Magnetic resonance imaging-based artificial intelligence in identifying imaging phenotypes of non-secondary trigeminal neuralgia: a systematic review and meta-analysis

Background Conventional visual magnetic resonance imaging (MRI) assessment of neurovascular compression may overlook subtle trigeminal nerve abnormalities. We evaluated the pooled discriminative performance of MRI-based artificial intelligence (AI) models for identifying pain-related trigeminal nerve phenotypes in non-secondary trigeminal neuralgia. Methods PubMed, Embase, Web of Science, and the Cochrane Library were searched from inception to April 2026. Eligible studies developed or validated MRI-based radiomics or AI models and provided sufficient information to construct or approximate 2 × 2 contingency tables. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Sensitivity and specificity were jointly pooled using a bivariate random-effects model, and a summary receiver operating characteristic curve was constructed. Results Eight studies comprising 628 nerve-level observations (298 symptomatic or affected nerves and 330 comparator nerves) were included. Pooled sensitivity was 0.83 (95% confidence interval [CI], 0.78–0.87), pooled specificity was 0.81 (95% CI, 0.74–0.86), and the summary area under the curve was 0.86 (95% CI, 0.82–0.88). Results remained stable after leave-one-out analysis. Radiomics-only models and models combining radiomic and anatomical features showed broadly comparable performance. Conclusions Preliminary evidence suggests that MRI-based AI models provide moderate discriminative ability for identifying the affected nerve side in trigeminal neuralgia, with relatively stable sensitivity but lower specificity. Given the limited number of studies, particularly in subgroup analyses, these findings should be interpreted cautiously. Such models may currently serve as adjunctive imaging tools. Larger multicenter studies with independent external validation and clinically relevant reference standards are needed.