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

Patent metadata

Field	Value
Publication number	US-9974453-B2
Application number	US-201615200402-A
Country	US
Kind code	B2
Filing date	Jul 1, 2016
Priority date	Sep 12, 2012
Publication date	May 22, 2018
Grant date	May 22, 2018

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.

First claim

What is claimed is:

1. A method for hemodynamic determination in medical imaging, the method comprising:
acquiring medical scan data representing an anatomical structure of a patient to generate a patient-specific geometric model of the patient's anatomical structure;
extracting a set of features of the patient's anatomical structure from the patient-specific geometric model;
inputting, by a processor, the features of the patient's anatomical structure from the patient-specific geometric model to a machine-trained classifier, the machine-trained classifier trained from synthetic anatomical data and hemodynamic metrics of a plurality of individuals; and
generating and outputting, by the processor using the machine-trained classifier applied to the extracted features of the patient's anatomical structure, a hemodynamic metric corresponding to a flow of blood through the anatomical structure of the patient.

2. The method of claim 1 wherein acquiring comprises acquiring angiography data.

3. The method of claim 1 wherein acquiring comprises acquiring with the medical scan data a geometrical representation of the anatomical structure.

4. The method of claim 1 wherein extracting the set of the features comprises:
extracting geometrical features of the anatomical structure.

5. The method of claim 1 wherein extracting the set of the features comprises extracting features representing operation of the anatomical structure, wherein the machine-trained classifier is trained from virtual representations of the operation of the anatomical structure.

6. The method of claim 1 wherein extracting the set of the features comprises extracting an ischemic weight.

7. The method of claim 1 wherein extracting the set of the features comprises extracting characteristics of a coronary branch geometry.

8. The method of claim 1 wherein outputting comprises outputting a value of the hemodynamic metric on a display with an image of the anatomical structure generated from the medical scan data.

9. The method of claim 1 wherein outputting the hemodynamic metric comprises outputting fractional flow reserve.

10. A system for hemodynamic determination in medical imaging, the system comprising:
a data storage device storing instructions for hemodynamic determination in medical imaging; and
a processor configured to execute the instructions to perform a method including the steps of:
acquiring medical scan data representing an anatomical structure of a patient to generate a patient-specific geometric model of the patient's anatomical structure;
extracting a set of features of the patient's anatomical structure from the patient-specific geometric model;
inputting, by a processor, the features of the patient's anatomical structure from the patient-specific geometric model to a machine-trained classifier, the machine-trained classifier trained from synthetic anatomical data and hemodynamic metrics of a plurality of individuals; and
generating and outputting, by the processor using the machine-trained classifier applied to the extracted features of the patient's anatomical structure, a hemodynamic metric corresponding to a flow of blood through the anatomical structure of the patient.

11. A non-transitory computer-readable medium storing instructions that, when executed by a computer, cause the computer to perform a method including:
acquiring medical scan data representing an anatomical structure of a patient to generate a patient-specific geometric model of the patient's anatomical structure;
extracting a set of features of the patient's anatomical structure from the patient-specific geometric model;
inputting, by a processor, the features of the patient's anatomical structure from the patient-specific geometric model to a machine-trained classifier, the machine-trained classifier trained from synthetic anatomical data and hemodynamic metrics of a plurality of individuals; and
generating and outputting, by the processor using the machine-trained classifier applied to the extracted features of the patient's anatomical structure, a hemodynamic metric corresponding to a flow of blood through the anatomical structure of the patient.

Assignees

• Heartflow Inc
• Heartflow Inc

Inventors

• Fonte Timothy
• Choi Gilwoo
• Grady Leo
• Singer Michael

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• A61B5/107

  Measuring physical dimensions, e.g. size of the entire body or parts thereof · CPC title

• A61B6/504 Primary

  for diagnosis of blood vessels, e.g. by angiography · CPC title

• A61B6/507

  for determination of haemodynamic parameters, e.g. perfusion CT · CPC title

• A61B5/14546

  for measuring analytes not otherwise provided for, e.g. ions, cytochromes · CPC title