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Geometric accuracy and time efficiency evaluation of a deep learning auto-segmentation system for head and neck radiotherapy: a single-center validation study

   
@article{TRO10554,
	author = {Po-Jui Chen and Ching-Hsin Lee and Sheng-Ping Hung and Chia-Wei Lee and I-Ling Shih and Ann-Joy Cheng and Joseph Tung-Chieh Chang},
	title = {Geometric accuracy and time efficiency evaluation of a deep learning auto-segmentation system for head and neck radiotherapy: a single-center validation study},
	journal = {Therapeutic Radiology and Oncology},
	volume = {10},
	number = {0},
	year = {2026},
	keywords = {},
	abstract = {Background: Automated segmentation in radiotherapy is critical for workflow efficiency, yet commercial prototypes require rigorous validation before deployment. This study aims to validate the geometric accuracy and time efficiency of a prototype deep learning contouring (DLC) system for organs at risk (OARs) in a cohort of head and neck cancer (HNC) patients.Methods: Fifty consecutive patients receiving intensity-modulated proton therapy (IMPT) for HNC between September 2019 and January 2021 at a single tertiary referral center in Taiwan were enrolled. Manual contours (MC) defined by one of three radiation oncologists served as the reference standard. We evaluated three strategies: unmodified DLC (DLC-u), DLC with manual modification (DLC-m), and MC. Performance was assessed using the Dice similarity coefficient (DSC), Hausdorff distance (HD), and a 5-point subjective clinical usability scale. Time efficiency was compared using paired t-tests.Results: DLC-u demonstrated robust geometric concordance for large, high-contrast organs such as the eyes, brainstem, and parotid glands with mean DSC ≥0.80. In contrast, performance for small or low-contrast structures was suboptimal, with the optic chiasm and pharyngeal constrictor muscle (PCM) achieving mean DSCs of 0.44 and 0.42, respectively. The correlation between objective metrics and subjective scores was modest (|τ| ≤0.42). The human-in-the-loop workflow (DLC-m) significantly reduced total contouring time from 35.3 to 24.7 minutes (30.0% reduction across all OARs; P},
	issn = {2616-2768},	url = {https://tro.amegroups.org/article/view/10554}
}