ArticleBMC medical imaging2025
Perilesional dominance: radiomics of multiparametric MRI enhances differentiation of IgG4-Related ophthalmic disease and orbital MALT lymphoma.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Review
- An explainable radiomics model based on multiparametric magnetic resonance for differentiating benign and malignant orbital tumors.BMC cancer · 2026Article
- Application of artificial intelligence in differentiating IgG4-related ophthalmic disease and orbital MALT lymphoma: a review of radiomics and deep learning advances.Frontiers in immunology · 2026Review
- Article
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7 authors.
Funding
Abstract
backgroundTo develop and validate a diagnostic framework integrating intralesional (ILN) and perilesional (PLN) radiomics derived from multiparametric MRI (mpMRI) for distinguishing IgG4-related ophthalmic disease (IgG4-ROD) from orbital mucosa-associated lymphoid tissue (MALT) lymphoma.
methodsThis multicenter retrospective study analyzed 214 histopathologically confirmed cases (68 IgG4-ROD, 146 MALT lymphoma) from two institutions (2019-2024). A LASSO-SVM classifier was optimized through comparative evaluation of seven machine learning models, incorporating fused radiomic features (1,197 features) from ILN/PLN regions. Diagnostic performance was benchmarked against two subspecialty radiologists (10-20 years' experience) using receiver operating characteristics - area under the curve (AUC), precision-recall AUC (PR-AUC), and decision curve analysis (DCA), adhering to CLEAR/METRICS guidelines.
resultsThe fusion model (FR_RAD) achieved state-of-the-art performance, with an AUC of 0.927 (95% CI 0.902-0.958) and a PR-AUC of 0.901 (95% CI 0.862-0.940) in the training set, and an AUC of 0.907 (95% CI 0.857-0.965) and a PR-AUC of 0.872 (95% CI 0.820-0.924) on external testing. In contrast, subspecialty radiologists achieved lower AUCs of 0.671-0.740 (95% CI 0.630-0.780) and PR-AUCs of 0.553-0.632 (95% CI 0.521-0.664) (all p < 0.001). FR_RAD also outperformed radiologists in accuracy (88.6% vs. 66.2% and 71.3%; p < 0.01). DCA demonstrated a net benefit of 0.18 at a high-risk threshold of 30%, equivalent to avoiding 18 unnecessary biopsies per 100 cases.
conclusionsThe fusion model integrating multi-regional radiomics from mpMRI achieves precise differentiation between IgG4-ROD and orbital MALT lymphoma, outperforming subspecialty radiologists. This approach highlights the transformative potential of spatial radiomics analysis in resolving diagnostic uncertainties and reducing reliance on invasive procedures for orbital lesion characterization.
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