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Simulation-Free Adaptive Prostate Stereotactic Body Radiation Therapy on Magnetic Resonance-Linac: Technical
Nicolas Côté1, Sun Lian2, Himanshu Nagar2
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York; Department of Physics, Université de Montréal, Montréal, Quebec, Canada.
Purpose:
To develop and evaluate 2 simulation-free (SF) stereotactic body radiation therapy (SBRT) workflows for prostate cancer on magnetic resonance (MR)-Linac: one using a diagnostic MR reference scan and another using a preapproved template scan.
Methods And Materials:
Population-based relative electron density (RED) values were derived from 100 prostate SBRT patients on the Elekta Unity MR-Linac and validated on a separate cohort of 10 patients for dosimetric equivalence. Two SF approaches were evaluated in another independent cohort of 10 patients using reference plans derived from: (1) a diagnostic MR scan (5 retrospective, 5 prospective), and (2) a digitally created pelvic phantom scan using population-based RED (all retrospective). The performance of artificial intelligence-generated contours was investigated during adaptive treatments using surface Dice (sDSC) with 1 mm tolerance and added path length. All adaptive plans, from both SF and the clinically delivered workflow, were compared in terms of dose metrics and monitor unit usage. A focused failure modes and effects analysis identified and mitigated diagnostic MR SF-specific risks by calculating the risk priority number (RPN).
Results:
Population-based RED assignments resulted in mean dose differences under 1%. Artificial intelligence contours showed strong agreement with physician-approved contours, with sDSC and added path length of 0.96/26.2cm,0.98/17.2cm,0.99/0.4cm, and 0.99/0.01cm for bladder, rectum, penile bulb, and bone, respectively. Across both SF workflows, adaptive plans were clinically comparable to the standard workflow, with mean dose differences from -1.7% to 4.6% and mean monitor unit differences remaining under 2%. Failure modes and effects analysis identified 3 high-risk failure modes: mislabeling diagnostic MR scans (RPN=39), case tracking lapses (RPN=29), and incorrect RED assignment (RPN=22), all mitigated through workflow refinements and training. The diagnostic MR SF workflow has been clinically implemented, treating 22 patients without failures.
Conclusions:
Both SF workflows eliminated the need for simulation, streamlining adaptive prostate SBRT without compromising plan quality. The template-based workflow further improved patient access by removing imaging prerequisites.
