The versatility of evolutionary intelligent tri-objective treatment planning for cervical cancer brachytherapy

Background: A multi-objective automated treatment planning approach, called BRIGHT, has demonstrated success in prostate cancer brachytherapy (BT). BRIGHT optimizes directly on dose-volume metrics, aligning with clinical protocol goals, and produces multiple plans that represent different trade-offs between tumor coverage and healthy organ sparing. Current automated treatment planning methods either do not optimize directly on dose-volume metrics or generate a single plan, which is only considered optimal in the specific optimization model. Purpose: We extended BRIGHT to cervical cancer BT, for which adding a third objective to the existing bi-objective approach was deemed necessary. In this work, we present the algorithmic adaptations made to the approach and highlight its flexibility, which enables straightforward inclusion of customizations. We further demonstrate that this approach produces clinically acceptable plans. Methods: The first two objectives in the proposed approach pertain to the EMBRACE-II protocol, which is divided into tumor coverage and healthy organ sparing. The third objective encompasses added aims, which were deemed necessary to be included to ensure dose distribution shape characteristics not captured in the EMBRACE-II protocol but which can also readily be tuned to include local clinical preferences. We illustrate this by proposing four different customizations: a baseline customization and three different customizations that lead to (potentially distinct) pear-shaped dose distributions, often desired in cervical cancer BT. We include optimization with contiguous volumes, a capability distinctive to BRIGHT, as an option for dose distribution shape optimization. We tested all four customizations on 269 BT fractions (123 patients), and studied differences in runtimes, 3D dose distributions, as well as obtained dose-volume values. Clinical acceptability was evaluated for six representative patient cases, by presenting the resulting set of plans for all customizations to a BT team of two radiation oncologists, a medical physicist, and a radiation therapy technologist. They were asked to assess whether there is at least one acceptable plan per patient in the given set of plans. Results: Treatment plans can be generated in under 2.8 min with the baseline tri-objective BRIGHT, or 3.7 min if contiguous volumes are included, even though 260.000 dose calculation points are used for highly accurate dose estimation during optimization. There are visual differences in dose distributions for some of the six patient cases when using the distinct customizations, although generally pear-shaped distributions were obtained. The contiguity of the dose distributions resulting from optimizing with contiguous volumes can be advantageous in special cases where the high-dose region is preferred in the target area, as well as directly being tied to the location of the inserted applicator. Achieved dose-volume values are clinically comparable between all four customizations. The BT team indicated that 3/4 customizations included at least one clinically acceptable plan for all six patients. Conclusions: Clinically acceptable plans for cervical cancer BT can be quickly generated using the new tri-objective version of BRIGHT. This approach allows for straightforward customization to accommodate local clinical preferences. We demonstrated this versatility through various customizations that produced generally pear-shaped, yet potentially distinct, dose distributions, with comparable dose-volume values according to the EMBRACE-II protocol.

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