Fangyan Li, Yao Liang, Xing Xia, Yong Wen, Maowen Tang, Zhaoshu Huang, Na Hu, Peng Luo, Pinggui Lei
{"title":"MRI-Based Radiomic Biomarkers for Non-invasive Assessment of Liver Fibrosis in MASLD: Diagnostic Performance and Molecular Mechanisms in a Rat Model.","authors":"Fangyan Li, Yao Liang, Xing Xia, Yong Wen, Maowen Tang, Zhaoshu Huang, Na Hu, Peng Luo, Pinggui Lei","doi":"10.1016/j.acra.2025.05.069","DOIUrl":null,"url":null,"abstract":"<p><strong>Rationale and objectives: </strong>Accurate, non-invasive assessment of liver fibrosis (LF) remains a clinical challenge. This study aimed to develop a MRI-based radiomic risk score (Radscore) for staging LF and to explore the biological relevance of radiomic features using transcriptomic analysis.</p><p><strong>Materials and methods: </strong>A total of 146 male Sprague-Dawley rats were split into two cohorts at random: 87 for training and 59 for testing. T2-weighted fat-suppressed (T2FS), proton density fat fraction (PDFF), in-phase, and out-of-phase images were among the multiparametric MRI sequences obtained. After radiomic features were collected, LASSO regression and redundancy analysis were used to create a 12-feature Radscore. The achieving area under the curve (AUC) was applied to assess the diagnostic performance of the Radscore for liver fibrosis detection (F0 vs. ≥F1) and staging (≤F2 vs. ≥F3). Additionally, 32 liver tissues underwent transcriptome sequencing. Radscore-associated genes were found using Pearson correlation, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. Functional enrichment analysis was then performed.</p><p><strong>Results: </strong>The Radscore demonstrated robust diagnostic performance in detecting liver fibrosis, with AUC values of 0.90 in the training cohort and 0.89 in the testing cohort (F0 vs. ≥F1). For fibrosis staging (≤F2 vs. ≥F3), the AUCs were 0.97 and 0.96, respectively. Furthermore, the Radscore was positively correlated with 10 fibrosis-associated genes (e.g., Col1a1, Col1a2, Ptprc) involved in extracellular matrix remodeling and inflammatory processes. In contrast, it exhibited negative correlations with 10 genes related to mitochondrial function and vascular integrity (e.g., Ndufa7, Cox5b, Kdr).</p><p><strong>Conclusion: </strong>The Radscore shows promise as a non-invasive imaging biomarker for liver fibrosis in MASLD. Its correlation with transcriptomic alterations indicates potential biological relevance, establishing a foundation for future studies investigating radiogenomic connections within the framework of precision medicine.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Academic Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.acra.2025.05.069","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Rationale and objectives: Accurate, non-invasive assessment of liver fibrosis (LF) remains a clinical challenge. This study aimed to develop a MRI-based radiomic risk score (Radscore) for staging LF and to explore the biological relevance of radiomic features using transcriptomic analysis.
Materials and methods: A total of 146 male Sprague-Dawley rats were split into two cohorts at random: 87 for training and 59 for testing. T2-weighted fat-suppressed (T2FS), proton density fat fraction (PDFF), in-phase, and out-of-phase images were among the multiparametric MRI sequences obtained. After radiomic features were collected, LASSO regression and redundancy analysis were used to create a 12-feature Radscore. The achieving area under the curve (AUC) was applied to assess the diagnostic performance of the Radscore for liver fibrosis detection (F0 vs. ≥F1) and staging (≤F2 vs. ≥F3). Additionally, 32 liver tissues underwent transcriptome sequencing. Radscore-associated genes were found using Pearson correlation, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. Functional enrichment analysis was then performed.
Results: The Radscore demonstrated robust diagnostic performance in detecting liver fibrosis, with AUC values of 0.90 in the training cohort and 0.89 in the testing cohort (F0 vs. ≥F1). For fibrosis staging (≤F2 vs. ≥F3), the AUCs were 0.97 and 0.96, respectively. Furthermore, the Radscore was positively correlated with 10 fibrosis-associated genes (e.g., Col1a1, Col1a2, Ptprc) involved in extracellular matrix remodeling and inflammatory processes. In contrast, it exhibited negative correlations with 10 genes related to mitochondrial function and vascular integrity (e.g., Ndufa7, Cox5b, Kdr).
Conclusion: The Radscore shows promise as a non-invasive imaging biomarker for liver fibrosis in MASLD. Its correlation with transcriptomic alterations indicates potential biological relevance, establishing a foundation for future studies investigating radiogenomic connections within the framework of precision medicine.
期刊介绍:
Academic Radiology publishes original reports of clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, image-guided interventions and related techniques. It also includes brief technical reports describing original observations, techniques, and instrumental developments; state-of-the-art reports on clinical issues, new technology and other topics of current medical importance; meta-analyses; scientific studies and opinions on radiologic education; and letters to the Editor.