Deep B Gandhi1, Amol Pednekar2,3,4, Adebayo B Braimah1, Jonathan Dudley1, Jean A Tkach5,6, Andrew T Trout5,6,7, Alexander G Miethke7,8, Marnix D Franck5,9, Jeremiah A Heilman10, Bogdan Dzyubak11, David S Lake11, Jonathan R Dillman1,5,6. 1. Department of Radiology, Imaging Research Center (IRC), Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA. 2. Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. Amol.Pednekar@cchmc.org. 3. Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA. Amol.Pednekar@cchmc.org. 4. Imaging Research Center, 3333 Burnet Avenue, Suite S1.533, Cincinnati, OH, 45229, USA. Amol.Pednekar@cchmc.org. 5. Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 6. Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA. 7. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA. 8. Division of Hepatology, Gastroenterology and Nutrition, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA. 9. Radboud University, Nijmegen, The Netherlands. 10. Resoundant, Inc., Rochester, MN, USA. 11. Department of Radiology, Mayo Clinic, Rochester, MN, USA.
Abstract
PURPOSE: To compare automated versus standard of care manual processing of 2D gradient recalled echo (GRE) liver MR Elastography (MRE) in children and young adults. MATERIALS AND METHODS: 2D GRE liver MRE data from research liver MRI examinations performed as part of an autoimmune liver disease registry between March 2017 and March 2020 were analyzed retrospectively. All liver MRE data were acquired at 1.5 T with 60 Hz mechanical vibration frequency. For manual processing, two independent readers (R1, R2) traced regions of interest on scanner generated shear stiffness maps. Automated processing was performed using MREplus+ (Resoundant Inc.) using 90% (A90) and 95% (A95) confidence masks. Agreement was evaluated using intra-class correlation coefficients (ICC) and Bland-Altman analyses. Classification performance was evaluated using receiver operating characteristic curve (ROC) analyses. RESULTS: In 65 patients with mean age of 15.5 ± 3.8 years (range 8-23 years; 35 males) median liver shear stiffness was 2.99 kPa (mean 3.55 ± 1.69 kPa). Inter-reader agreement for manual processing was very strong (ICC = 0.99, mean bias = 0.01 kPa [95% limits of agreement (LoA): - 0.41 to 0.44 kPa]). Correlation between manual and A95 automated processing was very strong (R1: ICC = 0.988, mean bias = 0.13 kPa [95% LoA: - 0.40 to 0.68 kPa]; R2: ICC = 0.987, mean bias = 0.13 kPa [95% LoA: - 0.44 to 0.69 kPa]). Automated measurements were perfectly replicable (ICC = 1.0; mean bias = 0 kPa). CONCLUSION: Liver shear stiffness values obtained using automated processing showed excellent agreement with manual processing. Automated processing of liver MRE was perfectly replicable.
PURPOSE: To compare automated versus standard of care manual processing of 2D gradient recalled echo (GRE) liver MR Elastography (MRE) in children and young adults. MATERIALS AND METHODS: 2D GRE liver MRE data from research liver MRI examinations performed as part of an autoimmune liver disease registry between March 2017 and March 2020 were analyzed retrospectively. All liver MRE data were acquired at 1.5 T with 60 Hz mechanical vibration frequency. For manual processing, two independent readers (R1, R2) traced regions of interest on scanner generated shear stiffness maps. Automated processing was performed using MREplus+ (Resoundant Inc.) using 90% (A90) and 95% (A95) confidence masks. Agreement was evaluated using intra-class correlation coefficients (ICC) and Bland-Altman analyses. Classification performance was evaluated using receiver operating characteristic curve (ROC) analyses. RESULTS: In 65 patients with mean age of 15.5 ± 3.8 years (range 8-23 years; 35 males) median liver shear stiffness was 2.99 kPa (mean 3.55 ± 1.69 kPa). Inter-reader agreement for manual processing was very strong (ICC = 0.99, mean bias = 0.01 kPa [95% limits of agreement (LoA): - 0.41 to 0.44 kPa]). Correlation between manual and A95 automated processing was very strong (R1: ICC = 0.988, mean bias = 0.13 kPa [95% LoA: - 0.40 to 0.68 kPa]; R2: ICC = 0.987, mean bias = 0.13 kPa [95% LoA: - 0.44 to 0.69 kPa]). Automated measurements were perfectly replicable (ICC = 1.0; mean bias = 0 kPa). CONCLUSION: Liver shear stiffness values obtained using automated processing showed excellent agreement with manual processing. Automated processing of liver MRE was perfectly replicable.
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