Literature DB >> 33791254

Use of Texture Analysis on Noncontrast MRI in Classification of Early Stage of Liver Fibrosis.

Ru Zhao1,2, Xi-Jun Gong2, Ya-Qiong Ge3, Hong Zhao2, Long-Sheng Wang2, Hong-Zhen Yu4, Bin Liu1.   

Abstract

Purpose. To compare the diagnostic value of texture analysis- (TA-) derived parameters from out-of-phase T1W, in-phase T1W, and T2W images in the classification of the early stage of liver fibrosis. Methods. Patients clinically diagnosed with hepatitis B infection, who underwent liver biopsy and noncontrast MRI scans, were enrolled. TA parameters were extracted from out-of-phase T1-weighted (T1W), in-phase T1W, and T2-weighted (T2W) images and calculated using Artificial Intelligent Kit (AK). Features were extracted including first-order, shape, gray-level cooccurrence matrix, gray-level run-length matrix, neighboring gray one tone difference matrix, and gray-level differential matrix. After statistical analyses, final diagnostic models were constructed. Receiver operating curves (ROCs) and areas under the ROC (AUCs) were used to assess the diagnostic value of each final model and 100-time repeated cross-validation was applied to assess the stability of the logistic regression models. Results. A total of 57 patients were enrolled in this study, with 27 in the fibrosis stage < 2 and 30 in stages ≥ 2. Overall, 851 features were extracted per ROI. Eight features with high correlation were selected by the maximum relevance method in each sequence, and all had a good diagnostic performance. ROC analysis of the final models showed that all sequences had a preferable performance with AUCs of 0.87, 0.90, and 0.96 in T2W and in-phase and out-of-phase T1W, respectively. Cross-validation results reported the following values of mean accuracy, specificity, and sensitivity: 0.98 each for out-of-phase T1W; 0.90, 0.89, and 0.90 for in-phase T1W; and 0.86, 0.88, 0.84 for T2W in the training set, and 0.76, 0.81, and 0.72 for out-of-phase T1W; 0.74, 0.72, and 0.75 for in-phase T1W; and 0.63, 0.64, and 0.63 for T2W for the test group, respectively. Conclusion. Noncontrast MRI scans with texture analysis are viable for classifying the early stages of liver fibrosis, exhibiting excellent diagnostic performance.
Copyright © 2021 Ru Zhao et al.

Entities:  

Year:  2021        PMID: 33791254      PMCID: PMC7997774          DOI: 10.1155/2021/6677821

Source DB:  PubMed          Journal:  Can J Gastroenterol Hepatol        ISSN: 2291-2789


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  2 in total

1.  Usefulness of Noncontrast MRI-Based Radiomics Combined Clinic Biomarkers in Stratification of Liver Fibrosis.

Authors:  Ru Zhao; Hong Zhao; Ya-Qiong Ge; Fang-Fang Zhou; Long-Sheng Wang; Hong-Zhen Yu; Xi-Jun Gong
Journal:  Can J Gastroenterol Hepatol       Date:  2022-06-21

2.  Computed Tomography Radiomics-Based Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

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Journal:  Front Med (Lausanne)       Date:  2022-03-24
  2 in total

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