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ORIGINAL RESEARCH article
Front. Oncol.
Sec. Radiation Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1582402
This article is part of the Research TopicInnovative Approaches in Precision Radiation OncologyView all 7 articles
Optimization Method for Determining Vertices in Lattice Radiotherapy
Provisionally accepted- Center for National Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Purpose: This study presents an optimization method for arranging lattice radiotherapy (LRT) targets to enhance the contrast between peak and valley doses, aiming to improve the treatment effectiveness and precision.The LRT target comprises multiple sphere-like vertices generated using the optimization method，which involves four steps: 1) generating a volume for vertex arrangement, 2) determining initial positions and size of packing units, 3) determining initial positions and size of all the vertices and 4) optimizing the final vertex positions by using adaptive simulated annealing (ASA). Volumetric modulated arc therapy plans were retrospectively regenerated using the initial vertices produced by closest packing (Plan_Clo) and vertices obtained after ASA optimization (Plan_Opt). The peak-to-valley index (PVI) that characterizes the difference between peak and valley doses was introduced to evaluate the performance.Results: A statistically significant difference was observed in the average PVI between Plan_Clo and Plan_Opt (p = 0.000). The average PVI ratio for Plan_Opt compared to Plan_Clo was 5. 95 ± 4.87 (range: 1.24-16.80).The proposed optimization method for determining LRT target vertices has been validated, demonstrating a significant improvement in the PVI. ASA optimization, combined with closest packing, effectively enhanced the peak-to-valley dose difference in LRT, showcasing its potential for advancing treatment planning.
Keywords: optimization, Adaptive simulated annealing, Closest packing, Lattice, peak-to-valley index
Received: 24 Feb 2025; Accepted: 09 Apr 2025.
Copyright: © 2025 Ma, Xu, Yao, Lu and Dai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: N Lu, Center for National Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.