Task-Specific Multimodal Fusion of MRI Radiomics, Patient-Specific Biomechanics, and Clinical Data for Noninvasive Liver Fibrosis Assessment
Chenming Wang, Jian Zhang, Xin Tian, Xuheng Teng, Ling Gong, Junping Shi, Zhenming YuanAccurate noninvasive assessment of liver fibrosis requires complementary characterization of tissue structure, biomechanical properties, and systemic disease status. In this retrospective single-center study, we developed a Task-Specific Multimodal Fusion (TSMF) framework integrating MRI radiomics, patient-specific Finite Element Modeling (FEM)-derived biomechanical features, clinical variables, and elastography-derived stiffness information. Data from 90 patients were used for pathology-based fibrosis classification, while subsets of patients with available FibroScan and Magnetic Resonance Elastography (MRE) measurements were further analyzed for continuous estimation of MRE-derived liver stiffness. For fibrosis classification, a clinical auxiliary gated-correction strategy built on a radiomics–FEM backbone achieved an AUROC of 0.818 ± 0.069, outperforming the best dual-modal model (0.794 ± 0.060) and direct tri-modal fusion (0.762 ± 0.096). For MRE stiffness estimation, FibroScan alone provided a strong baseline (R2 = 0.710 ± 0.084; mean absolute error [MAE] = 0.691 ± 0.133 kPa), while prediction-level stacking consistently improved performance over the corresponding direct-fusion approaches. Among the evaluated combinations, stacking of FibroScan and FEM features achieved an R2 of 0.723 ± 0.076 and an MAE of 0.665 ± 0.129 kPa, compared with an R2 of 0.689 ± 0.098 and an MAE of 0.723 ± 0.146 kPa using direct fusion. Notably, incorporating additional modalities did not necessarily improve performance, suggesting that effective multimodal modeling depends more on information complementarity and task-appropriate fusion strategies than on the number of modalities alone. These findings support a task-specific multimodal integration for noninvasive liver fibrosis assessment. The FibroScan-anchored regression framework demonstrated the feasibility of predicting MRE-derived liver stiffness within the study cohort; however, its clinical agreement, generalizability, and potential applicability as an alternative to direct MRE measurement require further validation.