Examining the Relationship between Semiquantitative Methods Analysing Concentration-Time and Enhancement-Time Curves from Dynamic-Contrast Enhanced Magnetic Resonance Imaging and Cerebrovascular Dysfunction in Small Vessel Disease

Author:

Bernal JoseORCID,Valdés-Hernández MaríaORCID,Escudero JavierORCID,Sakka Eleni,Armitage Paul A.,Makin Stephen,Touyz Rhian M.ORCID,Wardlaw Joanna M.ORCID

Abstract

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to examine the distribution of an intravenous contrast agent within the brain. Computational methods have been devised to analyse the contrast uptake/washout over time as reflections of cerebrovascular dysfunction. However, there have been few direct comparisons of their relative strengths and weaknesses. In this paper, we compare five semiquantitative methods comprising the slope and area under the enhancement-time curve, the slope and area under the concentration-time curve ( S l o p e C o n and A U C C o n ), and changes in the power spectrum over time. We studied them in cerebrospinal fluid, normal tissues, stroke lesions, and white matter hyperintensities (WMH) using DCE-MRI scans from a cohort of patients with small vessel disease (SVD) who presented mild stroke. The total SVD score was associated with A U C C o n in WMH ( p < 0.05 ), but not with the other four methods. In WMH, we found higher A U C C o n was associated with younger age ( p < 0.001 ) and fewer WMH ( p < 0.001 ), whereas S l o p e C o n increased with younger age ( p > 0.05 ) and WMH burden ( p > 0.05 ). Our results show the potential of different measures extracted from concentration-time curves extracted from the same DCE examination to demonstrate cerebrovascular dysfunction better than those extracted from enhancement-time curves.

Funder

Fondation Leducq

Wellcome Trust

Mrs Gladys Row Fogo Charitable Trust

British Heart Foundation

Horizon 2020

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging

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1. Protocol requirements for quantitation accuracy;Advances in Magnetic Resonance Technology and Applications;2023

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