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Modélisation du cancer de la prostate par l'imagerie : détection, stratification, planning thérapeutique et suivi en 3D d'une thérapie focale basés sur le recalage-fusion d'image en multi modalité

Abstract : Conventional prostate MRI, enhanced by diffusion and perfusion sequences, and then named multiparametric, showed high performances for detection of prostate cancer using visual scoring. Indications in stratification, prognosis, treatment planning and follow up are currently under investigations.First part of this work attached itself to describe, elaborate and use a non-rigid image fusion method in 3D between gold standard histology of radical prostatectomy and MRI. Investigations captured the significant differences in shape and volume of in vivo and ex vivo prostate using MRI. The developed multimodality fusion method was applied to a cohort of patients who underwent MRI prior surgery. Results showed a stratified underestimation of cancer volume by MRI. Clinical output resides in detection, stratification and surgical planning.The second part proposed some texture analysis of sequences and quantitative maps. As a multiparametric approach, the Entropy Score is applied in a pilot cohort at time of biopsy and showed some potential usefulness to select MRI targets without compromising detection of significant cancer. By positively correlating with the Gleason Score and the maximal core length of cancer, Entropy Score participates of stratification of cancer.The third part explored application of image registration in the longitudinal follow up of an emergent therapy, said focal (FT). As a conservative approach, FT induces very local deformation of the gland which appears to be appropriately modelled by non-rigid registration, then opening possibilities to guide further control biopsy and radiologic assessment.
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  • HAL Id : tel-01806345, version 1

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Clément Orczyk. Modélisation du cancer de la prostate par l'imagerie : détection, stratification, planning thérapeutique et suivi en 3D d'une thérapie focale basés sur le recalage-fusion d'image en multi modalité. Médecine humaine et pathologie. Normandie Université, 2017. Français. ⟨NNT : 2017NORMC405⟩. ⟨tel-01806345⟩

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