scholarly journals New criterion to aid manual and automatic selection of the arterial input function in dynamic susceptibility contrast MRI

2010 ◽  
Vol 65 (2) ◽  
pp. 448-456 ◽  
Author(s):  
Egbert J. W. Bleeker ◽  
Matthias J. P. van Osch ◽  
Alan Connelly ◽  
Mark A. van Buchem ◽  
Andrew G. Webb ◽  
...  
Keyword(s):  
Arterial Input Function ◽  
Input Function ◽  
Dynamic Susceptibility ◽  
Dynamic Susceptibility Contrast ◽  
Automatic Selection ◽  
Dynamic Susceptibility Contrast Mri ◽  
Susceptibility Contrast ◽  
New Criterion ◽  
Selection Of

scholarly journals Evaluation of signal formation in local arterial input function measurements of dynamic susceptibility contrast MRI

2011 ◽  
Vol 67 (5) ◽  
pp. 1324-1331 ◽  
Author(s):  
Egbert J. W. Bleeker ◽  
Andrew G. Webb ◽  
Marianne A. A. van Walderveen ◽  
Mark A. van Buchem ◽  
Matthias J. P. van Osch
Keyword(s):  
Arterial Input Function ◽  
Input Function ◽  
Dynamic Susceptibility ◽  
Dynamic Susceptibility Contrast ◽  
Dynamic Susceptibility Contrast Mri ◽  
Susceptibility Contrast

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

2020 ◽  
Vol 33 (5) ◽  
pp. 663-676
Author(s):  
Emelie Lind ◽  
Linda Knutsson ◽  
Freddy Ståhlberg ◽  
Ronnie Wirestam
Keyword(s):  
Contrast Agent ◽  
Arterial Input Function ◽  
Tissue Concentration ◽  
Input Function ◽  
Dynamic Susceptibility ◽  
Dynamic Susceptibility Contrast ◽  
Concentration Data ◽  
Concentration Time ◽  
Dynamic Susceptibility Contrast Mri ◽  
Dsc Mri

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 ΔR2* and QSM images and mutually compared by visual inspection. Both ΔR2*- and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from ΔR2*as well as QSM images. Results AIFs based on ΔR2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding ΔR2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s−1 mM−1, for voxels identified as useful AIF candidate in ΔR2* images according to the conventional criteria. Discussion Interestingly, arterial concentration time curves based on ΔR2* 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.

scholarly journals Automated Determination of Arterial Input Function for Dynamic Susceptibility Contrast MRI from Regions around Arteries Using Independent Component Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Sharon Chen ◽  
Yu-Chang Tyan ◽  
Jui-Jen Lai ◽  
Chin-Ching Chang
Keyword(s):  
Independent Component Analysis ◽  
Contrast Agent ◽  
Arterial Input Function ◽  
Input Function ◽  
Volume Effect ◽  
Partial Volume Effect ◽  
Independent Component ◽  
Dynamic Susceptibility ◽  
Dynamic Susceptibility Contrast ◽  
Susceptibility Contrast

Purpose.Quantitative cerebral blood flow (CBF) measurement using dynamic susceptibility contrast- (DSC-) MRI requires accurate estimation of the arterial input function (AIF). The present work utilized the independent component analysis (ICA) method to determine the AIF in the regions adjacent to the middle cerebral artery (MCA) by the alleviated confounding of partial volume effect.Materials and Methods.A series of spin-echo EPI MR scans were performed in 10 normal subjects. All subjects received 0.2 mmol/kg Gd-DTPA contrast agent. AIFs were calculated by two methods:(1)the region of interest (ROI) selected manually and(2)weighted average of each component selected by ICA (weighted-ICA). The singular value decomposition (SVD) method was then employed to deconvolve the AIF from the tissue concentration time curve to obtain quantitative CBF values.Results. The CBF values calculated by the weighted-ICA method were 41.1 ± 4.9 and 22.1 ± 2.3 mL/100 g/min for cortical gray matter (GM) and deep white matter (WM) regions, respectively. The CBF values obtained based on the manual ROIs were 53.6 ± 12.0 and 27.9 ± 5.9 mL/100 g/min for the same two regions, respectively.Conclusion.The weighted-ICA method allowed semiautomatic and straightforward extraction of the ROI adjacent to MCA. Through eliminating the partial volume effect to minimum, the CBF thus determined may reflect more accurate physical characteristics of theT2⁎signal changes induced by the contrast agent.

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