Stereotactic radiosurgery for radiation‑induced meningiomas: long‑term institutional outcomes with patient- and lesion‑level analyses and an updated meta‑analysis
摘要
Radiation-induced meningiomas (RIMs) are late sequelae of cranial irradiation that are often multifocal, atypical, and surgically challenging. Stereotactic radiosurgery (SRS) is a minimally invasive treatment alternative, but long-term outcomes have not been described fully.
MethodsAll patients with RIM treated with single-fraction SRS at a single tertiary care center (2002–2025) were reviewed for lesion-level local control (LC), progression-free survival (PFS), and toxicity graded by Common Terminology Criteria for Adverse Events v5.0 criteria. Histopathology was available for 9 of 25 lesions (5 WHO grade 1, 4 WHO grade 2); the remainder were diagnosed radiographically. We also conducted a systematic review and random-effects meta-analysis.
ResultsAmong 9 patients with 25 lesions, median age was 40 years, latency was 29 years, and median dose was 15 Gy (range 13–15 Gy), selected based on proximity to critical neurovascular structures. Median follow-up was 61 months; 1- and 5-year LC were 92% and 76%, respectively. LC declined with larger tumors (100% for < 10 mm, 94% for 10–<15 mm, 83% for 15–20 mm, and 58% for ≥ 20 mm; log-rank p = .04). Five-year PFS was 78%. No patients experienced toxicity greater than grade 3. Across four published series (110 patients with 212 lesions), pooled 5-year LC was 78% (95% confidence interval (CI) 69–85), PFS was 72% (95% CI 63–79), and overall toxicity was 12% (95% CI 9–17). Combining these cohorts yielded a pooled 5-year LC rate of 77% (95% CI 70–84).
ConclusionsSRS and fractionated SRS provide durable tumor control for most RIMs with low morbidity. Efficacy is lower for lesions ≥ 20 mm, and resection should be prioritized. Pooled 5-year LC approaches 80%, with between-study heterogeneity largely driven by cohort size and follow-up duration. Standardized toxicity reporting and prospective registries are needed to refine long-term risk modeling.