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Abstract #1828

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

Martijn Nagtegaal1, Ingo Hermann1,2, Sebastian Weingärtner1, Jeroen de Bresser3, and Frans Vos1
1Department of Imaging Physics, Delft University of Technology, Delft, Netherlands, 2Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, 3Department of Radiology, Leiden University Medical Centre, Leiden, Netherlands

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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