Staging liver fibrosis with various diffusion-weighted magnetic resonance imaging models

盒内非相干运动 有效扩散系数 医学 峰度 磁共振成像 肝纤维化 核医学 数学 磁共振弥散成像 放射科 纤维化 核磁共振 病理 统计 物理
作者
Yan-Li Jiang,Juan Li,Pengfei Zhang,Fengxian Fan,Jie Zou,Pin Yang,Pengfei Wang,Shaoyu Wang,Jing Zhang
出处
期刊:World Journal of Gastroenterology [Baishideng Publishing Group Co]
卷期号:30 (9): 1164-1176 被引量:1
标识
DOI:10.3748/wjg.v30.i9.1164
摘要

BACKGROUND Diffusion-weighted imaging (DWI) has been developed to stage liver fibrosis. However, its diagnostic performance is inconsistent among studies. Therefore, it is worth studying the diagnostic value of various diffusion models for liver fibrosis in one cohort. AIM To evaluate the clinical potential of six diffusion-weighted models in liver fibrosis staging and compare their diagnostic performances. METHODS This prospective study enrolled 59 patients suspected of liver disease and scheduled for liver biopsy and 17 healthy participants. All participants underwent multi-b value DWI. The main DWI-derived parameters included Mono-apparent diffusion coefficient (ADC) from mono-exponential DWI, intravoxel incoherent motion model-derived true diffusion coefficient (IVIM-D), diffusion kurtosis imaging-derived apparent diffusivity (DKI-MD), stretched exponential model-derived distributed diffusion coefficient (SEM-DDC), fractional order calculus (FROC) model-derived diffusion coefficient (FROC-D) and FROC model-derived microstructural quantity (FROC-μ), and continuous-time random-walk (CTRW) model-derived anomalous diffusion coefficient (CTRW-D) and CTRW model-derived temporal diffusion heterogeneity index (CTRW-α). The correlations between DWI-derived parameters and fibrosis stages and the parameters’ diagnostic efficacy in detecting significant fibrosis (SF) were assessed and compared. RESULTS CTRW-D (r = -0.356), CTRW-α (r = -0.297), DKI-MD (r = -0.297), FROC-D (r = -0.350), FROC-μ (r = -0.321), IVIM-D (r = -0.251), Mono-ADC (r = -0.362), and SEM-DDC (r = -0.263) were significantly correlated with fibrosis stages. The areas under the ROC curves (AUCs) of the combined index of the six models for distinguishing SF (0.697-0.747) were higher than each of the parameters alone (0.524-0.719). The DWI models’ ability to detect SF was similar. The combined index of CTRW model parameters had the highest AUC (0.747). CONCLUSION The DWI models were similarly valuable in distinguishing SF in patients with liver disease. The combined index of CTRW parameters had the highest AUC.

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