Systems and methods for processing electronic images to identify relevant flow characteristics

Abstract

Systems and methods are disclosed for identifying anatomically relevant blood flow characteristics in a patient. One method includes: receiving, in an electronic storage medium, a patient-specific representation of at least a portion of vasculature of the patient having a lesion at one or more points; receiving values for one or more metrics of interest associated with one or more locations in the vasculature of the patient; receiving one or more observed lumen measurements of the vasculature of the patient; determining the location of a diseased region in the vasculature of the patient using the received values for the one or more metrics of interest, wherein the determination of the location includes predicting or receiving one or more healthy lumen measurements of the vasculature of the patient; determining the extent of the diseased region; and generating a visualization of at least the diseased region.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method of processing electronic images to identify relevant flow characteristics in a patient, the method comprising:
 receiving a patient-specific representation of at least a portion of vasculature of the patient, the vasculature comprising at least one lesion;   determining or receiving values for one or more metrics of interest associated with one or more locations in the patient-specific representation;   determining a diseased region in the vasculature of the patient based on the values for the one or more metrics of interest;   determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region at least in part by automatically determining a proximity of the diseased region to a bifurcation, a proximity of the diseased region to a non-pinnable location, and/or a proximity of the diseased region to a second diseased region; and   generating a visualization of at least the diseased region, the visualization including markers illustrating the first position and second position.   
     
     
         22 . The computer implemented method of  claim 21 , further comprising:
 receiving one or more observed lumen measurements of the vasculature of the patient; and   determining the diseased region in the vasculature of the patient based on the one or more observed lumen measurements.   
     
     
         23 . The computer-implemented method of  claim 22 , wherein determining the diseased region further comprises:
 predicting or receiving one or more healthy lumen measurements of the vasculature of the patient;   generating a lumen narrowing score based on the observed lumen measurements and the predicted or received healthy lumen measurements of the vasculature of the patient; and   determining the location of the diseased region based on the generated lumen narrowing score.   
     
     
         24 . The computer-implemented method of  claim 23 , wherein predicting one or more healthy lumen measurements further comprises:
 forming a plurality of regressors based on one or more of the observed lumen measurements and/or the determined diseased region;   determining one or more parameter values for each of the plurality of regressors; and   performing a kernel regression of at least the diseased region to predict the one or more healthy lumen measurements.   
     
     
         25 . The computer-implemented method of  claim 21 , wherein the first position and the second position are set at a fixed distance from the diseased region when there is no bifurcation, non-pinnable location, or second diseased region within a set distance of the diseased region. 
     
     
         26 . The computer-implemented method of  claim 21 , further comprising:
 determining a lumen narrowing score; and   determining an acuity of the diseased region using the lumen narrowing score.   
     
     
         27 . The computer-implemented method of  claim 21 , wherein the markers illustrating the first position and second position comprise moveable pins. 
     
     
         28 . The computer-implemented method of  claim 27 , further comprising:
 providing interactive options to change in display features, range, magnification, or angle of the visualization of the diseased region.   
     
     
         29 . The computer-implemented method of  claim 21 , further comprising:
 enabling an assessment of treatment options for the diseased region.   
     
     
         30 . The computer-implemented method of  claim 21 , wherein the metrics of interest comprise one or more of:
 a function of fractional flow reserve (FFR), including FFR, distal point of FFR recovery, or a delta or change in FFR;   an instant wave free ratio (iFR);   a coronary flow reserve (CFR);   an anatomical characteristic including one or more of a vessel size or vessel thickness;   a plaque characteristic including one or more of a local calcium score, local low intensity plaque score, a measure of spotty calcification, a remodeling index, and/or an indicia of plaque signs;   a radiodensity; and/or   a blood flow characteristic including one or more of a blood flow rate or velocity, or a blood pressure.   
     
     
         31 . The computer-implemented method of  claim 22 , wherein lumen measurements of the vasculature of the patient comprise one or more of a radius, a diameter, an area, a circumference, a length, one or both elliptical radii, a torsion of the lumen, or a minima or maxima of the above. 
     
     
         32 . A system for processing electronic images to identify relevant flow characteristics, the system comprising:
 a data storage device storing instructions for processing electronic images to identify relevant flow characteristics in a patient; and   a processor configured to execute the instructions to perform operations comprising:
 receiving a patient-specific representation of at least a portion of vasculature of the patient, the vasculature comprising at least one lesion; 
 determining or receiving values for one or more metrics of interest associated with one or more locations in the patient-specific representation; 
 determining a diseased region in the vasculature of the patient based on the values for the one or more metrics of interest; 
 determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region at least in part by automatically determining a proximity of the diseased region to a bifurcation, a proximity of the diseased region to a non-pinnable location, and/or a proximity of the diseased region to a second diseased region; and 
 generating a visualization of at least the diseased region, the visualization including markers illustrating the first position and second position. 
   
     
     
         33 . The system of  claim 32 , the operations further comprising:
 receiving one or more observed lumen measurements of the vasculature of the patient;   predicting or receiving one or more healthy lumen measurements of the vasculature of the patient; and   comparing the observed lumen measurements with the predicted or received healthy lumen measurements of the vasculature of the patient.   
     
     
         34 . The system of  claim 33 , the operations further comprising:
 generating a lumen narrowing score based on the observed lumen measurements and the predicted or received healthy lumen measurements of the vasculature of the patient; and   determining the location of the diseased region based on the generated lumen narrowing score.   
     
     
         35 . The system of  claim 33 , wherein predicting one or more healthy lumen measurements further comprises:
 forming a plurality of regressors based on one or more of the observed lumen measurements and/or the determined locations of the diseased region;   determining parameter values for each of the plurality of regressors; and   performing a kernel regression of at least the diseased region to predict the one or more healthy lumen measurements.   
     
     
         36 . The system of  claim 32 , wherein the first position distal to the diseased region and the second position proximal to the diseased region is set at a fixed distance from the diseased region when there is no bifurcation, non-pinnable location, or second diseased region within a set distance of the diseased region. 
     
     
         37 . The system of  claim 32 , wherein the visualization of the diseased region comprises:
 displaying the values of one or more metrics of interest associated with one or more locations in the location of the diseased region, and at the first position and second position; and   enabling the visualization of the one or more metrics of interest in one or more of a table, graph, histogram, or movable visual pin.   
     
     
         38 . The system of  claim 37 , the operations further comprising:
 enabling a toggling of the display of one or more metrics of interest; and   enabling a change in a range, magnification, or angle of the vasculature to be displayed; and   modifying the display of the values of the one or more metrics of interest, as a result of the enabled change.   
     
     
         39 . A non-transitory computer-readable medium storing instructions that, when executed by a computer, causes the computer to perform operations for processing electronic images to identify relevant flow characteristics, the operations comprising:
 receiving a patient-specific representation of at least a portion of vasculature of the patient, the vasculature comprising at least one lesion;   determining or receiving values for one or more metrics of interest associated with one or more locations in the patient-specific representation;   determining a diseased region in the vasculature of the patient based on the values for the one or more metrics of interest;   determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region at least in part by automatically determining a proximity of the diseased region to a bifurcation, a proximity of the diseased region to a non-pinnable location, and/or a proximity of the diseased region to a second diseased region; and   generating a visualization of at least the diseased region, the visualization including markers illustrating the first position and second position.   
     
     
         40 . The non-transitory computer-readable medium of  claim 39 , the operations further comprising:
 receiving one or more observed lumen measurements of the vasculature of the patient;   predicting or receiving one or more healthy lumen measurements of the vasculature of the patient; and   comparing the observed lumen measurements with the predicted or received healthy lumen measurements of the vasculature of the patient.