Demonstrates that subendocardial and subepicardial segmentation improves MRI detection of myocardial perfusion deficits in coronary artery disease, indicating the value of detailed segment analysis.
RATIONALE AND OBJECTIVES: The aim of the study was to determine optimal thresholds for semiquantitative perfusion parameters and to evaluate the influence of different segmentation models in detecting malperfused regions. MATERIAL AND METHODS: In 6 healthy subjects and 13 patients with coronary artery disease, contrast-enhanced first-pass perfusion imaging was performed using a SR-TrueFISP-sequence. Thresholds for semiquantitative parameters were established, and different segmentation models of the left ventricular myocardium were tested. The standard of reference for patient studies was single photon emission computed tomography. RESULTS: Optimal thresholds were determined in healthy subjects for the perfusion parameters upslope, AUC, and peak SI of mv-0.5*std, mv-1.5*std, and mv-1.0*std, respectively. Using the optimal threshold for each parameter/segmentation combination sensitivities and specificities of stress studies were between 66% and 93% and 77% and 92%, respectively. Subdivision of radial segments into subendo/subepicardial segments increased sensitivities for perfusion deficits. CONCLUSIONS: Subdivision of radial myocardial segments is essential in analysis of magnetic resonance first-pass perfusion series. Semiquantitative perfusion parameters possess different sensitivities for the detection of perfusion deficits.
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Fenchel et al. (2004) studied this question.
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