TH-CD-207-01: BEST IN PHYSICS (IMAGING): Correction of the First-Pass Distortion in Arterial Input Function of DCE MRI for Perfusion Quantification

2015 ◽  
Vol 42 (6Part43) ◽  
pp. 3734-3734
Author(s):  
H Wang ◽  
T Verma ◽  
Y Cao
Keyword(s):  
Arterial Input Function ◽  
Input Function ◽  
Dce Mri ◽  
First Pass ◽  
Perfusion Quantification

scholarly journals Validating a Local Arterial Input Function Method for Improved Perfusion Quantification in Stroke

2011 ◽  
Vol 31 (11) ◽  
pp. 2189-2198 ◽  
Author(s):  
Lisa Willats ◽  
Soren Christensen ◽  
Henry K Ma ◽  
Geoffrey A Donnan ◽  
Alan Connelly ◽  
...  
Keyword(s):  
Time Course ◽  
Arterial Input Function ◽  
Input Function ◽  
Perfusion Magnetic Resonance Imaging ◽  
Data Sets ◽  
Bolus Tracking ◽  
Perfusion Quantification ◽  
Magnetic Resonance Imaging Mri ◽  
Arterial Input Functions ◽  
Contrast Bolus

In bolus-tracking perfusion magnetic resonance imaging (MRI), temporal dispersion of the contrast bolus due to stenosis or collateral supply presents a significant problem for accurate perfusion quantification in stroke. One means to reduce the associated perfusion errors is to deconvolve the bolus concentration time-course data with local Arterial Input Functions (AIFs) measured close to the capillary bed and downstream of the arterial abnormalities causing dispersion. Because the MRI voxel resolution precludes direct local AIF measurements, they must be extrapolated from the surrounding data. To date, there have been no published studies directly validating these local AIFs. We assess the effectiveness of local AIFs in reducing dispersion-induced perfusion error by measuring the residual dispersion remaining in the local AIF deconvolved perfusion maps. Two approaches to locating the local AIF voxels are assessed and compared with a global AIF deconvolution across 19 bolus-tracking data sets from patients with stroke. The local AIF methods reduced dispersion in the majority of data sets, suggesting more accurate perfusion quantification. Importantly, the validation inherently identifies potential areas for perfusion underestimation. This is valuable information for the identification of at-risk tissue and management of stroke patients.

The use of a reference tissue arterial input function with low-temporal-resolution DCE-MRI data

2010 ◽  
Vol 55 (16) ◽  
pp. 4871-4883 ◽  
Author(s):  
M Heisen ◽  
X Fan ◽  
J Buurman ◽  
N A W van Riel ◽  
G S Karczmar ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Arterial Input Function ◽  
Input Function ◽  
Reference Tissue ◽  
Dce Mri

SU-G-IeP1-03: Comparing Arterial Input Function Measurements in DCE-MRI Using MOLLI and Phase

2016 ◽  
Vol 43 (6Part25) ◽  
pp. 3644-3644
Author(s):  
N Majtenyi ◽  
H Gabrani-Juma ◽  
R Klein ◽  
RA deKemp ◽  
G Cron ◽  
...  
Keyword(s):  
Arterial Input Function ◽  
Input Function ◽  
Dce Mri

SU-D-BRB-06: Comprehensive Population-Averaged Arterial Input Function (AIF) for DCE-MRI of Head and Neck Cancer

2012 ◽  
Vol 39 (6Part3) ◽  
pp. 3615-3616 ◽  
Author(s):  
J Onxley ◽  
D Yoo ◽  
N Muradyan ◽  
J MacFall ◽  
D Brizel ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Arterial Input Function ◽  
Input Function ◽  
Dce Mri

Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model

2005 ◽  
Vol 23 (4) ◽  
pp. 519-529 ◽  
Author(s):  
Thomas E. Yankeelov ◽  
Jeffrey J. Luci ◽  
Martin Lepage ◽  
Rui Li ◽  
Laura Debusk ◽  
...  
Keyword(s):  
Arterial Input Function ◽  
Input Function ◽  
Pharmacokinetic Analysis ◽  
Reference Region ◽  
Dce Mri ◽  
Region Model
Sign in / Sign up

Export Citation Format

Share Document