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Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats
BACKGROUND: Diffusion tensor imaging (DTI) is mainly used for detecting white matter fiber in the brain. DTI was applied to assess fiber in liver disorders in previous studies. However, the data obtained have been insufficient in determining if DTI can be used to exactly stage chronic hepatitis. Thi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333377/ https://www.ncbi.nlm.nih.gov/pubmed/32615932 http://dx.doi.org/10.1186/s12880-020-00466-3 |
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author | Huang, Mengping Lu, Xin Wang, Xiaofeng Shu, Jian |
author_facet | Huang, Mengping Lu, Xin Wang, Xiaofeng Shu, Jian |
author_sort | Huang, Mengping |
collection | PubMed |
description | BACKGROUND: Diffusion tensor imaging (DTI) is mainly used for detecting white matter fiber in the brain. DTI was applied to assess fiber in liver disorders in previous studies. However, the data obtained have been insufficient in determining if DTI can be used to exactly stage chronic hepatitis. This study assessed the value of DTI for staging of liver fibrosis (F), necroinflammatory activity (A) and steatosis (S) with chronic hepatitis in rats. METHODS: Seventy male Sprague-Dawley rats were divided into a control group(n = 10) and an experimental group(n = 60). The rat models of chronic hepatitis were established by abdominal subcutaneous injections of 40% CCl(4). All of the rats underwent 3.0 T MRI. Regions of interest (ROIs) were subjected to DTI to estimate the MR parameters (rADC value and FA value). Histopathology was used as the reference standard. Multiple linear regression was used to analyze the associations between the MR parameters and pathology. The differences in the MR parameters among the pathological stages were evaluated by MANOVA or ANOVA. The LSD test was used to test for differences between each pair of groups. ROC analysis was also performed. RESULTS: The count of each pathology was as follows: F0(n = 15), F1(n = 11), F2(n = 6), F3(n = 9), F4(n = 6); A0(n = 8), A1(n = 16), A2(n = 16), A3(n = 7); S0(n = 10), S1(n = 7), S2(n = 3), S3(n = 11), S4(n = 16). The rADC value had a negative correlation with liver fibrosis (r = − 0.392, P = 0.008) and inflammation (r = − 0.359, P = 0.015). The FA value had a positive correlation with fibrosis (r = 0.409, P = 0.005). Significant differences were found in the FA values between F4 and F0 ~ F3 (P = 0.03), while no significant differences among F0 ~ F3 were found (P > 0.05). The AUC of the FA value differentiating F4 from F0 ~ F3 was 0.909 (p < 0.001) with an 83.3% sensitivity and an 85.4% specificity when the FA value was at the cut-off of 588.089 (× 10(− 6) mm(2)/s). CONCLUSION: The FA value for DTI can distinguish early cirrhosis from normal, mild and moderate liver fibrosis, but the rADC value lacked the ability to differentiate among the fibrotic grades. Both the FA and rADC values were unable to discriminate the stages of necroinflammatory activity and steatosis. |
format | Online Article Text |
id | pubmed-7333377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73333772020-07-06 Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats Huang, Mengping Lu, Xin Wang, Xiaofeng Shu, Jian BMC Med Imaging Research Article BACKGROUND: Diffusion tensor imaging (DTI) is mainly used for detecting white matter fiber in the brain. DTI was applied to assess fiber in liver disorders in previous studies. However, the data obtained have been insufficient in determining if DTI can be used to exactly stage chronic hepatitis. This study assessed the value of DTI for staging of liver fibrosis (F), necroinflammatory activity (A) and steatosis (S) with chronic hepatitis in rats. METHODS: Seventy male Sprague-Dawley rats were divided into a control group(n = 10) and an experimental group(n = 60). The rat models of chronic hepatitis were established by abdominal subcutaneous injections of 40% CCl(4). All of the rats underwent 3.0 T MRI. Regions of interest (ROIs) were subjected to DTI to estimate the MR parameters (rADC value and FA value). Histopathology was used as the reference standard. Multiple linear regression was used to analyze the associations between the MR parameters and pathology. The differences in the MR parameters among the pathological stages were evaluated by MANOVA or ANOVA. The LSD test was used to test for differences between each pair of groups. ROC analysis was also performed. RESULTS: The count of each pathology was as follows: F0(n = 15), F1(n = 11), F2(n = 6), F3(n = 9), F4(n = 6); A0(n = 8), A1(n = 16), A2(n = 16), A3(n = 7); S0(n = 10), S1(n = 7), S2(n = 3), S3(n = 11), S4(n = 16). The rADC value had a negative correlation with liver fibrosis (r = − 0.392, P = 0.008) and inflammation (r = − 0.359, P = 0.015). The FA value had a positive correlation with fibrosis (r = 0.409, P = 0.005). Significant differences were found in the FA values between F4 and F0 ~ F3 (P = 0.03), while no significant differences among F0 ~ F3 were found (P > 0.05). The AUC of the FA value differentiating F4 from F0 ~ F3 was 0.909 (p < 0.001) with an 83.3% sensitivity and an 85.4% specificity when the FA value was at the cut-off of 588.089 (× 10(− 6) mm(2)/s). CONCLUSION: The FA value for DTI can distinguish early cirrhosis from normal, mild and moderate liver fibrosis, but the rADC value lacked the ability to differentiate among the fibrotic grades. Both the FA and rADC values were unable to discriminate the stages of necroinflammatory activity and steatosis. BioMed Central 2020-07-02 /pmc/articles/PMC7333377/ /pubmed/32615932 http://dx.doi.org/10.1186/s12880-020-00466-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Huang, Mengping Lu, Xin Wang, Xiaofeng Shu, Jian Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats |
title | Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats |
title_full | Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats |
title_fullStr | Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats |
title_full_unstemmed | Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats |
title_short | Diffusion tensor imaging quantifying the severity of chronic hepatitis in rats |
title_sort | diffusion tensor imaging quantifying the severity of chronic hepatitis in rats |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333377/ https://www.ncbi.nlm.nih.gov/pubmed/32615932 http://dx.doi.org/10.1186/s12880-020-00466-3 |
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