AI for trigeminal neuralgia detection on MRI: meta-analysis shows high specificity and AUC

In a meta-analysis of 5 studies (577 patients), AI models for trigeminal neuralgia detection on MRI achieved pooled sensitivity 71% (95% CI 65-76%), specificity 92% (88-94%), and AUC 0.91 (0.88-0.93). High specificity may aid preop planning.

• Pooled diagnostic odds ratio was 26.71 (95% CI 16.38–43.56), indicating high discriminative ability.
• Positive likelihood ratio 8.5, negative likelihood ratio 0.32.
• Findings support AI's role in improving preoperative planning for microvascular decompression.

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