Work

Dynamic contrast-enhanced QSM for perfusion imaging: a systematic comparison of ΔR2*- and QSM-based contrast agent concentration time curves in blood and tissue

Year: 2020

Type: article

Abstract: Objective In dynamic susceptibility contrast MRI (DSC-MRI), an arterial input function (AIF) is required to quantify perfusion. However, estimation of the concentration of contrast agent (CA) from magnitude MRI signal data is challenging. A reasonable alternative would be to quantify CA concentration using quantitative susceptibility mapping (QSM), as the CA alters the magnetic susceptibility in proportion to its concentration. Material and methods AIFs with reasonable appearance, selected on the basis of conventional criteria related to timing, shape, and peak concentration, were registered from both Δ R 2* and QSM images and mutually compared by visual inspection. Both Δ R 2*- and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from Δ R 2*as well as QSM images. Results AIFs based on Δ R 2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding Δ R 2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s −1 mM −1 , for voxels identified as useful AIF candidate in Δ R 2* images according to the conventional criteria. Discussion Interestingly, arterial concentration time curves based on Δ R 2* versus QSM data, for a standard DSC-MRI experiment, were generally very similar in shape, and the relaxivity obtained in voxels representing blood was similar to tissue relaxivity obtained in previous studies.

Source: Magnetic Resonance Materials in Physics Biology and Medicine

DOI: 10.1007/s10334-020-00831-x

Authors: Emelie Lind, Linda Knutsson, Freddy Ståhlberg, Ronnie Wirestam

Institutions: Lund University, Johns Hopkins University, Johns Hopkins Medicine

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,860