Sebastiaan Breedveld

Mathemati(cian/cs) in Radiotherapy

Mathemati(cian/cs) in Radiotherapy
Sebastiaan Breedveld,
Erasmus University Medical Center, The Netherlands

About Sebastiaan

Sebastiaan Breedveld studied applied mathematics in Delft, University of Technology. With a strong desire to work in a medical environment, he started his MSc project in 2004 in radiotherapy treatment plan optimisation at the Erasmus University Medical Center in Rotterdam. The goal stated was simple: “Find us something to make better treatment plans.” Making tighter dose distributions was a first step. But how does a desired dose distribution look like? Unhindered by any knowledge or understanding of radiotherapy, he asked around for planning goals, and wrote them down on a list. This eventually evolved in the “wish-list” concept, which enabled automated treatment planning and  Erasmus-iCycle was born.

Breedveld pursued his PhD project on this topic from 2006 on, where the first patient was treated in 2010 with the aid of his work on automated treatment planning. He received his doctorate with honours in 2013. From the perspective of operational research, automated treatment planning in radiotherapy is a unique application, and requires some extensions in that field. Hereto, Breedveld received  the Multiple Criteria and Decision Making (MCDM) Doctoral Dissertation Award in 2015. In 2016 he was appointed as Assistant Professor,  and obtained a NWO Veni grant on Large-scale improvement of radiation treatment of cancer patients aiming at easier automation of treatment planning, while also striving for improved clinical trade-offs, and faster generation of treatment plans. In 2021, he obtained an NWO Vidi grant to achieve Instantaneous Treatment Planning.

After the clinical introduction of Erasmus-iCycle in the Erasmus University Medical Center in 2010, around 850 patients/year are treated with the aid of automated treatment planning. Recently, Elekta implemented this automated treatment planning cocept in their recent version of the Monaco TPS. He gave a TEDxDelft talk in 2016 on the topic of maximally utilising the available treatment hardware by using advanced algorithms (i.e Erasmus-iCycle), and released an open dataset (TROTS dataset) to enable cross-institutional testing and validation of algorithms for (multi-criteria) optimisation in radiotherapy in 2017.


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