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Jiang Y, Fan F, Zhang P, Wang J, Huang W, Zheng Y, Guo R, Wang S, Zhang J. Staging liver fibrosis by a continuous-time random-walk diffusion model. Magn Reson Imaging 2024; 105:100-107. [PMID: 37956960 DOI: 10.1016/j.mri.2023.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/25/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023]
Abstract
PURPOSE Noninvasive assessment of liver fibrosis holds significant clinical importance. We aimed to evaluate the clinical potential of using a continuous-time random-walk diffusion model (CTRW) for staging liver fibrosis. METHODS This prospective study included 52 patients suspected of liver disease and scheduled for liver biopsy. All patients underwent multi-b value diffusion-weighted imaging (DWI) using a 1.5 T MR scanner to derive the anomalous diffusion coefficient (D) and temporal (α) and spatial (β) diffusion heterogeneity indexes sourced from the CTRW. The mono-exponential DWI-derived apparent diffusion coefficient (ADC), transient elastography-derived liver stiffness measurement (LSM), aspartate aminotransferase-to-platelet ratio index (APRI), and fibrosis-4 (FIB-4) index were calculated. We assessed and compared the correlations of these parameters with fibrosis stages and their efficacy in staging liver fibrosis. RESULTS Significant correlations with fibrosis stages were found for APRI (r = 0.336), FIB-4 (r = 0.351), LSM (r = 0.523), D (r = -0.458), and ADC (r = -0.473). Significant differences were observed between APRI, LSM, D, and ADC of different fibrosis stages. The diagnostic performance of an index that combined D, α, β, ADC, and LSM was superior to that of ADC or LSM alone for fibrosis stage F ≥ 2 and better than the index that combined D, α, β for fibrosis stage F ≥ 4. CONCLUSIONS Accurate liver fibrosis staging was achieved with a model that combined CTRW-derived parameters (D, α, and β), ADC, and LSM. The model could serve as a reliable tool for noninvasive fibrosis evaluation.
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Affiliation(s)
- Yanli Jiang
- Second Clinical School, Lanzhou University, Lanzhou, China; Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Fengxian Fan
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Pengfei Zhang
- Second Clinical School, Lanzhou University, Lanzhou, China; Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Jun Wang
- Second Clinical School, Lanzhou University, Lanzhou, China; Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Wenjing Huang
- Second Clinical School, Lanzhou University, Lanzhou, China; Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Yu Zheng
- Second Clinical School, Lanzhou University, Lanzhou, China; Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Ruiqing Guo
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China.
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Liu X, Zhou J, Zhu L, Zhang X, Li F. Diagnostic accuracy of apparent diffusion coefficient values combined with γ-glutamyl transpeptidase-to-platelet ratio parameters for predicting hepatitis B-related fibrosis. Clin Res Hepatol Gastroenterol 2022; 46:101968. [PMID: 35649482 DOI: 10.1016/j.clinre.2022.101968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 05/12/2022] [Accepted: 05/27/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVES The accuracy of non-invasive liver fibrosis diagnosis based on the apparent diffusion coefficient (ADC) value combined with the γ-glutamyl transpeptidase-to-platelet ratio (GPR) model to predict the stage of hepatitis B-related fibrosis has not been reported. This study aimed to evaluate the diagnostic efficacy of ADC value combined with GPR for liver fibrosis grading. METHODS The data of 180 patients with chronic hepatitis B (CHB) diagnosed by liver biopsy were analyzed. The ADC value, GPR, and their combination were assessed in different cirrhosis stages using receiver operating characteristic curve analysis to evaluate their value in diagnosing liver fibrosis. RESULTS We observed that liver fibrosis stages were inversely associated with ADC values (r=-0.691, P<0.001), and positively associated with GPR (r=0.502, P<0.001). The area under the curve for diagnostic efficacy of ADC values, GPR, and their combination for F≥2 liver fibrosis was 0.831, 0.749, and 0.858, respectively, and for F≥3 was 0.872, 0.771, and 0.903, respectively. The diagnostic cutoffs of the combination for each stage were -7.07, -12.21 and -37.75, respectively. CONCLUSIONS The combined diagnostic tool of ADC and GPR may improve the accuracy of hepatitis B-related liver fibrosis diagnosis, especially for F≥3.
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Affiliation(s)
- Xingxiang Liu
- Department of Laboratory Medicine, Huai'an Infectious Disease Hospital, Jiangsu, China
| | - Jian Zhou
- Department of Gastroenterology, Huai'an Hospital of Huai'an City, Jiangsu, China
| | - Liyao Zhu
- Department of Hepatology, Huai'an Infectious Disease Hospital, Jiangsu, China
| | - Xin Zhang
- Department of Medical Imaging, Huai'an Infectious Disease Hospital, Jiangsu, China.
| | - Feng Li
- Department of Medical Imaging, Huai'an Infectious Disease Hospital, Jiangsu, China.
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Dai X, Zeng Y, Zhang H, Gu Z, Gong Q, Luo K. Advances on Nanomedicines for Diagnosis and Theranostics of Hepatic Fibrosis. ADVANCED NANOBIOMED RESEARCH 2021. [DOI: 10.1002/anbr.202000091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Affiliation(s)
- Xinghang Dai
- Huaxi MR Research Center (HMRRC) Department of Radiology Functional and molecular imaging Key Laboratory of Sichuan Province West China Hospital Sichuan University Chengdu 610041 China
- West China School of Medicine Sichuan University Chengdu 610041 China
| | - Yujun Zeng
- Huaxi MR Research Center (HMRRC) Department of Radiology Functional and molecular imaging Key Laboratory of Sichuan Province West China Hospital Sichuan University Chengdu 610041 China
| | - Hu Zhang
- Huaxi MR Research Center (HMRRC) Department of Radiology Functional and molecular imaging Key Laboratory of Sichuan Province West China Hospital Sichuan University Chengdu 610041 China
- Amgen Bioprocessing Centre Keck Graduate Institute CA 91711 USA
| | - Zhongwei Gu
- Research Unit of Psychoradiology Chinese Academy of Medical Sciences Chengdu 610041 China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC) Department of Radiology Functional and molecular imaging Key Laboratory of Sichuan Province West China Hospital Sichuan University Chengdu 610041 China
- Research Unit of Psychoradiology Chinese Academy of Medical Sciences Chengdu 610041 China
| | - Kui Luo
- Huaxi MR Research Center (HMRRC) Department of Radiology Functional and molecular imaging Key Laboratory of Sichuan Province West China Hospital Sichuan University Chengdu 610041 China
- Research Unit of Psychoradiology Chinese Academy of Medical Sciences Chengdu 610041 China
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Serag D, Ragab E. Diffusion-weighted MRI in staging of post hepatitis C fibrosis: does ADC value challenge liver biopsy? THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020. [DOI: 10.1186/s43055-020-00283-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
There is obvious interest in finding a non-invasive diagnostic tool to detect the development of hepatic fibrosis and distinguish between its various stages. Chronic inflammation of the liver secondary to viral hepatitis, autoimmune conditions, sclerosing cholangitis, drug toxicity, chronic alcohol intake, different metabolic disorders, and steatosis lead to fibrosis and maybe cirrhosis. The current study aimed to assess the usefulness of diffusion-weighted magnetic resonance imaging (DW-MRI) in diagnosis of post hepatitis C fibrosis and detection of its stage.
Results
A prospective study had included 232 participants; 120 patients had chronic hepatitis C with/without HCC and 112 subjects had normal liver. There was no significant difference between the two groups regarding age or gender (p 0.192 and 0.227 respectively). DW-MRI was performed using 1.5 T machine. The mean liver ADC values and normalized liver ADC (liver ADC/spleen ADC) were measured at b value 800 s/mm2; both were significantly lower among cases than controls. Cutoff values of liver ADC were 1.531 × 10−3 mm2/s, 1.409 × 10−3 mm2/s, 1.192 × 10−3 mm2/s, and 1.093 × 10−3 mm2/s for METAVIR stages ≥ F1, ≥ F2, ≥ F3, and F4, respectively. Normalized liver ADC showed larger area under the curve (AUC) than mean liver ADC in all differentiation categories except for differentiating between F0 and all other fibrosis stages.
Conclusion
In line with the literature, DW-MR imaging using b value of 800 s/mm2 has proved to be a valuable diagnostic technique for detection and staging of post hepatitis C fibrosis/cirrhosis being noninvasive procedure with acceptable accuracy. DWI using liver/spleen ADC values raised the diagnostic performance with AUC more than 90% in all fibrosis stages on METAVIR score.
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