Fully automated 16- and 32-segmentation quantitative perfusion CMR in detection of obstructive coronary artery disease

Le résumé fourni par la source

Recently, a fully automated QP CMR workflow has been established, which provides measures of stress MBF according to a 32-segmentation model with subdivision into endo- and epicardial subsegments. We compared the diagnostic accuracy of QP CMR according to the standard AHA 16-segment model (16M-QP) and the newly developed automated 32-segment model (32M-QP) with conventional visual assessment in patients who underwent adenosine stress perfusion CMR imaging followed by invasive coronary angiography and/or coronary computed tomography angiography. Our preliminary data have not shown superiority of diagnostic accuracy of 16M-QP or 32M-QP in comparison to visual assessment of adenosine stress first-pass perfusion imaging.

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