CT-Based Collision Prediction Software for External-Beam Radiation Therapy

Yu-Jen Wang; Jia-Sheng Yao; Feipei Lai; Jason Chia-Hsien Cheng

doi:10.3389/fonc.2021.617007

CT-Based Collision Prediction Software for External-Beam Radiation Therapy

Front Oncol. 2021 Mar 11:11:617007. doi: 10.3389/fonc.2021.617007. eCollection 2021.

Authors

Yu-Jen Wang^{1

2

3}, Jia-Sheng Yao⁴, Feipei Lai^{1

4}, Jason Chia-Hsien Cheng^{1

5

6

7}

Affiliations

¹ Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
² Department of Radiation Oncology, Fu Jen Catholic University Hospital, New Taipei City, Taiwan.
³ School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei City, Taiwan.
⁴ Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
⁵ Division of Radiation Oncology, Departments of Oncology, National Taiwan University Hospital, Taipei, Taiwan.
⁶ Graduate Institutes of Oncology, Taipei, Taiwan.
⁷ Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.

Abstract

Purpose: Beam angle optimization is a critical issue for modern radiotherapy (RT) and is a challenging task, especially for large body sizes and noncoplanar designs. Noncoplanar RT techniques may have dosimetric advantages but increase the risk of mechanical collision. We propose a software solution to accurately predict colliding/noncolliding configurations for coplanar and noncoplanar beams.

Materials and methods: Individualized software models for two different linear accelerators were built to simulate noncolliding gantry orientations for phantom/patient subjects. The sizes and shapes of the accelerators were delineated based on their manuals and on-site measurements. The external surfaces of the subjects were automatically contoured based on computed tomography (CT) simulations. An Alderson Radiation Therapy phantom was used to predict the accuracy of spatial collision prediction by the software. A gantry collision problem encountered by one patient during initial setup was also used to test the validity of the software. Results: In the comparison between the software estimates and on-site measurements, the noncoplanar collision angles were all predicted within a 5-degree difference in gantry position. The confusion matrix was calculated for each of the two empty accelerator models, and the accuracies were 98.7% and 97.3%. The true positive rates were 97.7% and 96.9%, while the true negative rates were 99.8% and 97.9%, respectively. For the phantom study, the collision angles were predicted within a 5-degree difference. The software successfully predicted the collision problem encountered by the breast cancer patient in the initial setup position and generated shifted coordinates that were validated to correspond to a noncolliding geometry.

Conclusion: The developed software effectively and accurately predicted collisions for accelerator-only, phantom, and patient setups. This software may help prevent collisions and expand the range of spatially applicable beam angles.

Keywords: beam angle; collision; noncoplanar; radiotherapy; software.