Related Experiment Video
Updated: Jul 7, 2026
In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Nonlinear myocardial signal intensity correction improves quantification of contrast-enhanced first-pass MR perfusion
Li-Yueh Hsu1, Peter Kellman, Andrew E Arai
1Laboratory of Cardiac Energetics, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892-1061, USA. lyhsu@nhlbi.nih.gov
Purpose:
To study the nonlinearity of myocardial signal intensity and gadolinium contrast concentration during first-pass perfusion MRI, and to compare quantitative perfusion estimates using nonlinear myocardial signal intensity correction.
Materials And Methods:
The nonlinearity of signal intensity and contrast concentration was simulated by magnetization modeling and evaluated in phantom measurements. A total of 10 healthy volunteers underwent rest and stress dual-bolus perfusion studies using an echo-planar imaging sequence at both short and long saturation-recovery delay times (TD70 and TD150). Perfusion estimates were compared before and after the correction.
Results:
The phantom data showed a linear relationship (R(2) = 1.00 and 0.99) of corrected signal intensity vs. contrast concentrations. Peak myocardial contrast concentration averaged 0.64 +/- 0.10 mmol x L(-1) at rest and 0.91 +/- 0.21 mmol x L(-1) during stress for TD70 and were similar for TD150 (P = not significant [NS]). The corrections were larger for stress than rest perfusion and larger for TD150 than TD70 studies (both P < 0.01). Perfusion estimates of TD70 and TD150 stress studies were significantly different before the correction (P < 0.01) but equivalent after the correction (P = NS).
Conclusion:
The nonlinearity between signal intensity and myocardial contrast concentration in perfusion MRI can be corrected through magnetization modeling. A nonlinear correction of myocardial signal intensity is feasible and improves quantitative perfusion analysis.
