Methods and systems for assessing image quality in modeling of patient anatomic or blood flow characteristics

• US 9,672,615 B2
• Filed: 11/26/2014
• Issued: 06/06/2017
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Heartflow Inc.
• Original Assignee: Heartflow Inc.
• Inventors: Fonte, Timothy A., Wu, Zhongle, Schaap, Michiel, Hunley, Stanley C., Sengupta, Souma, Grady, Leo J.
• Primary Examiner(s): Harandi, Siamak
• Application Number:
  US14/554,653
• Publication Number:
  US 20150086093A1
• Time in Patent Office: 923 Days
• CPC Class Codes: A61B 2576/02 specially adapted for a particular organ or body part
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/0263 using NMR
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/037 Emission tomography
• CPC Class Codes: A61B 6/481 involving the use of contrast agents
• CPC Class Codes: A61B 6/504 for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 6/507 for determination of haemodynamic parameters, e.g. perfusion CT
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: A61B 6/5258 involving detection or reduction of artifacts or noise
• CPC Class Codes: A61B 6/5294 involving using additional data, e.g. patient information, image labeling, acquisition parameters
• CPC Class Codes: A61B 8/0883 for diagnosis of the heart
• CPC Class Codes: A61B 8/5223 for extracting a diagnostic or physiological parameter from medical diagnostic data for algorithms to analyse biomedical images G06T7/0012
• CPC Class Codes: G01R 33/5635 Angiography, e.g. contrast-enhanced angiography [CE-MRA] or time-of-flight angiography [TOF-MRA]
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/10104 Positron emission tomography [PET]
• CPC Class Codes: G06T 2207/10108 Single photon emission computed tomography [SPECT]
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/30004 : Biomedical image processing
• CPC Class Codes: G06T 2207/30104 : Vascular flow; Blood flow; Perfusion
• CPC Class Codes: G06T 2207/30168 : Image quality inspection
• CPC Class Codes: G06T 2207/30172 : Centreline of tubular or elongated structure
• CPC Class Codes: G06T 2207/30196 : Human being; Person
• CPC Class Codes: G06T 2210/41 : Medical
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders

Abstract

Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient'"'"'s anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient'"'"'s anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient'"'"'s anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient'"'"'s anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.

Claims

1. A method for automatically selecting image(s) to produce model(s) for a patient-specific simulation of blood flow, using at least one computer system, the method comprising:

receiving one or more images of at least a portion of a patient'"'"'s anatomy;

obtaining one or more image properties of the received images using one or more processors of the at least one computer system;

obtaining, for a selected one of the received images, an identification of one or more image characteristics of the selected one of the received images, where the one or more image characteristics are associated with an anatomic feature of the patient'"'"'s anatomy;

identifying a type of patient-specific simulation to perform using the received images;

receiving, for the type of patient-specific medical simulation using the received images, a selected level of simulation accuracy, precision, or performance;

quantifying a minimum image quality to render the received selected level of simulation accuracy, precision, or performance;

generating an image assessment based on the quantified minimum image quality, and the one or more image properties or image characteristics; and

applying the image assessment to each of the received images to select one or more images to produce one or more models for a patient-specific simulation of blood flow.

2. The method of claim 1, further comprising:

combining or correcting one or more of the selected images to generate a model for a patient-specific simulation of blood flow.

3. The method of claim 1, further comprising:

guiding simulation techniques based on the selected level of accuracy, precision, or performance.

4. The method of claim 1, further comprising:

performing, using a processor of the computer system, a patient-specific simulation of blood flow using one or more of the selected images.

5. The method of claim 4, further comprising:

performing anatomic localization of the at least a portion of the patient'"'"'s anatomy based on the received images, wherein the simulation is based on the anatomic localization of the at least a portion of the patient'"'"'s anatomy.

6. The method of claim 1, further comprising:

estimating performance metrics based on time to complete a simulation or cost of a simulation, wherein the image assessment is based on the estimated performance metrics.

7. The method of claim 1, further comprising:

calculating an image quality score based on the one or more image properties or the one or more image characteristics, wherein the image assessment is based on the image quality score.

8. The method of claim 1, wherein the one or more image characteristics include one or more of:

a local contrast level, a local noise level, a misregistration, a misalignment, a local motion anomaly, a local blurring anomaly, a partial volume effect, a blooming effect, and an artifact.

9. The method of claim 1, wherein the one or more image properties include one or more of:

an image resolution, a medical anatomy slice thickness, a number of scanner slices, a medication parameter, and a patient characteristic.

10. The method of claim 1, further comprising:

generating and transmitting a rendering of a recommendation to perform or not perform patient-specific medical simulation based on the image assessment.

11. A system for automatically selecting image(s) to produce model(s) for a patient-specific simulation of blood flow, the system comprising:

a digital storage device storing instructions for assessing the quality of medical images of at least a portion of a patient'"'"'s anatomy; and

a processor configured to execute the instructions to perform a method including;

receiving one or more images of at least a portion of a patient'"'"'s anatomy;

obtaining one or more image properties of the received images using one or more processors of the at least one computer system;

obtaining, for a selected one of the received images, an identification of one or more image characteristics of the selected one of the received images, where the one or more image characteristics are associated with an anatomic feature of the patient'"'"'s anatomy;

identifying a type of patient-specific simulation to perform using the received images;

receiving, for the type of patient-specific simulation using the received images, a selected level of accuracy, precision, or performance;

quantifying a minimum image quality to render the received selected level of accuracy, precision, or performance;

generating an image assessment based on the quantified minimum image quality, and the one or more image properties or image characteristics; and

applying the image assessment to each of the received images to select one or more images to produce one or more models for a patient-specific simulation of blood flow.

12. The system of claim 11, wherein the processor is further configured for:

combining or correcting one or more of the selected images to generate a model for a patient-specific simulation of blood flow.

13. The system of claim 12, wherein the processor is further configured for:

guiding simulation techniques based on the selected level of accuracy, precision, or performance.

14. The system of claim 11, wherein the processor is further configured for:

performing, using a processor of the computer system, a patient-specific simulation of blood flow using one or more of the selected images.

15. The system of claim 14, wherein the processor is further configured for:

performing anatomic localization of the at least a portion of the patient'"'"'s anatomy based on the received images, wherein the simulation is based on the anatomic localization of the at least a portion of the patient'"'"'s anatomy.

16. The system of claim 11, wherein the processor is further configured for:

estimating performance metrics based on time to complete a simulation or cost of a simulation, wherein the image assessment is based on the estimated performance metrics.

17. The system of claim 11, wherein the processor is further configured for:

calculating an image quality score based on the one or more image properties or the one or more image characteristics, wherein the image assessment is based on the image quality score.

18. The system of claim 11, wherein the one or more image characteristics include one or more of:

a local contrast level, a local noise level, a misregistration, a misalignment, a local motion anomaly, a local blurring anomaly, a partial volume effect, a blooming effect, and an artifact.

19. The system of claim 11, wherein the one or more image properties include one or more of:

an image resolution, a medical anatomy slice thickness, a number of scanner slices, a medication parameter, and a patient characteristic.

20. A non-transitory computer readable medium for use on at least one computer system containing computer-executable programming instructions for automatically selecting image(s) to produce model(s) for a patient-specific simulation of blood flow, that when executed by the at least one computer system, cause the performance of a method comprising:

receiving one or more images of at least a portion of a patient'"'"'s anatomy;

obtaining one or more image properties of the received images using one or more processors of the at least one computer system;

obtaining, for a selected one of the received images, an identification of one or more image characteristics of the selected one of the received images, where the one or more image characteristics are associated with an anatomic feature of the patient'"'"'s anatomy;

identifying a type of patient-specific medical modeling or simulation to perform using the received images;

receiving, for the type of patient-specific medical modeling or simulation using the received images, a selected level of accuracy, precision, or performance;

quantifying a minimum image quality to render the received selected level of accuracy, precision, or performance;

generating an image assessment based on the quantified minimum image quality, and the one or more image properties or the image characteristics; and

applying the image assessment to each of the received images to select one or more images to produce one or more models for a patient-specific simulation of blood flow.