Impact of the Choice of Native T1 in Pixelwise Myocardial Blood Flow Quantification. Issue 3 (8th October 2020)

• Record Type: Journal Article
• Authors: Kräuter, Corina; Reiter, Ursula; Reiter, Clemens; Nizhnikava, Volha; Schmidt, Albrecht; Stollberger, Rudolf; Fuchsjäger, Michael; Reiter, Gert
• Is Part Of: Journal of magnetic resonance imaging. Volume 53:Issue 3(2021)
• Page Start: 755
• Page End: 765
• Publication Date: 2020-10-08
• Subjects: myocardial blood flow -- cardiovascular magnetic resonance -- nonlinearity correction -- T1 mapping -- Fermi modeling -- dynamic contrast enhancement; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.27375
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Background: Quantification of myocardial blood flow (MBF) from dynamic contrast‐enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T1 values of blood and myocardium. Purpose: To assess the impact of T1 values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population‐averaged vs. subject‐specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T1 values. Study Type: Prospective. Subjects: Fifteen patients with chronic coronary heart disease. Field Strength/Sequence: 3T; modified Look–Locker inversion recovery for T1 mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid‐ventricular short‐axis slice in systole and diastole. Assessment: MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T1 values: study population‐averaged blood and myocardial, subject‐specific systolic and diastolic, and segmental T1 values. Myocardial segments with perfusion deficits were identified visually from DCE series. Statistical Tests: The relationships between MBF parameters derived by different methods were analyzed by Bland–Altman analysis; corresponding mean values were compared by t ‐test. Results: Using subject‐specific diastolic T1 values, global diastolic MBF was 0.61 ± 0.13 mL/(min·g). It did not differ from global MBF derived from the study population‐averaged T1 ( P = 0.88), but the standard deviation of differences was large (0.07 mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ ( P = 0.12), whereas global diastolic MBF using systolic (0.62 ± 0.13 mL/(min·g)) and diastolic T1 values differed ( P < 0.05). If regional instead of global T1 values were used, segmental MBF was lower in segments with perfusion deficits (bias = −0.03 mL/(min·g), −7% of mean MBF, P < 0.05) but higher in segments without perfusion deficits (bias = 0.01 mL/(min·g), 1% of mean MBF, P < 0.05). Data Conclusion: Whereas cardiac phase‐specific T1 values have a minor impact on MBF estimates, subject‐specific and myocardial segment‐specific T1 values substantially affect MBF quantification. Level of Evidence: 3 Technical Efficacy Stage: 3