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Delft University of Technology

1. Bennan, Amit (author). Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer.

Degree: 2017, Delft University of Technology

Introduction: High Dose Rate (HDR) Brachytherapy is a radiotherapy modality that involves temporarily introducing a highly radioactive source into the target volume with the use of an applicator. With respect to HDR brachytherapy for prostate cancer, an 192Iridium source is driven into the target volume through catheters implanted into the prostate. The dose delivered to a point in the prostate depends on the time the source dwells at a given position. Treatment planning for brachytherapy involve the optimization of dwell times and dwell positions. The aim of the treatment plan is to deliver the prescribed dose to the target volume, the prostate, while minimizing the dose to the organs at risk (OAR), namely the urethra, bladder and rectum. In current clinical practice, the process of treatment planning involves the manual manipulation of the parameters of an optimizer until the desired dose distribution is achieved. This implies that the plan quality depends on the experience of the planner, and there is variation in plan quality between planners. The aim of this project was to develop an automated treatment planning system that would able to generate clinically acceptable plans with minimal human intervention. The brachytherapy treatment planning module is named B-iCycle and may be integrated in the future with the treatment planning software suite, called Erasmus-iCycle, developed at the Erasmus MC. Materials and methods: At the core of the treatment planning system (TPS) is a precise and fast dose engine that is able to simulate the dose to be delivered. In this project, we employ the TG-43 dose calculation formalism as it is the most widely implemented method in dose engines for brachytherapy treatment planning systems. The dose engine is then verified against the dose engine of the clinical treatment planning system. B-iCycle uses the 2-phase ϵ-constraint (2pϵc) algorithm to optimize the dwell times and positions. The 2pϵc algorithm requires a ‘wish-list’, which encapsulates the treatment protocol as goals and constraints for each critical structure. For this project three treatment protocols were chosen, four fractions of 9.5 Gy, single fraction of 19 Gy and single fraction of 20 Gy, and wish-lists were generated for each protocol. Three patient groups with different catheter geometries were selected. Treatment plans were generated for each patient and compared against the plans that were generated, for the same patients, in the clinic. The treatment plans that were generated in B-iCycle were then exported to the clinical treatment planning system (Oncentra from Elekta) to obtain the dose characteristics. The plans were compared based on the dose characteristics and the Conformity Index (COIN). The plans were also verified by a radiation oncologist. Results: The TG-43 dose engine was successfully verified against the clinical dose engine. The Gamma analysis showed that only 0.68% of the voxels failed the gamma analysis and these voxels were located within the catheters therefore they can be ignored as… Advisors/Committee Members: Schaart, Dennis (mentor), Breedveld, S. (mentor), Kolkman-Deurloo, I.K.K. (mentor), Heijman, B.J.M. (mentor), Lathouwers, Danny (mentor), Goorden, Marlies (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: brachytherapy; Treatment Planning; prostate cancer; HDR

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bennan, A. (. (2017). Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer. (Masters Thesis). Delft University of Technology. Retrieved from

Chicago Manual of Style (16th Edition):

Bennan, Amit (author). “Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer.” 2017. Masters Thesis, Delft University of Technology. Accessed April 20, 2021.

MLA Handbook (7th Edition):

Bennan, Amit (author). “Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer.” 2017. Web. 20 Apr 2021.


Bennan A(. Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 20]. Available from:

Council of Science Editors:

Bennan A(. Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer. [Masters Thesis]. Delft University of Technology; 2017. Available from: