Non-invasive functional assessment technique for determining hemodynamic severity of an arterial stenosis

A noninvasive method for determining the hemodynamic severity of arterial stenosis (mild, severe, or moderate) and predicting possible lesion improvement from an interventional treatment for existing stenosis:

• a) virtually worsening the stenosis by varying lumen volumetric reduction (VR) levels from 0% to 95%, wherein stenosis shape remains substantially constant;
• b) computing a translesional pressure indicator (TPI) value for each lumen volumetric reduction level with a three-element Windkessel model (WK3 model);
• wherein the flow domain excepting the existing stenosis and inlet boundary conditions remain the same subject to adjustment of r, C, and R parameters in the WK3 model;
• c) establishing a functional relationship between TPI and lumen volumetric reduction along a curve of TPI=TPI(VR);
• d) identifying two thresholds of mild volume reduction (VRmild) and severe volume reduction (VRsevere) based on analysis of the TPI=TPI(VR) curve;
• e) determining the severity of the existing stenosis by comparing existing volume reduction (VRexisting) with VRmild and VRsevere;
• f) predicting an outcome of TPI after interventional treatment.

A method for noninvasively quantifying a translesional pressure indicator of existing arterial stenosis and predicting possible lesion improvement from an interventional treatment for existing stenosis, comprising:

• a) receiving a patient's CT/MRI imaging data, ultrasound velocity wave information, blood viscosity, and blood density;
• b) extracting velocity waveforms from ultrasound sensors positioned at an existing arterial stenosis blood flow inlet and outlet;
• c) quantifying a translesional pressure indicator of arterial stenosis between the blood flow inlet and outlet;
• d) extracting anatomical information from the CT/MRI imaging data;
• and
• e) computing the translesional pressure indicator for the existing arterial stenosis over a virtual lumen volumetric reduction range from 0% to 95%;
• f) building a functional relationship curve of TPI=TPI(VR);
• g) identifying two thresholds of VRmild and VRsevere based on analysis of the TPI=TPI(VR) curve;
• h) determining the severity of the existing stenosis by plotting VRexisting with VRmild and VRsevere;
• and
• i) predicting an outcome of TPI after interventional treatment.