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. 2019 Sep;46(9):3767-3775.
doi: 10.1002/mp.13586. Epub 2019 Jul 9.

Automated treatment planning of postmastectomy radiotherapy

Affiliations

Automated treatment planning of postmastectomy radiotherapy

Kelly Kisling et al. Med Phys. 2019 Sep.

Abstract

Purpose: Breast cancer is the most common cancer in women globally and radiation therapy is a cornerstone of its treatment. However, there is an enormous shortage of radiotherapy staff, especially in low- and middle-income countries. This shortage could be ameliorated through increased automation in the radiation treatment planning process, which may reduce the workload on radiotherapy staff and improve efficiency in preparing radiotherapy treatments for patients. To this end, we sought to create an automated treatment planning tool for postmastectomy radiotherapy (PMRT).

Methods: Algorithms to automate every step of PMRT planning were developed and integrated into a commercial treatment planning system. The only required inputs for automated PMRT planning are a planning computed tomography scan, a plan directive, and selection of the inferior border of the tangential fields. With no other human input, the planning tool automatically creates a treatment plan and presents it for review. The major automated steps are (a) segmentation of relevant structures (targets, normal tissues, and other planning structures), (b) setup of the beams (tangential fields matched with a supraclavicular field), and (c) optimization of the dose distribution by using a mix of high- and low-energy photon beams and field-in-field modulation for the tangential fields. This automated PMRT planning tool was tested with ten computed tomography scans of patients with breast cancer who had received irradiation of the left chest wall. These plans were assessed quantitatively using their dose distributions and were reviewed by two physicians who rated them on a three-tiered scale: use as is, minor changes, or major changes. The accuracy of the automated segmentation of the heart and ipsilateral lung was also assessed. Finally, a plan quality verification tool was tested to alert the user to any possible deviations in the quality of the automatically created treatment plans.

Results: The automatically created PMRT plans met the acceptable dose objectives, including target coverage, maximum plan dose, and dose to organs at risk, for all but one patient for whom the heart objectives were exceeded. Physicians accepted 50% of the treatment plans as is and required only minor changes for the remaining 50%, which included the one patient whose plan had a high heart dose. Furthermore, the automatically segmented contours of the heart and ipsilateral lung agreed well with manually edited contours. Finally, the automated plan quality verification tool detected 92% of the changes requested by physicians in this review.

Conclusions: We developed a new tool for automatically planning PMRT for breast cancer, including irradiation of the chest wall and ipsilateral lymph nodes (supraclavicular and level III axillary). In this initial testing, we found that the plans created by this tool are clinically viable, and the tool can alert the user to possible deviations in plan quality. The next step is to subject this tool to prospective testing, in which automatically planned treatments will be compared with manually planned treatments.

Keywords: automated treatment planning; postmastectomy radiotherapy.

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Conflict of interest statement

This work was partially supported by Varian Medical Systems.

Figures

Figure 1
Figure 1
Overview of the method for automated planning of postmastectomy radiotherapy. OARs, organs at risk; BEV, beam's eye view; ROIs, regions of interest. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 2
Figure 2
Beam's eye view of supraclavicular fields for the original match line plan (left) and alternative match line plan (right) for the same patient. The contour of the level III axillary nodes are shown projected in orange. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 3
Figure 3
Comparison of the automatically generated and physician‐approved contours of the heart and ipsilateral lung. The top row shows the following results of the geometric comparisons: Dice similarity coefficient (DSC; left), mean surface distance (MSD; center), and Hausdorff distance (HD; right). The bottom row shows the following results of the dosimetric comparisons: mean OAR dose (left) and dose–volume histogram metric (right). The absolute difference in metrics was the results for the physician‐approved contour minus that for the automatically generated contour for the same plan. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 4
Figure 4
The final dose metrics for the ten automatically planned treatments. The dose–volume histogram (DVH) metrics (top left), mean dose delivered to the heart and ipsilateral lung (top right), coverage of targets by 95% or the prescription dose (bottom left), and maximum doses for the tangential and SCV plans and for a composite of the two plans (bottom right) are shown. OARs, organs at risk; SCV, supraclavicular; Ax3, level III axillary; Rx, prescription. [Color figure can be viewed at wileyonlinelibrary.com]

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