Abstract
First pass gadolinium-enhanced cardiovascular magnetic resonance (CMR) perfusion imaging allows fully quantitative pixel-wise myocardial blood flow (MBF) assessment, with proven diagnostic value for coronary artery disease. Segmental analysis requires manual segmentation of the myocardium. This work presents a fully automatic method of segmenting the left ventricular myocardium from MBF pixel maps, validated on a retrospective dataset of 247 clinical CMR perfusion studies, each including rest and stress images of three slice locations, performed on a 1.5T scanner. Pixel-wise MBF maps were segmented using an automated pipeline including region growing, edge detection, principal component analysis, and active contours to segment the myocardium, detect key landmarks, and divide the myocardium into sectors appropriate for analysis. Automated segmentation results were compared against a manually defined reference standard using three quantitative metrics: Dice coefficient, Cohen Kappa and myocardial border distance. Sector-wise average MBF and myocardial perfusion reserve (MPR) were compared using Pearson’s correlation coefficient and Bland-Altman Plots. The proposed method segmented stress and rest MBF maps of 243 studies automatically. Automated and manual myocardial segmentation had an average (± standard deviation) Dice coefficient of 0.86 ± 0.06, Cohen Kappa of 0.86 ± 0.06, and Euclidian distances of 1.47 ± 0.73 mm and 1.02 ± 0.51 mm for the epicardial and endocardial border, respectively. Automated and manual sector-wise MBF and MPR values correlated with Pearson’s coefficient of 0.97 and 0.92, respectively, while Bland-Altman analysis showed bias of 0.01 and 0.07 ml/g/min. The validated method has been integrated with our fully automated MBF pixel mapping pipeline to aid quantitative assessment of myocardial perfusion CMR.
Highlights
First pass gadolinium-enhanced cardiovascular magnetic resonance (CMR) perfusion imaging allows for fullyThe associate editor coordinating the review of this manuscript and approving it for publication was Derek Abbott .quantitative assessment of myocardial blood flow (MBF) and has proven to have a diagnostic value for coronary artery disease as well as myocardial ischemia [1]–[6]
The stress sector plots of manual and automated origin both show values consistent with regional perfusion defects, which is supported by the visual impression on all three stress slices
We have presented a fully automated method for segmental analysis of fully quantitative CMR perfusion MBF pixel maps
Summary
First pass gadolinium-enhanced cardiovascular magnetic resonance (CMR) perfusion imaging allows for fullyThe associate editor coordinating the review of this manuscript and approving it for publication was Derek Abbott .quantitative assessment of myocardial blood flow (MBF) and has proven to have a diagnostic value for coronary artery disease as well as myocardial ischemia [1]–[6]. M. Jacobs et al.: Automated Segmental Analysis of Fully Quantitative MBF Maps by First-Pass Perfusion CMR provide similar blood flow values to positron emission tomography [8], are capable of diagnosing coronary artery disease [5], [9], [10], and have high repeatability [11]. Jacobs et al.: Automated Segmental Analysis of Fully Quantitative MBF Maps by First-Pass Perfusion CMR provide similar blood flow values to positron emission tomography [8], are capable of diagnosing coronary artery disease [5], [9], [10], and have high repeatability [11] These analyses were performed based on manually segmented MBF maps according to the American Heart Association (AHA) segment model [12]. Is this process tedious and timeconsuming, but it is prone to errors
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