TY - JOUR
T1 - Customizable landmark-based field aperture design for automated whole-brain radiotherapy treatment planning
AU - Xiao, Yao
AU - Cardenas, Carlos Eduardo
AU - Rhee, Dong Joo
AU - Netherton, Tucker
AU - Zhang, Lifei
AU - Nguyen, Callistus
AU - Douglas, Raphael
AU - Mumme, Raymond
AU - Skett, Stephen
AU - Patel, Tina
AU - Trauernicht, Chris
AU - Chung, Caroline
AU - Simonds, Hannah
AU - Aggarwal, Ajay
AU - Court, Laurence
N1 - Funding Information:
The authors highly appreciate Caroline Chung, Prajnan Das, Anuja Jhingran, Simeng Zhu, Melody Xu, Indranil Mallick, Mary Feng, and Hina Saeed for reviewing the field aperture design and the generated plans and providing prestigious feedback during the implementation of the field apertures. The authors thank Laura Russell from the department of scientific publications at The University of Texas MD Anderson Cancer Center for editing this work. The authors would also like to thank the Wellcome Trust for funding this work. We gratefully acknowledge the support of The University of Texas MD Anderson Cancer Center High-Performance Computing Center for computational resources to support the present research.
Funding Information:
The authors highly appreciate Caroline Chung, Prajnan Das, Anuja Jhingran, Simeng Zhu, Melody Xu, Indranil Mallick, Mary Feng, and Hina Saeed for reviewing the field aperture design and the generated plans and providing prestigious feedback during the implementation of the field apertures. The authors thank Laura Russell from the department of scientific publications at The University of Texas MD Anderson Cancer Center for editing this work. The authors would also like to thank the Wellcome Trust for funding this work. We gratefully acknowledge the support of The University of Texas MD Anderson Cancer Center High‐Performance Computing Center for computational resources to support the present research.
Publisher Copyright:
© 2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.
PY - 2023/3
Y1 - 2023/3
N2 - Purpose: To develop and evaluate an automated whole-brain radiotherapy (WBRT) treatment planning pipeline with a deep learning–based auto-contouring and customizable landmark-based field aperture design. Methods: The pipeline consisted of the following steps: (1) Auto-contour normal structures on computed tomography scans and digitally reconstructed radiographs using deep learning techniques, (2) locate the landmark structures using the beam's-eye-view, (3) generate field apertures based on eight different landmark rules addressing different clinical purposes and physician preferences. Two parallel approaches for generating field apertures were developed for quality control. The performance of the generated field shapes and dose distributions were compared with the original clinical plans. The clinical acceptability of the plans was assessed by five radiation oncologists from four hospitals. Results: The performance of the generated field apertures was evaluated by the Hausdorff distance (HD) and mean surface distance (MSD) from 182 patients’ field apertures used in the clinic. The average HD and MSD for the generated field apertures were 16 ± 7 and 7 ± 3 mm for the first approach, respectively, and 17 ± 7 and 7 ± 3 mm, respectively, for the second approach. The differences regarding HD and MSD between the first and the second approaches were 1 ± 2 and 1 ± 3 mm, respectively. A clinical review of the field aperture design, conducted using 30 patients, achieved a 100% acceptance rate for both the first and second approaches, and the plan review achieved a 100% acceptance rate for the first approach and a 93% acceptance rate for the second approach. The average acceptance rate for meeting lens dosimetric recommendations was 80% (left lens) and 77% (right lens) for the first approach, and 70% (both left and right lenses) for the second approach, compared with 50% (left lens) and 53% (right lens) for the clinical plans. Conclusion: This study provided an automated pipeline with two field aperture generation approaches to automatically generate WBRT treatment plans. Both quantitative and qualitative evaluations demonstrated that our novel pipeline was comparable with the original clinical plans.
AB - Purpose: To develop and evaluate an automated whole-brain radiotherapy (WBRT) treatment planning pipeline with a deep learning–based auto-contouring and customizable landmark-based field aperture design. Methods: The pipeline consisted of the following steps: (1) Auto-contour normal structures on computed tomography scans and digitally reconstructed radiographs using deep learning techniques, (2) locate the landmark structures using the beam's-eye-view, (3) generate field apertures based on eight different landmark rules addressing different clinical purposes and physician preferences. Two parallel approaches for generating field apertures were developed for quality control. The performance of the generated field shapes and dose distributions were compared with the original clinical plans. The clinical acceptability of the plans was assessed by five radiation oncologists from four hospitals. Results: The performance of the generated field apertures was evaluated by the Hausdorff distance (HD) and mean surface distance (MSD) from 182 patients’ field apertures used in the clinic. The average HD and MSD for the generated field apertures were 16 ± 7 and 7 ± 3 mm for the first approach, respectively, and 17 ± 7 and 7 ± 3 mm, respectively, for the second approach. The differences regarding HD and MSD between the first and the second approaches were 1 ± 2 and 1 ± 3 mm, respectively. A clinical review of the field aperture design, conducted using 30 patients, achieved a 100% acceptance rate for both the first and second approaches, and the plan review achieved a 100% acceptance rate for the first approach and a 93% acceptance rate for the second approach. The average acceptance rate for meeting lens dosimetric recommendations was 80% (left lens) and 77% (right lens) for the first approach, and 70% (both left and right lenses) for the second approach, compared with 50% (left lens) and 53% (right lens) for the clinical plans. Conclusion: This study provided an automated pipeline with two field aperture generation approaches to automatically generate WBRT treatment plans. Both quantitative and qualitative evaluations demonstrated that our novel pipeline was comparable with the original clinical plans.
KW - automation
KW - customizable field aperture
KW - deep learning
KW - whole-brain radiotherapy
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U2 - 10.1002/acm2.13839
DO - 10.1002/acm2.13839
M3 - Article
C2 - 36412092
AN - SCOPUS:85141952777
SN - 1526-9914
VL - 24
JO - Journal of applied clinical medical physics
JF - Journal of applied clinical medical physics
IS - 3
M1 - e13839
ER -