Systems and methods for estimating ischemia and blood flow characteristics from vessel geometry and physiology

Abstract

Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual—specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

1 . A method for determining individual-specific blood flow characteristics, the method comprising:
 acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system;   executing a machine learning algorithm on the individual -specific anatomic data and blood flow characteristics for each of the plurality of individuals;   relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics;   acquiring, for an individual, individual-specific anatomic data of at least part of the individual's vascular system; and   for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.   
     
     
         2 . The method of  claim 1 , further comprising:
 acquiring, for each of the plurality of individuals, one or more individual characteristics; and   executing the machine learning algorithm further based on the one or more individual characteristics.   
     
     
         3 . The method of  claim 1 , wherein the blood flow characteristics of the individuals include ischemia, blood flow, or fractional flow reserve. 
     
     
         4 . The method of  claim 1 , further comprising:
 generating a set of features for each point of interest where a blood flow characteristic is desired;   using a regression or machine learning technique to weight the impact of features on the blood flow characteristic; and   using the regression or machine learning technique to estimate a blood flow characteristic numerically, classify a vessel as ischemia positive or negative, or classify an individual as ischemia positive or negative.   
     
     
         5 . The method of  claim 2 , wherein the individual characteristics include one or more of: heart rate, blood pressure, demographics such as age or sex, medication, disease states, including diabetes, hypertension, vessel dominance, and prior MI. 
     
     
         6 . The method of  claim 1 , further comprising: displaying or storing the produced estimates in one or more of a media, including images, renderings, tables of values, or reports, or transferring the produced estimates to a physician through other electronic or physical delivery methods. 
     
     
         7 . The method of  claim 1 , further comprising displaying along with each produced estimate a confidence level or a positive, negative, or inconclusive indication. 
     
     
         8 . The method of  claim 1 , further comprising producing estimates based on one or more of analytical fluid dynamics equations and morphometry scaling laws. 
     
     
         9 . The method of  claim 1 , wherein the individual-specific anatomic data includes one or more of: vessel size, vessel size at ostium, vessel size at distal branches, reference and minimum vessel size at plaque, distance from ostium to plaque, length of plaque and length of minimum vessel size, myocardial volume, branches proximal/distal to measurement location, branches proximal/distal to plaque, and measurement location. 
     
     
         10 . The method of  claim 2 , further comprising:
 compiling a library or database of anatomic and individual characteristics along with FFR, ischemia test results, previous simulation results, and imaging data.   
     
     
         11 . The method of  claim 10 , further comprising:
 refining the machine learning algorithm based on additional data added to the library or database.   
     
     
         12 . The method of  claim 10 , wherein the individual-specific anatomic data for the individual or the plurality of individuals is obtained from one or more of: medical image data, measurements, models, and segmentations. 
     
     
         13 . A system for determining individual-specific blood flow characteristics, the system comprising:
 a data storage device storing instructions for estimating individual-specific blood flow characteristics; and   a processor configured to execute the instructions to perform a method including the steps of:
 acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; 
 executing a machine learning algorithm on the individual -specific anatomic data and blood flow characteristics for each of the plurality of individuals; 
 relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; 
 acquiring, for an individual, individual-specific anatomic data of at least part of the individual's vascular system; and 
 for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics. 
   
     
     
         14 . The system of  claim 13 , wherein the system is further configured for:
 acquiring, for each of the plurality of individuals, one or more individual characteristics; and   executing the machine learning algorithm further based on the one or more individual characteristics.   
     
     
         15 . The system of  claim 13 , wherein the blood flow characteristics include ischemia, blood flow, or fractional flow reserve. 
     
     
         16 . The system of  claim 13 , wherein the processor is further configured for:
 generating a set of features for each point of interest where a blood flow characteristic is desired;   using a regression or machine learning technique to weight the impact of features on estimated blood flow characteristic; and   using the regression or machine learning technique to estimate a blood flow characteristic numerically, classify a vessel as ischemia positive or negative, or classify an individual as ischemia positive or negative.   
     
     
         17 . The system of  claim 14 , wherein the individual characteristics include one or more of: heart rate, blood pressure, demographics such as age or sex, medication, disease states, including diabetes, hypertension, vessel dominance, and prior MI. 
     
     
         18 . The system of  claim 13 , wherein the processor is further configured for:
 displaying or storing the produced estimates in one or more of a media, including images, renderings, tables of values, or reports, or transferring the produced estimates to a physician through other electronic or physical delivery methods.   
     
     
         19 . The system of  claim 13 , wherein the processor is further configured for:
 displaying along with each produced estimate a confidence level or a positive, negative, or inconclusive indication.   
     
     
         20 . The system of  claim 13 , further comprising producing estimates based on one or more of analytical fluid dynamics equations and morphometry scaling laws.