Clinical outcomes of stereotactic MR-guided adaptive radiation therapy for high-risk lung tumors

Purpose: Magnetic resonance (MR)-guided SABR was performed for patients with lung tumors in whom treatment delivery was challenging owing to tumor location, motion, or pulmonary comorbidity. Because stereotactic MR-guided adaptive radiation therapy (SMART) is a novel approach, we studied clinical outcomes in these high-risk lung tumors. Methods and Materials: Fifty consecutive patients (54 lung tumors) underwent SMART between 2016 and 2018 for either a primary lung cancer (29 patients) or for lung metastases (21 patients). Eligible patients had risk factors that could predispose them to toxicity, including a central tumor location (n = 30), previous thoracic radiation therapy (n = 17), and interstitial lung disease (n = 7). A daily 17-second breath-hold MR scan was acquired in treatment position, and on-table plan adaptation was performed using the anatomy of the day. Gated SABR was delivered during repeated breath-holds under continuous MR guidance. Results: All but 1 patient completed the planned SMART schedule. With daily plan adaptation, a biologically effective dose ≥100 Gy to 95% of the planning target volume was delivered in 50 tumors (93%). Median follow-up was 21.7 months (95% confidence interval, 19.9-28.1). Local control and overall and disease-free survival rates at 12 months were 95.6%, 88.0%, and 63.6%, respectively. Local failures developed in 4 patients: in 2 after reirradiation for a recurrent lung cancer and in 2 patients with a colorectal metastasis. Overall rates of any grade ≥2 and ≥3 toxicity were 30% and 8%, respectively. Commonest toxicities were grade ≥2 radiation pneumonitis (12%) and chest wall pain (8%). No grade 4 or 5 toxicities were observed. Conclusions: Use of MR-guided SABR resulted in low rates of high-grade toxicity and encouraging early local control in a cohort of high-risk lung tumors. Additional studies are needed to identify patients who are most likely to benefit from the SMART approach