Abstract Pituitary lesions are increasingly detected due to widespread use of magnetic resonance imaging (MRI), with incidental findings (“incidentalomas”) now identified in 10–20% of brain imaging studies. MRI remains the gold standard for evaluating sellar and parasellar pathology, offering superior soft-tissue contrast without ionizing radiation. This comprehensive narrative review synthesizes current evidence on the role of MRI in evaluating pituitary lesions, with a primary focus on intrasellar pathologies and post-operative imaging. We highlight technical advances from dynamic contrast-enhanced (DCE) imaging to emerging artificial intelligence (AI) applications. Dynamic contrast-enhanced MRI significantly improves microadenoma detection, with sensitivity exceeding 90% compared to approximately 50% with static imaging. High-field 3 T imaging offers 10–15% improved detection compared to 1.5 T systems. Post-operative baseline imaging optimally performed at 3–4 months minimizes false-positive residual tumor interpretation. AI-based radiomics models demonstrate promising accuracy (AUC 0.85–0.95) for predicting tumor consistency, invasiveness, and recurrence, though prospective validation remains limited. A systematic approach to pituitary MRI interpretation, integrating optimized protocols with emerging AI tools, enhances diagnostic accuracy and guides clinical decision-making.
Khimani et al. (Tue,) studied this question.