Sensitivity of dose‐volume indices to computation settings in high‐dose‐rate prostate brachytherapy treatment plan evaluation

Meer, Marjolein C. van der; Bosman, Peter A. N.; Pieters, Bradley R.; Niatsetski, Yury; Wieringen, N. Van; Alderliesten, Tanja; Bel, Arjan

doi:10.1002/acm2.12563

Cited by 12 publications

(13 citation statements)

References 23 publications

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“…A potential solution is to further accelerate MO-RV-GOMEA with the use of GPU parallelization, which we recently successfully achieved [38]. To further speed up both the CPU and GPU versions of our approach, we will study alternative ways of sampling dose calculation points that, for the specific DV indices of interest, result in the same precision of the DV indices, but using fewer dose calculation points (e.g., by exploiting shapes and surfaces of organs) [39,40]. Furthermore, our approach has been tested so far with only one protocol for prostate HDR-BT at our clinic (Amsterdam UMC, University of Amsterdam).…”

Section: Discussionmentioning

confidence: 99%

Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy

Luong

Alderliesten

Pieters

et al. 2019

Applied Soft Computing

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h i g h l i g h t s• Challenges of the brachytherapy planning problem for prostate cancer treatment.• Accuracy and efficiency issues in multi-objective prostate brachytherapy planning. • A multi-resolution scheme to accelerate the optimization of brachytherapy planning. • A multi-core CPU parallelization of our approach in brachytherapy planning. • Comparing solutions created by our approach with clinically approved treatment plans. a b s t r a c tPurpose: Prostate high-dose-rate brachytherapy (HDR-BT) planning involves determining the movement that a high-strength radiation stepping source travels through the patient's body, such that the resulting radiation dose distribution sufficiently covers tumor volumes and safely spares nearby healthy organs from radiation risks. The Multi-Objective Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (MO-RV-GOMEA) has been shown to be able to effectively handle this inherent bi-objective nature of HDR-BT planning. However, in clinical practice there is a very restricted planning time budget (often less than 1 h) for HDR-BT planning, and a considerable amount of running time needs to be spent before MO-RV-GOMEA finds a good trade-off front of treatment plans (about 20-30 min on a single CPU core) with sufficiently accurate dose calculations, limiting the applicability of the approach in the clinic. To address this limitation, we propose an efficiency enhancement technique for MO-RV-GOMEA solving the bi-objective prostate HDR-BT planning problem. Methods: Dose-Volume (DV) indices are often used to assess the quality of HDR-BT plans. The accuracy of these indices depends on the number of dose calculation points at which radiation doses are computed. These are randomly uniformly sampled inside target volumes and organs at risk. In available HDR-BT planning optimization algorithms, the number of dose calculation points is fixed. The more points are used, the better the accuracy of the obtained results will be, but also the longer the algorithms need to be run. In this work, we introduce a so-called multi-resolution scheme that gradually increases the number of dose calculation points during the optimization run such that the running time can be substantially reduced without compromising on the accuracy of the obtained results. Results and conclusion: Experiments on a data set of 18 patient cases show that with the multiresolution scheme, MO-RV-GOMEA can achieve a sufficiently good trade-off front of treatment plans after five minutes of running time on a single CPU core (4-6 times faster than the old approach with a fixed number of dose calculation points). When the optimization with the multi-resolution scheme is run on a quad-core machine, five minutes are enough to obtain trade-off fronts that are nearly as good as those obtained by running optimization with the old approach in one hour (i.e., 12 times faster). This leaves ample time to perform the selection of the preferred treatment plan from the trade-off front for the specific patient at hand. Furthermore, compa...

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Section: Discussionmentioning

confidence: 99%

Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy

Luong

Alderliesten

Pieters

et al. 2019

Applied Soft Computing

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“…Due to the shield thickness required to shield 192 Ir, alternatives have been suggested for IMBT, such as an electronic source 117 or other radiation isotopes. 118 When for example 153 Gd is used, it however comes at the cost of longer treatment times; the dose delivery for prostate cancer takes on average 217 vs 15 min for conventional HDR BT, 116 and 154 vs 12 min. 115 A smaller increase in the total delivery time is seen when using the radiation source 169 Yb; 118 delivery times are here on average 19 and 9 min for IMBT and HDR BT, respectively.…”

Section: H Intensity-modulated Brachytherapymentioning

confidence: 99%

Optimization in treatment planning of high dose‐rate brachytherapy — Review and analysis of mathematical models

2021

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Treatment planning in high dose-rate brachytherapy has traditionally been conducted with manual forward planning, but inverse planning is today increasingly used in clinical practice. There is a large variety of proposed optimization models and algorithms to model and solve the treatment planning problem. Two major parts of inverse treatment planning for which mathematical optimization can be used are the decisions about catheter placement and dwell time distributions. Both these problems as well as integrated approaches are included in this review. The proposed models include linear penalty models, dose-volume models, mean-tail dose models, quadratic penalty models, radiobiological models, and multiobjective models. The aim of this survey is twofold: (i) to give a broad overview over mathematical optimization models used for treatment planning of brachytherapy and (ii) to provide mathematical analyses and comparisons between models. New technologies for brachytherapy treatments and methods for treatment planning are also discussed. Of particular interest for future research is a thorough comparison between optimization models and algorithms on the same dataset, and clinical validation of proposed optimization approaches with respect to patient outcome.

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“…Clinical treatment guidelines of HDR BT for prostate cancer [10] suggests that the number of dose points should be at least 5 000 for each structure. The correlation between the number of dose points and the uncertainty in evaluation criteria is studied in [13]. For each target and OAR they suggest 32 000 and 256 000 dose points, respectively.…”

Section: Dose Points and Dose Calculationmentioning

confidence: 99%

Treatment Planning of High Dose-Rate Brachytherapy - Mathematical Modelling and Optimization

Morén

2021

Linköping Studies in Science and Technology. Dissertations

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Cancer is a widespread class of diseases that each year affects millions of people. It is mostly treated with chemotherapy, surgery, radiation therapy, or combinations thereof. High doserate (HDR) brachytherapy (BT) is one modality of radiation therapy, which is used to treat for example prostate cancer and gynecologic cancer. In BT, catheters (i.e., hollow needles) or applicators are used to place a single, small, but highly radioactive source of ionizing radiation close to or within a tumour, at dwell positions. An emerging technique for HDR BT treatment is intensity modulated brachytherapy (IMBT), in which static or dynamic shields are used to further shape the dose distribution, by hindering the radiation in certain directions.The topic of this thesis is the application of mathematical optimization to model and solve the treatment planning problem. The treatment planning includes decisions on catheter placement, that is, how many catheters to use and where to place them, as well as decisions for dwell times. Our focus is on the latter decisions. The primary treatment goals are to give the tumour a sufficiently high radiation dose while limiting the dose to the surrounding healthy organs, to avoid severe side effects. Because these aims are typically in conflict, optimization models of the treatment planning problem are inherently multiobjective. Compared to manual treatment planning, there are several advantages of using mathematical optimization for treatment planning. First, the optimization of treatment plans requires less time, compared to the time-consuming manual planning. Secondly, treatment plan quality can be improved by using optimization models and algorithms. Finally, with the use of sophisticated optimization models and algorithms the requirements of experience and skill level for the planners are lower. The use of optimization for treatment planning of IMBT is especially important because the degrees of freedom are too many for manual planning.The contributions of this thesis include the study of properties of treatment planning models, suggestions for extensions and improvements of proposed models, and the development of new optimization models that take clinically relevant, but uncustomary aspects, into account in the treatment planning. A common theme is the modelling of constraints on dosimetric indices, each of which is a restriction on the portion of a volume that receives at least a specified dose, or on the lowest dose that is received by a portion of a volume. Modelling dosimetric indices explicitly yields mixed-integer programs which are computationally demanding to solve. We have therefore investigated approximations of dosimetric indices, for example using smooth non-linear functions or convex functions. Contributions of this thesis are also a literature review of proposed treatment planning models for HDR BT, including mathematical analyses and comparisons of models, and a study of treatment planning for IMBT, which shows how robust optimization can be used to mitigate the risks fro...

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Sensitivity of dose‐volume indices to computation settings in high‐dose‐rate prostate brachytherapy treatment plan evaluation

Cited by 12 publications

References 23 publications

Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy

Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy

Optimization in treatment planning of high dose‐rate brachytherapy — Review and analysis of mathematical models

Treatment Planning of High Dose-Rate Brachytherapy - Mathematical Modelling and Optimization

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