Project

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Decision making in radio-oncology with multi-criteria optimization treatment planning

English title Decision making in radio-oncology with multi-criteria optimization treatment planning
Applicant Moeckli Raphaël
Number 149489
Funding scheme Project funding (Div. I-III)
Research institution Institut de Radiophysique Département de Radiologie Université de Lausanne/CHUV
Institution of higher education University of Lausanne - LA
Main discipline Clinical Cancer Research
Start/End 01.11.2013 - 31.01.2016
Approved amount 113'873.00
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All Disciplines (2)

Discipline
Clinical Cancer Research
Biophysics

Keywords (5)

Radiothérapie; Planification; Décision; Optimisation; Multi-critères

Lay Summary (French)

Lead
La radiothérapie est l'une des disciplines médicales qui prend en charge le traitement des pathologies cancéreuses. Avant l'irradiation de la pathologie, un plan de traitement spécifique au patient est généré pour déterminer la meilleure configuration d'irradiation pour le patient. L'optimisation multi-critères est une nouvelle méthode d'optimisation des plans de traitement qui permet d'explorer interactivement une série de plans optimaux pour un cas donné.
Lay summary

L'optimisation multi-crières permet de naviger dans une large gamme de combinaisons possibles en tenant compte d'objectifs conflictuels. Cette nouvelle méthode d'optimisation va changer la façon dont les radio-oncologues et les physiciens médicaux vont prendre la décision du choix du meilleur plan de traitement. Actuellement, ils ont à décider si un plan est adéquat pour le traitement. Si ça n'est pas le cas, la procédure d'optimisation est pousuivie jusqu'à atteindre un accord (il s'agit d'un processus OUI-NON). Avec l'optimisation multi-critères, plusieurs plans mathématiquement équivalent seront à disposition.  Ainsi, la décision ne se prendra plus par rapport à un seul plan, mais il faudra faire un choix entre plusieurs plans. Il est dès lors important de déterminer quels seront les paramètres psycho-physiques qui vont conduire le choix des radio-oncologues et des physiciens médicaux. 

L'objectif général de ce projet est d'explorer les possibilités offertes par cette nouvelle technique de planification. Plusieurs cas cliniques vont être réalisés à l'aide de l'optimisation multi-critères. Les plans de traitements obtenus seront tous mathématiquement équivalents et les radio-oncologues et les physiciens médicaux choisiront le plan de traitement optimal selon un certain nombre de critères. Les résultats seront analysés en transposant des outil psycho-physiques déjà utilisés en radiologie dans le domaine de la détection de pathologies.

Nous allons déterminer si la méthode d'optimisation multi-critères apporte une amélioration pour le choix du traitement des patients en radiothérapie. Nous déterminerons quels paramètres cliniques sont utilisés et comment ces choix influencent le processus de décision. Ces résultats sont importants pour la pratique de la radiothérapie car le choix du plan de traitement optimal pour le patient est une étape très importante du processus de traitement.

Direct link to Lay Summary Last update: 05.11.2013

Responsible applicant and co-applicants

Employees

Name Institute

Publications

Publication
A clinical distance measure for evaluating treatment plan quality difference with Pareto fronts in radiotherapy
Petersson Kristoffer Kyroudi Archonteia Bourhis Jean Ceberg Crister Knöös Tommy Bochud Françoi (2017), A clinical distance measure for evaluating treatment plan quality difference with Pareto fronts in radiotherapy, in Physics and Imaging in Radiation Oncology, 3, 53-56.
Discrepancies between selected Pareto optimal plans and final deliverable plans in radiotherapy multi-criteria optimization
Kyroudi Archonteia (2016), Discrepancies between selected Pareto optimal plans and final deliverable plans in radiotherapy multi-criteria optimization, in Radiotherapy & Oncology, 120(2), 346-348.
Analysis of the treatment plan evaluation process in radiotherapy through eye tracking
Kyroudi A. Petersson K. Ozsahin M. Bourhis J. Bochud F. Moeckli R., Analysis of the treatment plan evaluation process in radiotherapy through eye tracking, in Zeitschrift für Medizinische Physik.

Collaboration

Group / person Country
Types of collaboration
Lund University Sweden (Europe)
- in-depth/constructive exchanges on approaches, methods or results

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Congrès annuel de la SSRPM Talk given at a conference A clinical distance measure for evaluating radiotherapy treatment plan quality difference with Pareto fronts 21.10.2015 Fribourg, Switzerland Moeckli Raphaël; Kyroudi Archonteia;
World Congress on Medical Physics and Biomedical Engineering (IUPESM) Poster Dosimetric evaluation of deliverable and navigated Pareto optimal plans generated with Multi-Criteria Optimization 07.06.2015 Toronto, Canada Moeckli Raphaël;
ESTRO annual meeting Poster Where do radiation oncologists and medical physicists look when they evaluate a patient treatment plan? 24.04.2014 Barcelona, Spain Bourhis Jean; Moeckli Raphaël;
SASRO annual meeting Talk given at a conference Searching for the Optimal Plan in Radiation Therapy 27.03.2014 Lugano, Switzerland Kyroudi Archonteia; Moeckli Raphaël;


Abstract

BackgroundMulticriteria Optimization is a new method in radiation therapy treatment plan optimization that offers the possibility of interactively exploring a set of optimal plans (Pareto front) for a given case. The approach of Multicriteria Optimization (MCO) allows navigation through a wide range of combinations among conflicting objectives. The decision maker can have a good understanding of the trade-offs involved that contribute to the final outcome. However this new optimization method will change the way decision is taken by the radiation oncologist and the medical physicist (the decision makers). In present practice, where the decision makers generally have to decide if a single plan is adequate for patient treatment or not. With MCO, they will face many plans, all being optimal from a mathematical point of view. Therefore, it is of importance to determine if MCO optimization does add value to patient treatment, and if yes what are the clinical and physical criteria that lead to a decision for a given plan.Aim and ObjectivesThe 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. Materials and MethodsDuring Phase 1, ten clinical prostate cases and ten Head&Neck cases will be planned by different planners with the MCO modality of Raystation TPS and with the classical optimization method. The Pareto fronts will be produced and compared by determining the relative Euclidean distance and the alternative distance measure proposed by Craft [2010]. During Phase 2, for each clinical case, five radiation oncologists and five medical physicists will have to choose the plan they consider as optimal among five proposed plans. These plans will belong to Pareto surface (and they will therefore be mathematically equally optimal). The method chosen for the evaluation will be 2AFC. The results will be analyzed with a transposition of the tools used for detection in radiology (adapted ROC curves).Expected results and importanceExpected results are twofold. First, we will determine if MCO optimization and Pareto concepts give additional information to the decision makers. Second, we will determine which clinical parameter is chosen by the decision makers and how these choices depend on these parameters.These results are of importance for future clinical practice in radiation therapy. The choice of a treatment plan for a patient is an important step in the radiation therapy workflow. Our work will show the importance of the use of a new technology for treatment planning optimization in clinical practice and it will help defining a new way for decision makers in the choice of an optimal treatment plan for the patients.CollaborationsThis work will take place in the Institute of Radiation Physics (IRA) from Lausanne University Hospital of (CHUV) which is in strong collaboration with the Radio-oncology department of the CHUV.A collaboration with Prof. Tommy Knöös from Lund University for the first part of the work concerning MCO optimization will be set-up. His expertise in the field will allow us to optimize the planning with MCO strategy.Collaboration with the Raysearch company, providing the treatment planning system with MCO optimization, is already set-up and will be continued. It will allow us to work on up to date TPS and tools useful with the second part of the study concerning decision making.
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