A multi-scale sub-voxel perfusion model to estimate diffusive capillary wall conductivity in multiple sclerosis lesions from perfusion MRI data.

Koch, Timo; Flemisch, Bernd; Helmig, Rainer; Wiest, Roland; Obrist, Dominik (2020). A multi-scale sub-voxel perfusion model to estimate diffusive capillary wall conductivity in multiple sclerosis lesions from perfusion MRI data. International Journal for Numerical Methods in Biomedical Engineering, 36(2), e3298. Wiley 10.1002/cnm.3298

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We propose a new mathematical model to learn capillary leakage coefficients from dynamic susceptibility contrast MRI data. To this end, we derive an embedded mixed-dimension flow and transport model for brain tissue perfusion on a sub-voxel scale. This model is used to obtain the contrast agent concentration distribution in a single MRI voxel during a perfusion MRI sequence. We further present a magnetic resonance signal model for the considered sequence including a model for local susceptibility effects. This allows modeling MR signal-time curves that can be compared to clinical MRI data. The proposed model can be used as a forward model in the inverse modeling problem of inferring model parameters such as the diffusive capillary wall conductivity. Acute multiple sclerosis lesions are associated with a breach in the integrity of the blood brain barrier. Applying the model to perfusion MR data of a patient with acute multiple sclerosis lesions, we conclude that diffusive capillary wall conductivity is a good indicator for characterizing activity of lesions, even if other patient-specific model parameters are not well-known. This article is protected by copyright. All rights reserved.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Cardiovascular Engineering (CVE)

UniBE Contributor:

Wiest, Roland and Obrist, Dominik

Subjects:

600 Technology > 610 Medicine & health

ISSN:

2040-7947

Publisher:

Wiley

Language:

English

Submitter:

Martin Zbinden

Date Deposited:

21 Jan 2020 12:47

Last Modified:

12 Feb 2020 01:33

Publisher DOI:

10.1002/cnm.3298

PubMed ID:

31883316

Uncontrolled Keywords:

NMR signal brain tissue perfusion embedded mixed-dimension microcirculation modeling multiple sclerosis

BORIS DOI:

10.7892/boris.137837

URI:

https://boris.unibe.ch/id/eprint/137837

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