IP Library Granted Patent US 9,974,453
Granted Patent B2
US 9,974,453 · App. 15/200,402 · Granted May 22, 2018

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

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Quick Facts
Patent No.
US 9,974,453
App. No.
15/200,402
Granted
May 22, 2018
Kind
B2
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.

Claims (26)

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.

Assignments (5)
RELEASE OF SECURITY INTEREST Recorded Sep 11, 2025
From: HAYFIN SERVICES LLP
To: HEARTFLOW, INC.
Reel/Frame 072876/0775 →
RELEASE OF SECURITY INTEREST Recorded Jun 21, 2024
From: HAYFIN SERVICES LLP
To: HEARTFLOW, INC.
Reel/Frame 067801/0032 →
SECURITY INTEREST Recorded Jun 18, 2024
From: HEARTFLOW, INC.
To: HAYFIN SERVICES LLP
Reel/Frame 067775/0966 →
SECURITY INTEREST Recorded Jan 20, 2021
From: HEARTFLOW, INC.
To: HAYFIN SERVICES LLP
Reel/Frame 055037/0890 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 1, 2016
From: FONTE, TIMOTHY; CHOI, GILWOO; GRADY, LEO; SINGER, MICHAEL A.
To: HEARTFLOW, INC.
Reel/Frame 039066/0533 →