Abstract
High dose-rate brachytherapy is a modality of radiation therapy used for cancer treatment, in which the radiation source is placed within the body. The treatment goal is to give a high enough dose to the tumour while sparing nearby healthy tissue and organs (organs-at-risk). The most common criteria for evaluating dose distributions are dosimetric indices. For the tumour, such an index is the portion of the volume that receives at least a specified dose level (e.g. the prescription dose), while for organs-at-risk it is instead the portion of the volume that receives at most a specified dose level. Dosimetric indices are aggregate criteria and do not consider spatial properties of the dose distribution. Further, there are neither any established evaluation criteria for characterizing spatial properties, nor have such properties been studied in the context of mathematical optimization of brachytherapy. Spatial properties are however of clinical relevance and therefore dose plans are sometimes adjusted manually to improve them. We propose an optimization model for reducing the prevalence of contiguous volumes with a too high dose (hot spots) or a too low dose (cold spots) in a tentative dose plan. This model is independent of the process of constructing the tentative plan. We conduct computational experiments with tentative plans obtained both from optimization models and from clinical practice. The objective function considers pairs of dose points and each pair is given a distance-based penalty if the dose is either too high or too low at both dose points. Constraints are included to retain dosimetric indices at acceptable levels. Our model is designed to automate the manual adjustment step in the planning process. In the automatic adjustment step large-scale optimization models are solved. We show reductions of the volumes of the largest hot and cold spots, and the computing times are feasible in clinical practice.
Highlights
Radiation therapy is commonly used to treat cancer
Despite the lack of spatial evaluation criteria in the clinical treatment guidelines, a few have been proposed for BT. We present such criteria proposed for external beam radiation therapy (EBRT), our focus is on BT
Each point on the dose-volume histogram (DVH)-curve corresponds to a dosimetric index (DI); for the PTV it is the portion of the volume that receives at least a specified radiation dose, while for an OAR it is here instead the portion of the volume that receives at most a specified dose
Summary
Radiation therapy is commonly used to treat cancer. A number of cancer types, such as prostate cancer, can be treated with high dose-rate brachytherapy (HDR BT), which is a modality of radiation therapy. The goal of radiation therapy is to deliver a high enough radiation dose (in Gray, Gy) to the tumour (planning target volume, PTV), while limiting the dose to nearby healthy tissue and organs (organs-at-risk, OAR) to avoid severe complications. In order to evaluate a dose plan, the treated three-dimensional structures (PTV and OAR) are discretized into dose points at which the received radiation doses are calculated. Dose distributions are commonly evaluated using aggregate criteria such as dosimetric indices; see for example Hoskin et al (2013) for clinical treatment guidelines for HDR BT of prostate cancer. For a thorough introduction to BT the reader is referred to Halperin et al (2013)
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