Voxel-wise quantification of myocardial blood flow with cardiovascular magnetic resonance: effect of variations in methodology and validation with positron emission tomography.
BACKGROUND
Quantitative assessment of myocardial blood flow (MBF) from cardiovascular magnetic resonance (CMR) perfusion images appears to offer advantages over qualitative assessment. Currently however, clinical translation is lacking, at least in part due to considerable disparity in quantification methodology. The aim of this study was to evaluate the effect of common methodological differences in CMR voxel-wise measurement of MBF, using position emission tomography (PET) as external validation.


METHODS
Eighteen subjects, including 9 with significant coronary artery disease (CAD) and 9 healthy volunteers prospectively underwent perfusion CMR. Comparison was made between MBF quantified using: 1. Calculated contrast agent concentration curves (to correct for signal saturation) versus raw signal intensity curves; 2. Mid-ventricular versus basal-ventricular short-axis arterial input function (AIF) extraction; 3. Three different deconvolution approaches; Fermi function parameterization, truncated singular value decomposition (TSVD) and first-order Tikhonov regularization with b-splines. CAD patients also prospectively underwent rubidium-82 PET (median interval 7 days).


RESULTS
MBF was significantly higher when calculated using signal intensity compared to contrast agent concentration curves, and when the AIF was extracted from mid- compared to basal-ventricular images. MBF did not differ significantly between Fermi and Tikhonov, or between Fermi and TVSD deconvolution methods although there was a small difference between TSVD and Tikhonov (0.06 mL/min/g). Agreement between all deconvolution methods was high. MBF derived using each CMR deconvolution method showed a significant linear relationship (p<0.001) with PET-derived MBF however each method underestimated MBF compared to PET (by 0.19 to 0.35 mL/min/g).


CONCLUSIONS
Variations in more complex methodological factors such as deconvolution method have no greater effect on estimated MBF than simple factors such as AIF location and observer variability. Standardization of the quantification process will aid comparison between studies and may help CMR MBF quantification enter clinical use.
North West Heart Centre, University Hospital of South Manchester, Wythenshawe Hospital, Manchester, UK. chrismiller@doctors.org.uk.
Christopher A
CA
Miller
Josephine H
JH
Naish
Mark P
MP
Ainslie
Christine
C
Tonge
Deborah
D
Tout
Parthiban
P
Arumugam
Anita
A
Banerji
Robin M
RM
Egdell
David
D
Clark
Peter
P
Weale
Christopher D
CD
Steadman
Gerry P
GP
McCann
Simon G
SG
Ray
Geoffrey J M
GJ
Parker
Matthias
M
Schmitt
D000328:Adult; D000368:Aged; D001783:Blood Flow Velocity; D016022:Case-Control Studies; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology; D003326:Coronary Circulation; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D015588:Observer Variation; D049268:Positron-Emission Tomography; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012039:Regional Blood Flow; D015203:Reproducibility of Results