Purpose: To analyze institutional performance irradiating IROC Houston’s lung phantom to identify traits that are most predictive of a failing phantom result.
Methods: Irradiation results of 1643 lung phantoms between 2012-2020 were abstracted. Univariate analysis, factor analysis, clustering, and random forest models were used to associate irradiation conditions and plan complexity scores with phantom results. Phantom results included pass/fail classification, average TLD ratio for primary target, and percent of pixels passing gamma. The following treatment parameters were evaluated in terms of how they predicted these outcomes: planning system, irradiation year, algorithm, machine model, energy, irradiation technique, motion technique, motion extent, and 17 complexity scores were utilized including: monitor units (MU), MLC speed modulation, and modulation complexity score (MCS).
Results: All evaluated complexity scores showed a statistically significant increase in complexity except MCS and MLC speed modulation (p<0.05; regression). In terms of predicting pass/fail, 3D conformal radiation therapy (3D-CRT) was statistically superior to dynamic MLC (p = 0.004; chi squared) and segmental (p = 0.041) irradiation techniques. In addition, gating was statistically inferior to no motion management (p < 0.001) and tracking (p = 0.02). Internal target volume (ITV) motion techniques was also statistically inferior to no motion management (p = 0.02). For overall pass/fail and percent pixels passing gamma, motion extent and motion management technique were the two most important predictor. However, for TLD prediction, MU was the most important predictor.
Conclusion: Dynamic MLC and segmental irradiation techniques lag behind simpler techniques in 3D-CRT, while gating motion management lags behind tracking. Motion and use of MU, which is higher in more complex irradiations, shows to be the most important parameters regardless of which endpoint is predicted. As complexity increases, especially adding in the confounding need to manage motion, implementation and proper use in the clinic is a vital task.
Funding Support, Disclosures, and Conflict of Interest: This work was supported by grants CA214526 and CA180803 awarded by NCI.