Detection of small cerebral lesions using multi-component MR Fingerprinting with local joint sparsity

Abstract (2020)

Authors

M.A. Nagtegaal ImPhys/Computational Imaging - AS , ImPhys/Medical Imaging - AS
I. Hermann ImPhys/Computational Imaging - AS
S.D. Weingärtner ImPhys/Medical Imaging - AS , ImPhys/Computational Imaging - AS
Jeroen de Bresser Leiden University Medical Center
F.M. Vos ImPhys/Medical Imaging - AS , ImPhys/Computational Imaging - AS
Research Group
ImPhys/Medical Imaging (AS) (TU Delft)
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Published Date

2020

Language

English

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Faculty

Applied Sciences

Department

ImPhys/Imaging Physics

Research Group

ImPhys/Medical Imaging

Abstract

We propose a novel multi-component analysis for MR fingerprinting that enables detection of small lesions, while taking partial volume effects into account. The algorithm uses a joint sparsity constraint limiting the number of components in local regions. It is evaluated in simulations and on MRF-EPI data from a patient with multiple sclerosis (MS). MS-lesions are separated from other tissues based on having increased T2* relaxation times. The improved sensitivity to multiple components makes it possible to detect components with long relaxation times within the lesion, possibly increasing our insight into these small pathologies.

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