables high-resolution T1 mapping with adequate anatomical coverage in a clinically acceptable time.
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Affiliation(s)
- Zhitao Li
- Department of Electrical and Computer Engineering, the University of Arizona, Tucson, AZ 85721, USA; Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | - Zhiyang Fu
- Department of Electrical and Computer Engineering, the University of Arizona, Tucson, AZ 85721, USA; Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | - Mahesh Keerthivasan
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA; Siemens Healthcare USA, Tucson, AZ 85724, USA
| | - Ali Bilgin
- Department of Electrical and Computer Engineering, the University of Arizona, Tucson, AZ 85721, USA; Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA; Department of Biomedical Engineering, the University of Arizona, Tucson, AZ 85721, USA
| | - Kevin Johnson
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | | | | | - Diego R Martin
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA
| | - Maria I Altbach
- Department of Medical Imaging, the University of Arizona, Tucson, AZ 85724, USA; Department of Biomedical Engineering, the University of Arizona, Tucson, AZ 85721, USA.
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12
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Mozes FE. Editorial for "Free-Breathing Volumetric Liver R2* and Proton-Density Fat Fraction Quantification in Pediatric Patients Using Stack-of- Radial MRI With Self-Gating Motion Compensation". J Magn Reson Imaging 2020; 53:130-131. [PMID: 32521077 DOI: 10.1002/jmri.27243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 05/18/2020] [Indexed: 11/09/2022] Open
Affiliation(s)
- Ferenc E Mozes
- Radcliffe Department of Medicine, Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, UK
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