Predictive use of quantitative imaging

Patent metadata

Field	Value
Publication number	US-10682098-B2
Application number	US-201815928921-A
Country	US
Kind code	B2
Filing date	Mar 22, 2018
Priority date	Mar 22, 2018
Publication date	Jun 16, 2020
Grant date	Jun 16, 2020

Abstract

The present disclosure provides systems and methods for predicting a disease state of a subject using ultrasound imaging and ancillary information to the ultrasound imaging. At least two quantitative measurements of a subject, including at least one measurement taken using ultrasound imaging, as part of quantified information can be identified. One of the quantitative measurements can be compared to a first predetermined standard, included as part of ancillary information to the quantified information, in order to identify a first initial value. Further, another of the quantitative measurements can be compared to a second predetermined standard, included as part of the ancillary information, in order to identify a second initial value. Subsequently, the quantitative information can be correlated with the ancillary information using the first initial value and the second initial value to determine a final value that is predictive of a disease state of the subject.

First claim

The invention claimed is:

1. A method comprising:
identifying at least two quantitative measurements of a subject, at least one of the at least two quantitative measurement taken using ultrasound imaging, the at least two quantitative measurements included as part of quantitative information of the subject gathered based on the ultrasound imaging;
comparing one of the at least two quantitative measurements to a first predetermined standard to determine a first initial value, the first predetermined standard included as part of ancillary information to the quantitative information of the subject and falling within a first range of quantities;
comparing another of the at least two quantitative measurements to a second predetermined standard to determine a second initial value, the second predetermined standard included as part of the ancillary information to the quantitative information of the subject and falling within a second range of quantities; and
correlating the quantitative information with the ancillary information using the first initial value and the second initial value to determine a final value that is used in predicting a disease state of the subject.

2. The method of claim 1 , wherein the at least one of the at least two quantitative measurements included as part of the quantitative information is an ultrasonic quantitative measurement formed from contrast-enhanced ultrasound, photo-acoustic imaging, acoustic radiation force impulse imaging, ultrasonic characterization of non-linear properties, ultrasonic attenuation, ultrasonic sound speed characterizations and/or ultrasonic speckle statistics.

3. The method of claim 1 , wherein the at least two quantitative measurements includes a measurement of at least one of a core biopsy, blood pressure, metabolic rate, pulse, BMI, body fat, angiography, blood analysis, saliva analysis, photo-acoustic imaging, protein screening and genetic screening.

4. The method of claim 1 , further comprising using other imaging modalities to determine the final value that is used in predicting the disease state of the subject.

5. The method of claim 4 , wherein the other imaging modalities include one of core biopsy, X-rays, fluoroscopy, computed tomography or MRI.

6. The method of claim 1 , further comprising using raw data to determine the final value that is used in predicting the disease state of the subject.

7. The method of claim 1 , further comprising using a machine-learning algorithm to predict the disease state of the subject.

8. The method of claim 7 , wherein the machine-learning algorithm is maintained using at least one of decision tree learning, association rule learning, artificial neural networks, inductive logic, a support vector, clustering, Baysian networks, reinforcement learning, representation learning, similarity and/or metric learning, sparse dictionary learning and/or protein and/or genetic algorithms.

9. The method of claim 1 , wherein the quantitative information is correlated with the ancillary information by combining the first initial value with the second initial value to identify the final value that is used in predicting the disease state of the subject.

10. The method of claim 1 , wherein the quantitative information is correlated with the ancillary information by comparing the quantitative information to the ancillary information to determine the final value.

11. A system comprising:
one or more processors; and
at least one computer-readable storage medium having stored therein instructions, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
identifying at least two quantitative measurements of a subject, at least one of the at least two quantitative measurement taken using ultrasound imaging, the at least two quantitative measurements included as part of quantitative information of the subject gathered based on the ultrasound imaging;
comparing one of the at least two quantitative measurements to a first predetermined standard to determine a first initial value, the first predetermined standard included as part of ancillary information to the quantitative information of the subject and falling within a first range of quantities;
comparing another of the at least two quantitative measurements to a second predetermined standard to determine a second initial value, the second predetermined standard included as part of the ancillary information to the quantitative information of the subject and falling within a second range of quantities; and
correlating the quantitative information with the ancillary information using the first initial value and the second initial value to determine a final value that is used in predicting a disease state of the subject.

12. The system of claim 11 , wherein the at least one of the at least two quantitative measurements included as part of the quantitative information is an ultrasonic quantitative measurement formed from contrast-enhanced ultrasound, photo-acoustic imaging, acoustic radiation force impulse imaging, ultrasonic characterization of non-linear properties, ultrasonic attenuation, ultrasonic sound speed characterizations and/or ultrasonic speckle statistics.

13. The system of claim 11 , wherein the at least two quantitative measurements includes a measurement of at least one of a core biopsy, blood pressure, metabolic rate, pulse, BMI, body fat, angiography, blood analysis, saliva analysis, photo-acoustic imaging, protein screening and genetic screening.

14. The system of claim 11 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to perform operations further comprising using other imaging modalities to determine the final value that is used in predicting the disease state of the subject.

15. The system of claim 14 , wherein the other imaging modalities include one of core biopsy, X-rays, fluoroscopy, computed tomography or MRI.

16. The system of claim 11 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to perform operations further comprising using raw data to determine the final value that is used in predicting the disease state of the subject.

17. The system of claim 11 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to perform operations further comprising using a machine-learning algorithm to predict the disease state of the subject.

18. The system of claim 17 , wherein the machine-learning algorithm is maintained using at least one of decision tree learning, association rule learning, artificial neural networks, inductive logic, a support vector, clustering, Baysian networks, reinforcement learning, representation learning, similarity and/or metric learning, sparse dictionary learning and/or protein and/or genetic algorithms.

19. The system of claim 11 , wherein the quantitative information is correlated with the ancillary information by combining the first initial value with the second initial value to identify the final value that is used in predicting the disease state of the subject.

20. The system of claim 11 , wherein the quantitative information is correlated with the ancillary information by comparing the quantitative information to the ancillary information to determine the final value.

Assignees

• Shenzhen Mindray Biomedical Electronics Co Ltd

Inventors

• Mclaughlin Glen W

Classifications

• A61B8/481 Primary

  involving the use of contrast agents, e.g. microbubbles introduced into the bloodstream · CPC title

• G06V10/774

  Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

• G06V10/84

  using probabilistic graphical models from image or video features, e.g. Markov models or Bayesian networks · CPC title

• A61B5/7267 Primary

  involving training the classification device · CPC title

• G06F18/28

  Determining representative reference patterns, e.g. by averaging or distorting; Generating dictionaries · CPC title