Feasibility of histogram analysis of susceptibility-weighted MRI for staging of liver fibrosis

Yang, Zhao; Liang, He; Hu, Xin Xing; Huang, Ya Qin; Ding, Ying; Yang, Shan; Zeng, Meng Su; Rao, Sheng-Xiang

doi:10.5152/dir.2016.15284

Cited by 12 publications

(9 citation statements)

References 34 publications

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“…All parameters showed excellent inter- and intra-observer agreement. Consistent with other studies [ 26 – 29 ], the most promising parameters of our study are diff-entropy, entropy, and diff-variance, achieving an AUC value greater than 0.8 ( p < 0.001) in differentiating intermediate-to-high-risk advanced fibrosis from low risk.…”

Section: Discussionsupporting

confidence: 91%

“…Although the texture of T1map was rarely studied in the abdomen, animal experiments have found that the texture parameters of T1 map can be used for detection of hepatic fibrosis [ 26 ]; studies in patients with NAFLD have shown that entropy on T1-weighted images can help measure hepatic fibrosis [ 27 ]; Fujimoto et al [ 28 ] have reported that entropy of ADC map correlated with pathologic fibrosis stage in chronic hepatitis C; Yang et al [ 29 ] have demonstrated that histogram analysis of susceptibility-weighted imaging, particularly the variance, can be used for predicting advanced liver fibrosis. Histopathologically, the early accumulation of fat within the liver tends to be diffuse and uneven distributed in NAFLD [ 30 ]; the fatty acids (secreted from the fat) can contribute to the formation of lipotoxic species, oxidant stress, and inflammasome activation.…”

Section: Discussionmentioning

confidence: 99%

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Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD

Zhu

et al. 2020

Eur Radiol

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Objectives To assess whole-liver texture analysis on T1 maps for risk stratification of advanced fibrosis in patients with suspected nonalcoholic fatty liver disease (NAFLD). Methods This retrospective study included 53 patients. Histogram and texture parameters (volume, mean, SD, median, 5th percentile, 95th percentile, skewness, kurtosis, diff-entropy, diff-variance, contrast, and entropy) of T1 maps were calculated based on the semi-automatically segmented whole-liver volume. A two-step approach combining the Nonalcoholic Fatty Liver Disease Fibrosis Score (NFS) and Fibrosis-4 Index (FIB-4) with the liver stiffness measurement (LSM) for the risk stratification was used. Univariate analysis was performed to identify significant parameters. Logistic regression models were then run on the significant features. Diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis. Results In total, 33 (62%) subjects had a low risk and 20 (38%) subjects had an intermediate-to-high risk of advanced fibrosis. The following significantly different parameters with the best performance were diff-entropy, entropy, and diff-variance, with AUROC 0.837 (95% CI 0.73–0.95), 0.821 (95% CI 0.71–0.94), and 0.807 (95% CI 0.69–0.93). The optimal combination of median, 5th percentile, and diff-entropy as a multivariate model improved the diagnostic performance to diagnose an intermediate-to-high risk of advanced fibrosis with AUROC 0.902(95% CI 0.79–0.97). Conclusions Parameters obtained by histogram and texture analysis of T1 maps may be a noninvasive analytical approach for stratifying the risk of advanced fibrosis in NAFLD. Key Points • Variable flip angle (VFA) T1 mapping can be used to acquire 3D T1 maps within a clinically acceptable duration. • Whole-liver histogram and texture parameters on T1 maps in patients with NAFLD can distinguish those with an intermediate-to-high risk of advanced fibrosis. • The multivariate model of combination of texture parameters improved the diagnostic performance for a high risk of advanced fibrosis and clinical parameters offer no added value to the multivariate model.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD

Zhu

et al. 2020

Eur Radiol

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“…Honsoul Kim et al [18] reported that the correct coefficient of variation (cCV) of histograms of the hepatobiliary phase of gadoxetic acid-enhanced MRI demonstrated statistically significant differences among different pathologic fibrosis grades (p < 0.001). ZX Yang et al showed that variance for susceptibility-weighted imaging (SWI) with TE = 10 ms could be helpful for identifying advanced liver fibrosis or cirrhotic liver [19]. Our study demonstrated SD had a relative poor correlation with liver fibrosis grades, one possible reason may be that ADC maps have an inherent low image resolution.…”

Section: Discussionmentioning

confidence: 64%

“…MR histogram is a new approach in hepatic texture analysis for depicting the distribution of signal intensity levels using acquired MR data, which can reflect the heterogeneity of pathologic changes. Previous study demonstrated that MR histogram analysis facilitated detection and staging of liver fibrosis in susceptibilityweighted MRI (SWI), gadoxetic acid-enhanced MRI and conventional DWI [17][18][19][20]. Thus, we aimed to evaluate whether histogram analysis of volumetric liver ADC maps could quantify liver fibrosis stages.…”

Section: Introductionmentioning

confidence: 99%

Value of whole-liver apparent diffusion coefficient histogram analysis for quantification of liver fibrosis stages

Yang

Grimm

et al. 2019

Chin J Acad Radiol

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Aim To explore whether volumetric acquisition of histogram analysis of apparent diffusion coefficient (ADC) maps could quantify liver fibrosis stages. Materials and methods 84 patients underwent MRI exams including DWI before surgery or liver biopsy were included. Histogram analysis of whole liver ADC maps were performed and parameters including ADC mean, ADC median, ADC skewness, ADC kurtosis, ADC standard deviation (SD), ADC 5th, 10th, 25th, 75th, 90th and 95th percentiles were calculated. The correlations between different histopathologic grades and histogram analysis parameters were determined. For the significant parameters, receiver operating characteristics (ROC) analyses were further established to evaluate the potential diagnostic performance for differentiating liver fibrosis stages. Results The ADC mean and ADC median, ADC SD, ADC5th, 10th, 25th, 75th, 90th and 95th percentile were significantly lower with the increasing grade of liver fibrosis (rho: from − 0.580 to − 0.230). ADC skewness and ADC kurtosis were significantly higher with the increasing grade of liver fibrosis (rho: 0.243, 0.347, respectively). Areas under the ROC curve (AUC) of ADC mean and ADC 75th percentile for identification liver fibrosis (F1-F4), moderate to advanced liver fibrosis (F2-F4), advanced liver fibrosis (F3-F4), cirrhosis (F4) were 0.87, 0.83, 0.82, 0.76 and 0.88, 0.82, 0.80, 0.74, respectively. Conclusion Histogram analysis of volumetric acquisition of liver ADC maps has a potential value for quantifying liver fibrosis grades.

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“…SWI has a demonstrated ability to quantify and grade liver fibrosis in patients with chronic liver disease. However, it is more sensitive in high-stage liver fibrosis (F3, F4) than low-stage liver fibrosis (F0–F2) because of more nonhomogeneous iron deposition and secondary pathologic changes that occur at higher grades of liver fibrosis [32].…”

Section: Evaluation Of Liver Fibrosis By Mri Us and Ctmentioning

confidence: 99%

Liver Fibrosis Conventional and Molecular Imaging Diagnosis Update

Li¹,

Sun²,

Chen³

et al. 2019

J Liver

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Liver fibrosis is a serious, life-threatening disease with high morbidity and mortality that result from diverse causes. Liver biopsy, considered the “gold standard” to diagnose, grade, and stage liver fibrosis, has limitations in terms of invasiveness, cost, sampling variability, inter-observer variability, and the dynamic process of fibrosis. Compelling evidence has demonstrated that all stages of fibrosis are reversible if the injury is removed. There is a clear need for safe, effective, and reliable non-invasive assessment modalities to determine liver fibrosis in order to manage it precisely in personalized medicine. However, conventional imaging methods used to assess morphological and structural changes related to liver fibrosis, including ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), are only useful in assessing advanced liver disease, including cirrhosis. Functional imaging techniques, including MR elastography (MRE), US elastography, and CT perfusion are useful for assessing moderate to advanced liver fibrosis. MRE is considered the most accurate noninvasive imaging technique, and US elastography is currently the most widely used noninvasive means. However, these modalities are less accurate in early-stage liver fibrosis and some factors affect the accuracy of these techniques. Molecular imaging is a target-specific imaging mechanism that has the potential to accurately diagnose early-stage liver fibrosis. We provide an overview of recent advances in molecular imaging for the diagnosis and staging of liver fibrosis which will enable clinicians to monitor the progression of disease and potentially reverse liver fibrosis. We compare the promising technologies with conventional and functional imaging and assess the utility of molecular imaging in precision and personalized clinical medicine in the early stages of liver fibrosis.

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Feasibility of histogram analysis of susceptibility-weighted MRI for staging of liver fibrosis

Cited by 12 publications

References 34 publications

Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD

Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD

Value of whole-liver apparent diffusion coefficient histogram analysis for quantification of liver fibrosis stages

Liver Fibrosis Conventional and Molecular Imaging Diagnosis Update

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