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Acquisition IRM optimisée en vue du dépistage du cancer du sein

Abstract : Diffusion-weighted imaging (DWI) is a promising tool to increase the specificity of MRI for breast cancer screening. However, the field of view covering the breasts makes the DWI at high resolution difficult and the images obtained have low signal-to-noise ratios (SNR). The current DWI techniques are limited by the spatial resolution, mainly a slice thickness greater than or equal to 3 mm. In this work, an isotropic DWI method was developed to obtain high resolution isotropic images (1x1x1 mm3) covering the entire breast. These images are obtained by combining: (i) a readout-segmented DW-EPI sequence (rs-EPI), with several segments of k-space and echo navigator providing high in-plane resolution, (ii) a super-resolution (SR) strategy, which consists of acquiring three datasets with thick slices (3 mm) and 1mm-shifts in the slice direction, (iii) and combining them into a 1x1x1 mm3 dataset using a dedicated reconstruction. Several SR reconstruction schemes were investigated, based on different regularizations. The proposed SR strategy was compared to native 1x1x1 mm3 acquisitions (i.e. with 1 mm slice thickness) on eight healthy subjects, and synthetics phantoms. To validate the SR method, we used several methods: Monte Carlo simulations, SNR measurements and sharpness metrics, the apparent diffusion coefficient (ADC) values in normal breast tissue and breast diffusion/resolution phantom were also compared. A new clinical research protocol is proposed to evaluate the effectiveness of the high resolution diffusion sequence on breast cancer screening. The aim of this protocol is to replace the contrast-enhanced perfusion by the diffusion sequence for screening.
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Submitted on : Thursday, May 16, 2019 - 9:51:40 AM
Last modification on : Tuesday, October 13, 2020 - 10:46:40 AM


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Maya Delbany. Acquisition IRM optimisée en vue du dépistage du cancer du sein. Traitement du signal et de l'image [eess.SP]. Université de Lorraine, 2019. Français. ⟨NNT : 2019LORR0018⟩. ⟨tel-02130741⟩



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