Renaud de Crevoisier
University of Rennes
CancerInternal medicineRadiologyUrologySurgeryMagnetic resonance imagingOncologyArtificial intelligenceImage registrationPattern recognitionProstateProstate cancerRectumPopulationNuclear medicineComputer visionComputer scienceRadiation therapyMedicineImage-guided radiation therapy
157Publications
28H-index
3,027Citations
Publications 133
Newest
#1Martin A. Ebert (SCGH: Sir Charles Gairdner Hospital)H-Index: 26
#2Sarah L. Gulliford (UCLH: University College London Hospitals NHS Foundation Trust)H-Index: 23
Last. Claudio Fiorino (UniSR: Vita-Salute San Raffaele University)H-Index: 55
view all 10 authors...
For decades, dose-volume information for segmented anatomy has provided the essential data for correlating radiotherapy dosimetry with treatment-induced complications. Dose-volume information has formed the basis for modelling those associations via normal tissue complication (NTCP) models and for driving treatment planning. Limitations to this approach have been identified. Many studies have emerged demonstrating that the incorporation of information describing the spatial nature of the dose di...
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OBJECTIVE Purposes of this work were i) to develop an in silico model of tumor response to radiotherapy, ii) to perform an exhaustive sensitivity analysis in order to iii) propose a simplified version and iv) to predict biochemical recurrence with both the comprehensive and the reduced model. METHODS A multiscale computational model of tumor response to radiotherapy was developed. It integrated the following radiobiological mechanisms: oxygenation, including hypoxic death; division of tumor cell...
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#2Pierre FontaineH-Index: 3
Last. Oscar AcostaH-Index: 21
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In prostate cancer radiotherapy, biochemical recurrence has been traditionally predicted using radiomics approaches with however limited performance. The purpose of this work was to use a mechanistic in silico model of tumor growth and response to irradiation to obtain better predictions. A cohort of 76 patients with localized prostate adenocarcinoma having undergone external beam radiotherapy was used. Analogous digital tissues were built from pre-treatment MRI. The prescribed irradiation proto...
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#2A. BarateauH-Index: 5
Last. Oscar AcostaH-Index: 21
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Several approaches have been proposed to generate pseudo computed tomography (pCT) from MR images for radiotherapy dose calculation. Quantification of errors in pCT has been reported using global scores disregarding spatial heterogeneity. The aim of this work was to propose a population voxel-based workflow allowing the local assessment of errors in the generation of pCTs from MRI. For the voxel-wise analysis to be anatomically meaningful, a robust customized inter-patient non-rigid registration...
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#1Eugenia Mylona (French Institute of Health and Medical Research)H-Index: 4
#2Martin A. Ebert (UWA: University of Western Australia)H-Index: 26
Last. Renaud de Crevoisier (French Institute of Health and Medical Research)H-Index: 28
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Abstract Purpose /Objectives: Recent voxel-based studies have shown that the dose to specific rectal and urethro-vesical subregions is predictive of toxicities, following prostate cancer IMRT. The objective of this study was to validate the discriminatory power of these subregions with respect to the whole organs, in a large independent population. Material/Methods The validation cohort consisted of 450 patients, from the XXX(BLIND) trial, treated with 3D-CRT at 66-74 Gy. Previous voxel-based an...
1 CitationsSource
#1Pierre FontaineH-Index: 3
#2Oscar Acosta (French Institute of Health and Medical Research)H-Index: 21
Last. Adrien Depeursinge (University of Applied Sciences Western Switzerland)H-Index: 26
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In standard radiomics studies the features extracted from clinical images are mostly quantified with simple statistics such as the average or variance per Region of Interest (ROI). Such approaches may smooth out any intra-region heterogeneity and thus hide some tumor aggressiveness that may hamper predictions. In this paper we study the importance of feature aggregation within the standard radiomics workflow, which allows to take into account intra-region variations. Feature aggregation methods ...
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#1Filippos Filias (University of Patras)
#2Eugenia Mylona (University of Rennes)H-Index: 4
Last. Oscar Acosta (University of Rennes)H-Index: 21
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Prediction of urinary toxicity after prostate cancer radiotherapy (RT) is remarkably challenging. Not only it is a multifaceted phenomenon, encompassing different symptoms (retention, dysuria, haematuria, etc.), but also a multifactorial problem, as it depends on both patient-specific clinical factors, individual biological parameters, and dosimetric patterns. Thus, there are a plethora of potential predictors compared to the paucity of available symptom-specific toxicity data. On top of that, i...
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#1A. Barateau (French Institute of Health and Medical Research)H-Index: 5
#2Renaud de Crevoisier (French Institute of Health and Medical Research)H-Index: 28
Last. Caroline LafondH-Index: 15
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PURPOSE Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) from CBCT to perform dose calculation. This study aims to evaluate the accuracy of a DLM and to compare this method with three existing methods of dose calculation from CBCT in H&N cancer ra...
2 CitationsSource
#1Caroline Lafond (French Institute of Health and Medical Research)H-Index: 15
#2A. Barateau (French Institute of Health and Medical Research)H-Index: 5
Last. Renaud de Crevoisier (French Institute of Health and Medical Research)H-Index: 28
view all 10 authors...
Background: A rectal sub-region (SRR) has been previously identified by voxel-wise analysis in the inferior-anterior part of the rectum as highly predictive of rectal bleeding (RB) in prostate cancer radiotherapy. Translating the SRR to patient-specific radiotherapy planning is challenging as new constraints have to be defined. A recent geometry-based model proposed to optimize the planning by determining the achievable mean doses (AMDs) to the organs at risk (OARs), taking into account the over...
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Jul 1, 2020 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Pierre FontaineH-Index: 3
Last. Oscar Acosta (French Institute of Health and Medical Research)H-Index: 21
view all 7 authors...
Hepatocellular carcinoma (HCC) is the sixth more frequent cancer worldwide. This type of cancer has a poor overall survival rate mainly due to underlying cirrhosis and risk of recurrence outside the treated lesion. Quantitative imaging within a radiomics workflow may help assessing the probability of survival and potentially may allow tailoring personalized treatments. In radiomics a large amount of features can be extracted, which may be correlated across a population and very often can be surr...
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