1147 - Clinical Implementation of an Automated VMAT Treatment Planning Script for Head and Neck Cancer Patients: 3 Year-Experience

N. Kovalchuk¹, P. Dong², M. Xiang³, E. J. Moding⁴, M. F. Gensheimer⁵, B. M. Beadle⁵, Q. T. Le⁶, L. Xing¹, and Y. Yang¹; ¹Department of Radiation Oncology, Stanford University, Stanford, CA, ²Stanford University School of Medicine, Stanford, CA, ³Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, ⁴Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, ⁵Radiation Oncology, Stanford University, Stanford, CA, ⁶Stanford University, Stanford, CA

Purpose/Objective(s): This study aimed to assess the impact of implementing an in-house automated VMAT treatment planning script for patients with head and neck (HN) cancer. Materials/

Methods: The automated planning script, developed using Eclipse Scripting Application Programming Interface (ESAPI), was introduced in 2020 for HN cancer patients. To evaluate its efficacy, dosimetric indices for 1000 patients treated between 2017 and 2023 were compared, with 500 patients planned manually and 500 patients planned using the automated script. Differences in target and organ-at-risk metrics were analyzed using a t-test, with p < 0.05 considered significant. Additionally, 5 radiation oncologists blindly reviewed 20 plans (10 auto- and 10 manual) and assessed their clinical acceptability and preference for treatment.
Results: Compared to the manually generated clinical head and neck plans, all auto plans achieved PTV D_95% coverage and critical organs at risk sparing without statistically significant change in average global D_max (107.4% for manual vs 107.5% for automated plans). The auto-planning solution provided reduced maximum doses to brainstem and spinal cord (average reductions of 3.6 ± 0.1 Gy and 2.1 ± 1.1 Gy, respectively, all p <0.001), reduced average mean doses to contralateral submandibular gland, ipsilateral parotid, oral cavity, cochleae, larynx, contralateral parotid (reductions of 4.1 ± 1.2 Gy, 3.9 ± 0.4 Gy, 2.5 ± 0.1 Gy, 2.4 ± 0.2 Gy, 2.0 ± 1.4 Gy, 1.5 ± 0.1 Gy, respectively, all p < 0.03) and reduced average maximum doses to mandible and lips (reductions of 2.9 ± 2.8 Gy and 2.3 ± 1.2 Gy, respectively, all p < 0.04). In the blinded review by physicians, out of 50 responses 94% considered auto-plans clinically acceptable versus 86% for manual plans. Overall, 7 auto-plans were preferred for treatment, 1 was deemed equivalent, while only 2 manual plans were preferred.
Conclusion: The automated treatment planning script significantly improved plan quality for HN cancer patients by reducing important dosimetric indices to organs at risk while maintaining target coverage and dose homogeneity. Radiation oncologists appreciate reproducibility and efficiency of the auto-planning script in generating high-quality plans within a short timeframe.