PURPOSE: Clinical implementation of lattice radiotherapy (LRT) remains constrained by the absence of standardized, automated tools for comprehensive post-plan dosimetric analysis within commercial treatment planning systems (TPS). Herein, an automated script-based tool was developed using the Eclipse Scripting API (ESAPI) to enable rapid, standardized calculation of key LRT-specific metrics, including peak-to-valley dose ratio (PVDR), equivalent uniform dose (EUD), and ablative dose ratio (ADR). METHODS: A modular computational architecture comprising four functional layers was implemented: (1) user interface for protocol configuration, (2) computation layer integrating multiple PVDR algorithms, (3) data service layer providing direct read-only access to three-dimensional dose and anatomical data via ESAPI, and (4) reporting module. To accommodate ESAPI security restrictions, a dual-script architecture incorporating a preprocessing sphere segmentation module was established. Validation was performed using a retrospective cohort of 12 lung cancer LRT patients, with accuracy assessed against manual TPS measurements and established reference values. RESULTS: Concordance between automated and manual TPS measurements was high. Standard dose-volume parameter extraction exhibited perfect agreement. For spatially explicit PVDR analysis, mean absolute error relative to manual profile assessment was 0.034 (absolute VPDR units). EUD calculations deviated less than 3% from published reference data. Evaluation time per plan was reduced from 15.41 ± 3.20 min (manual) to 1.97 ± 0.34 min (automated), representing a 7.8-fold efficiency gain with elimination of inter-operator variability. CONCLUSION: This ESAPI-based tool automates and standardizes dosimetric evaluation of LRT, addressing a practical workflow bottleneck. Integration of multiple calculation methods within a deterministic framework establishes a shareable benchmark for consistent multi-institutional analysis, providing a foundation for future investigations correlating detailed dosimetric parameters with clinical outcomes in spatially fractionated radiotherapy.
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Wang et al. (2026) studied this question.
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