- Poster presentation
- Open Access
Interobserver reproducibility of fully quantitative pixel-wise analysis of clinical CMR perfusion imaging
© Conn et al.; licensee BioMed Central Ltd. 2014
- Published: 16 January 2014
- Cardiac Magnetic Resonance
- Myocardial Blood Flow
- Invasive Coronary Angiography
- Coronary Artery Disease Group
Quantitative first pass cardiac magnetic resonance (CMR) perfusion imaging has shown excellent interobserver agreement at a sector level in healthy volunteers and patients. In this study, we compare the myocardial blood flow (MBF) estimates in sector-wise and pixel-wise analysis. We also study the interobserver variability in pixel-wise MBF estimates from patients with coronary artery disease (CAD).
First pass CMR imaging was performed on 29 patients with known or suspected CAD (15 females, age 54.9 ± 14.3 years). Twenty of the patients, defined as the normal group, had minimal or no stenosis ( < 30% by computed tomographic angiogram) and nine patients, defined as the CAD group, had significant CAD ( > 70% stenosis by invasive coronary angiography). All patients were scanned on a 1.5T scanner using a steady state free precession imaging sequence for regadenoson stress perfusion followed by rest perfusion 20 minutes later. Two observers independently traced the myocardial regions of interest in the mid-ventricular slice and quantified the MBF in sector-wise and pixel-wise analyses by a model-constrained deconvolution approach. Pixel-wise MBF estimates were averaged to six transmural sectors to compare with sector-wise analysis. Pearson correlation, Bland-Altman analysis, and paired student t-test were used to compare the results.
Clinical first pass CMR perfusion can be quantified at the pixel level and the results agree well with sector-wise comparison. There is an excellent interobserver agreement in pixel-wise quantification of patients with CAD.
This research was supported by the Intramural Research Program of the National Heart, Lung, and Blood Institute, National Institutes of Health.
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