Somatostatin receptor PET-guided treatment and artificial intelligence applications in meningioma: a comprehensive...

Meningiomas are the most common primary intracranial tumors, with treatment involving resection and radiation therapy. However, therapeutic options are limited for recurrent or progressive disease, particularly in higher World Health Organization (WHO) grade tumors. Somatostatin receptor (SSTR) expression in meningiomas has opened new therapeutic opportunities as the differential SSTR2 overexpression permits molecular targeting using radiolabeled somatostatin analogs. PRRT offers promising therapeutic efficacy in select meningioma patients, with clinical responses strongly correlated to WHO tumor grade and SSTR expression levels. Combining SSTR PET imaging, to evaluate receptor density, with radiomic analysis can reveal tumor heterogeneity patterns and quantitative imaging features that can guide clinical decision-making and monitor treatment response. Integrating machine learning and artificial intelligence (AI) into clinical workflows offer novel approaches to apply quantitative SUV parameters, image texture features, and histopathologic data in order to identify patients with WHO grade II and III meningiomas at greater risk of tumor recurrence. Given the heterogeneity in imaging and treatment protocols across institutions and the limited number of PRRT-treated meningioma cohorts, future research should prioritize prospective, multicenter studies that integrate histologic and molecular imaging data to refine patient selection strategies and establish PRRT's role within personalized, precision cancer treatment paradigms.