Physique de la radiothérapie (GRT)

FLASH radiotherapy

FLASH radiotherapy is a way of delivering the dose to the patient in a very short time (milliseconds) leading to ultra-high dose rates (UHDR) up to 100 Gy/s and above. It has been shown in multiple species and biological models that such kind of UHDR triggers FLASH effect in the sense that healthy tissues are protected compared to a conventional irradiation whereas the tumour does not react differently to radiation. This leads to a differential effect that has been shown to be up to 30% increase in protection for pig skin. Beside that main biological effect, FLASH therapy potentially reduces the problem of target motion, and drastically shortens the number of irradiation sessions.

In order to obtain adequate information in pre-clinical studies, the reference dose of UHDR has to be guaranteed and the dose distribution has to be determined and validated. UHDR leads to saturation in commonly used detectors and new dosimetric techniques have to be developed. In parallel, FLASH radiotherapy needs to be transferred to clinics so that a first step of clinical trials may be performed. The optimization of delivery parameters becomes then crucial to implement FLASH radiotherapy and maximize its effect for patients. In that context, CHUV develops collaboration with private companies that may provide devices able to trigger FLASH effect, and also with CERN. The CHUV-CERN collaboration aims at developing a concept of a new FLASH treatment device for deep-seated tumours.

The main objective of this part of research is to implement and validate devices for clinical transfer by optimizing the dose delivery configuration. This multidisciplinary research is and has been founded by SNF and Swiss Cancer league.

Decision making in radio-oncology with multi-criteria optimization

Radiation therapy is the treatment of malignant cancer tumors with external radiation beams. The beam configuration and settings superposed on the patient’s CT scan slices results to a patient-specific radiation therapy treatment plan. Given the multiple beam configurations, multiple initial conditions and parameter settings there is a wide range of clinically acceptable treatment plans which express different trade-offs between target coverage and organs at risk (OAR). The standard technique in inverse radiation therapy treatment planning involves the search of the optimal solution through an optimization process based on pre-defined objectives and constraints. These initial conditions are defined by the planner who, based on his experience and training, searches the optimal solution through a trial-and-error loop. This method may lead to suboptimal choices of final treatment plans because the total solution space of plans is not fully explored. Multi-criteria Optimization (MCO) is a new method in radiation therapy that offers the possibility of creating a set of optimal plans representing different trade-offs. In the context of MCO problems there is no unique optimal solution that can satisfy all the objectives at the same time but rather a set of mathematically equivalent compromised solutions, called Pareto optimal solutions. For these solutions no objective can be improved without deteriorating another. In order to ensure real time navigation, the Pareto surface that represents the set of Pareto optimal plans in N dimensions, is approximated by a limited number of pre-calculated Pareto optimal solutions. The majority of the solutions available to the decision maker during navigation are near-Pareto optimal solutions that result as a linear combination of the above mentioned pre-calculated Pareto optimal solutions. 

The general aim of the project is to explore the possibilities offered by a multi-criteria based inverse treatment planning system, to determine the differences with the classical optimization methods and evaluate the impact of the available decision making tools on the quality of the final plan. 

This work is founded by OncoSuisse  project N° KFS-4399-02-2018.


In radiotherapy, an essential requirement is to ensure that the delivered dose distribution to the patient corresponds to the one prepared and validated during the treatment planning phase. A specific challenge is that the tumor may move during the delivery and action may be taken to account for that movement. One of the solutions is to follow the tumor so that the beam remains at the correct position compared to the target. This is what has been developed by Accuray with  Synchrony on the Radixact System.

When the delivery is adapted online to track the tumor, there is a need to, at least, record what happened, and at best, control that the delivery is performed correctly.

The aim of this project is to refine and validate quantitative assessment of treatment deliveries on the Radixact System with the ultimate goal that such techniques would be used as part of the implementation of a robust online adaptive solution.

This work is founed by Accuray Inc. 

Dose calculation produced by imaging in radiation therapy

Outcome of radiotherapy is strongly dependent not only on the planning dosimetry but also on the tumor localization at the time of beam delivery. Standard method of localization is based on image guidance (IGRT) by wall or gantry mounted X-ray tubes leading to extra dose delivered to the patient inside and outside the treated volume. Dose distributions of these acquisitions inside patients are complex depending not only on beam energy, gantry arc and filter, but also on patient anatomy especially in heterogeneous regions such as H&N and thorax. Thus, they cannot be characterized by only one quantity such as CTDI and should be fully calculated.

Calculation of IGRT dose distributions is not yet implemented in commercial softwares used for treatment planning systems, but several studies have demonstrated the feasibility of it.

This project aims at calculating a set of IGRT dose distributions of various radiotherapy devices for brain, thoracic, H&N and pelvic treatments, at extracting from them the engaged effective dose as well as its variability. Proposition of new more specific indicators are also be considered.

This work is partly founded by Federal Office of Public Health.

 Dernière mise à jour le 16/09/2020 à 16:09