Implementation and evaluation of an iterative-based algorithm for automatic beam angle optimization in breast cancer treatment planning

Ying Guo; Yang Zhong; Lei Yu; Kang Zhang; Jiazhou Wang; Weigang Hu

doi:10.1016/j.meddos.2023.10.002

Implementation and evaluation of an iterative-based algorithm for automatic beam angle optimization in breast cancer treatment planning

Med Dosim. 2024;49(2):127-138. doi: 10.1016/j.meddos.2023.10.002. Epub 2023 Nov 3.

Authors

Ying Guo¹, Yang Zhong¹, Lei Yu¹, Kang Zhang², Jiazhou Wang¹, Weigang Hu³

Affiliations

¹ Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China; Shanghai Clinical Research Center for Radiation Oncology; Shanghai Key Laboratory of Radiation Oncology, Shanghai, 200032, China.
² United Imaging Healthcare, Shanghai, 20032, China.
³ Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China; Shanghai Clinical Research Center for Radiation Oncology; Shanghai Key Laboratory of Radiation Oncology, Shanghai, 200032, China. Electronic address: jackhuwg@gmail.com.

PMID: 37925299
DOI: 10.1016/j.meddos.2023.10.002

Abstract

Introduction: A beam angle optimization (BAO) algorithm was developed to evaluate its clinical feasibility and investigate the impact of varying BAO constraints on breast cancer treatment plans.

Materials and methods: A two-part study was designed. In part 1, we retrospectively selected 20 patients treated with radiotherapy after breast-conserving surgery. For each patient, BAO plans were designed using beam angles optimized by the BAO algorithm and the same optimization constraints as manual plans. Dosimetric indices were compared between BAO and manual plans. In part 2, fifteen patients with left breast cancer were included. For each patient, three distinct cardiac constraints (mean heart dose < 5 Gy, 3 Gy or 1 Gy) were established during the BAO process to obtain three optimized beam sets which were marked as BAO_H1, BAO_H3, BAO_H5, respectively. These sets of beams were then utilized under identical IMRT constraints for planning. Comparative analysis was conducted among the three groups of plans.

Results: For part 1, no significant differences were observed between BAO plans and manual plans in all dosimetric indices, except for ipsilateral lung V5, where BAO plans performed slightly better than manual plans (35.5% ± 5.6% vs 36.9% ± 4.3%, p = 0.034). For part 2, Stricter BAO heart constraints resulted in more perpendicular beams. However, there was no significant difference between BAO_H1, BAO_H3 and BAO_H5 with the same IMRT constraint in the heart dose. Meanwhile, the left lung dose was increased while the right breast and lung doses were decreased with stricter heart constraints in BAO. When mean heart dose < 5 Gy in IMRT constraint, the mean dose to the right lung was decreased from 0.46 Gy for BAO_H5 to 0.33 Gy for BAO_H1 (p = 0.027).

Conclusions: The BAO algorithm can achieve quality plans comparable to manual plans. IMRT constraints dominate the final plan dose, while varying BAO constraints alter the trade-off among structures, providing an additional degree of freedom in planning design.

Keywords: Automatic beam angle optimization; Automatic radiotherapy plan; Breast cancer.

MeSH terms

Algorithms*
Breast Neoplasms* / radiotherapy
Female
Humans
Organs at Risk
Radiotherapy Dosage*
Radiotherapy Planning, Computer-Assisted* / methods
Radiotherapy, Intensity-Modulated / methods
Retrospective Studies