Model-based analysis of CT myocardial perfusion imaging (CT-MPI) constrains the form of the impulse response according to physiologic assumptions and includes parameters such as flow that can be physiologically interpreted. However, if too many parameters exist in the model, it can lead to unreliable parameter estimates. A strangeness of perfusion models is that flow does not explicitly depend on the time delay of bolus arrival, yet a stenosis creates a measurable time delay along an affected vessel. To address this, we propose a new metric, flow-rate-to-fill-theintravascular- volume (FRIV), which is the intravascular blood volume divided by (time-delay + intravascular-transittime). This index is affected both by the appearance time as well as a reduced amount of contrast agent flowing in the affected vessel tree. We evaluate FRIV for a model from the literature, adiabatic approximation of tissue homogeneity (AATH) and compare to myocardial blood flow (MBF). For evaluation, we use a physiologic simulator, digital CT-MPI phantom at different x-ray dose level, and in vivo CT-MPI data from a porcine model with and without partial occlusion of the LAD coronary artery with known pressure-wire fractional flow reserve. FRIV shows much better precision than MBF. For example, at simulated MBF=100-mL/min-100g and nominal dose (200mAs) in the digital simulator, MBF and FRIV give coefficients of variation (CV) of 0.33 and 0.09, respectively, using the AATH model. At 50% nominal dose (100mAs) results are 0.45 and 0.16, respectively. In a porcine model of coronary artery stenosis, FRIV shows higher CNR than MBF and properly detects ischemia.
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