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Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis

BACKGROUND: The assessment of liver surface nodularity (LSN) for staging hepatic fibrosis is restricted in clinical practice because it requires customized software and time‐consuming procedures. A simplified method to estimate LSN score may be useful in the clinic. PURPOSE: To evaluate the regional...

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Autores principales: Kim, Tae‐Hoon, Kim, Youe Ree, Jeong, Chang‐Won, Kim, Hyung Joong, Kim, Jin Woong, Lee, Young Hwan, Yoon, Kwon‐Ha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790718/
https://www.ncbi.nlm.nih.gov/pubmed/35543163
http://dx.doi.org/10.1002/jmri.28208
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author Kim, Tae‐Hoon
Kim, Youe Ree
Jeong, Chang‐Won
Kim, Hyung Joong
Kim, Jin Woong
Lee, Young Hwan
Yoon, Kwon‐Ha
author_facet Kim, Tae‐Hoon
Kim, Youe Ree
Jeong, Chang‐Won
Kim, Hyung Joong
Kim, Jin Woong
Lee, Young Hwan
Yoon, Kwon‐Ha
author_sort Kim, Tae‐Hoon
collection PubMed
description BACKGROUND: The assessment of liver surface nodularity (LSN) for staging hepatic fibrosis is restricted in clinical practice because it requires customized software and time‐consuming procedures. A simplified method to estimate LSN score may be useful in the clinic. PURPOSE: To evaluate the regional analysis of LSN and processing time in a single axial liver MR image for staging liver fibrosis. STUDY TYPE: Retrospective. POPULATION: A total of 210 subjects, a multicenter study. FIELD STRENGTH/SEQUENCE: A 3 T/noncontrast gradient echo T1WI. ASSESSMENT: Subjects were divided into five fibrosis groups (F(0) = 29; F(1) = 20; F(2) = 32; F(3) = 50; F(4) = 79) based on the METAVIR fibrosis scoring system. The mean LSN (on three slices) and regional LSN (on one slice) measurements, and the processing times, are compared. The regional LSN scores in five regions‐of‐interests (ROI(1‐5)) were analyzed in a single axial MRI at the level of the hilum by two independent observers. STATISTICAL TESTS: Regional variations in LSN scores were compared using ANOVA with Tukey test. Agreement between the mean and regional LSN measurements was evaluated using Pearson correlation coefficients (r) and Bland–Altman plots. The diagnostic performance of mean and regional LSN scores according to fibrosis stage was evaluated with the AUROC. A P value < 0.05 was considered statistically significant. RESULTS: Total processing time for a regional LSN measurement (3.6 min) was 75.5% less than that for mean LSN measurement (14.7 min). Mean LSN scores and all five regional LSN scores showed significant differences between fibrosis groups. Among regional LSN scores, ROI(5) showed the highest AUROC (0.871 at cut‐off 1.12) for discriminating F(0‐2) vs. F(3‐4) and the best correlation with mean LSN score (r = 0.800, −0.07 limit of agreement). CONCLUSION: Quantitative regional LSN measurement in a single axial MR image reduces processing time. Regional ROI(5) LSN score might be useful for clinical decision‐making and for distinguishing the difference between early fibrosis (F(0‐2)) and advanced fibrosis (F(3−4)) in the liver. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2
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spelling pubmed-97907182022-12-28 Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis Kim, Tae‐Hoon Kim, Youe Ree Jeong, Chang‐Won Kim, Hyung Joong Kim, Jin Woong Lee, Young Hwan Yoon, Kwon‐Ha J Magn Reson Imaging Research Articles BACKGROUND: The assessment of liver surface nodularity (LSN) for staging hepatic fibrosis is restricted in clinical practice because it requires customized software and time‐consuming procedures. A simplified method to estimate LSN score may be useful in the clinic. PURPOSE: To evaluate the regional analysis of LSN and processing time in a single axial liver MR image for staging liver fibrosis. STUDY TYPE: Retrospective. POPULATION: A total of 210 subjects, a multicenter study. FIELD STRENGTH/SEQUENCE: A 3 T/noncontrast gradient echo T1WI. ASSESSMENT: Subjects were divided into five fibrosis groups (F(0) = 29; F(1) = 20; F(2) = 32; F(3) = 50; F(4) = 79) based on the METAVIR fibrosis scoring system. The mean LSN (on three slices) and regional LSN (on one slice) measurements, and the processing times, are compared. The regional LSN scores in five regions‐of‐interests (ROI(1‐5)) were analyzed in a single axial MRI at the level of the hilum by two independent observers. STATISTICAL TESTS: Regional variations in LSN scores were compared using ANOVA with Tukey test. Agreement between the mean and regional LSN measurements was evaluated using Pearson correlation coefficients (r) and Bland–Altman plots. The diagnostic performance of mean and regional LSN scores according to fibrosis stage was evaluated with the AUROC. A P value < 0.05 was considered statistically significant. RESULTS: Total processing time for a regional LSN measurement (3.6 min) was 75.5% less than that for mean LSN measurement (14.7 min). Mean LSN scores and all five regional LSN scores showed significant differences between fibrosis groups. Among regional LSN scores, ROI(5) showed the highest AUROC (0.871 at cut‐off 1.12) for discriminating F(0‐2) vs. F(3‐4) and the best correlation with mean LSN score (r = 0.800, −0.07 limit of agreement). CONCLUSION: Quantitative regional LSN measurement in a single axial MR image reduces processing time. Regional ROI(5) LSN score might be useful for clinical decision‐making and for distinguishing the difference between early fibrosis (F(0‐2)) and advanced fibrosis (F(3−4)) in the liver. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2 John Wiley & Sons, Inc. 2022-05-11 2022-12 /pmc/articles/PMC9790718/ /pubmed/35543163 http://dx.doi.org/10.1002/jmri.28208 Text en © 2022 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Kim, Tae‐Hoon
Kim, Youe Ree
Jeong, Chang‐Won
Kim, Hyung Joong
Kim, Jin Woong
Lee, Young Hwan
Yoon, Kwon‐Ha
Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis
title Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis
title_full Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis
title_fullStr Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis
title_full_unstemmed Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis
title_short Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis
title_sort regional analysis of liver surface nodularity in a single axial mr image for staging liver fibrosis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790718/
https://www.ncbi.nlm.nih.gov/pubmed/35543163
http://dx.doi.org/10.1002/jmri.28208
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