Identifying types of adipose tissue

Patent metadata

Field	Value
Publication number	US-10813600-B2
Application number	US-201716316446-A
Country	US
Kind code	B2
Filing date	Jul 13, 2017
Priority date	Jul 15, 2016
Publication date	Oct 27, 2020
Grant date	Oct 27, 2020

Abstract

A method of an image processing apparatus for identifying a type of adipose body tissue within a subject, based on performing a spectral computed tomography (CT) scan of a region of interest of the subject; and using a combination of different image processing techniques to differentiate between at least two adipose tissue types within the region of interest.

First claim

The invention claimed is:

1. An image processing apparatus adapted to identify a type of adipose body tissue within a subject, the apparatus comprising:
at least one data input interface; and
at least one processors circuitry;
wherein the data input interface is configured to receive spectral computed tomography (CT) imaging data of a region of interest of the subject; and
wherein the at least one processor circuitry is configured to:
perform at least one data processing technique on the spectral CT imaging data that differentiates between at least two adipose tissue types within the region of interest based on spectrally different attenuation properties of the at least two adipose tissue types; and
identify at least one adipose tissue type from the at least two tissue types.

2. The image processing apparatus of claim 1 , wherein the at least one data processing technique includes a data processing technique that differentiates between at least two adipose tissue types based upon differing vascularization of one of the adipose tissue types.

3. The image processing apparatus of claim 1 , wherein the spectral CT imaging data is contrast enhanced spectral CT imaging data.

4. The image processing apparatus of claim 1 , wherein the at least one data processing technique includes a data processing technique that differentiates between at least two adipose tissue types based upon selective imaging of a contrast agent by differing K shell binding energies.

5. The image processing apparatus of claim 1 , wherein the at least one data processing technique includes a data processing technique that differentiates between at least two adipose tissue types based upon the lipid content of tissue in the region of interest.

6. The image processing apparatus of claim 1 , wherein the at least one data processing technique includes a data processing technique that differentiates based upon the carbon/oxygen ratio of the adipose tissue.

7. The image processing apparatus of claim 1 , wherein the at least one processor circuitry is configured to perform a data processing technique that differentiates the at least two types of adipose tissue based on intensity of attenuation.

8. The image processing apparatus of claim 1 , wherein the at least one processor circuitry is configured to perform a combination of different data processing techniques on the spectral CT imaging data that respectively represent the spectral CT imaging data in different variable spaces, wherein results of the different data processing techniques in the different variable spaces differentiate the at least two adipose tissue types.

9. The image processing apparatus of claim 1 , wherein the at least one processor circuitry is configured determine a quantitative measure of the at least one identified adipose tissue type.

10. The image processing apparatus of claim 1 , wherein the at least one processor circuitry is configured to perform data processing techniques on the spectral CT imaging data to determine at least two of the following different data maps:
a quantity of lipid content;
a quantity of contrast agent; and
a quantity of attenuation.

11. The image processing apparatus of claim 1 , wherein the at least one processor circuitry is configured to:
perform cluster analysis on data maps to place data points in a plural dimensional space of the map quantities; and
identify different clusters of data points based on the cluster analysis corresponding to different types of adipose tissue.

12. A system for identifying a type of adipose body tissue within a subject, comprising:
an image processing apparatus adapted to identify a type of adipose body tissue within a subject, the apparatus comprising:
at least one data input interface; and
at least one processor circuitry;
wherein the data input interface is configured to receive spectral computed tomography (CT) imaging data of a region of interest of the subject; and
wherein the at least one processor circuitry is configured to:
perform at least one data processing technique on the spectral CT imaging data that differentiates between at least two adipose tissue types within the region of interest based on spectrally different attenuation properties of the at least two adipose tissue types; and
identify at least one adipose tissue type from the at least two tissue types; and

a spectral CT scanner to obtain the spectral CT imaging data.

13. The system of claim 12 , wherein the at least one processor circuitry is configured to perform data processing techniques on the spectral CT imaging data to determine at least two of the following different data maps:
a quantity of lipid content;
a quantity of contrast agent; and
a quantity of attenuation.

14. The system of claim 12 , wherein the at least one processor circuitry is configured to:
perform cluster analysis on data maps to place data points in a plural dimensional space of the map quantities; and
identify different clusters of data points based on the cluster analysis corresponding to different types of adipose tissue.

15. A method of identifying a type of adipose body tissue within a subject, the method comprising:
receiving spectral computed tomography (CT) imaging data of a region of interest of the subject;
performing at least one data processing technique on the spectral CT imaging data that differentiates between at least two adipose tissue types within the region of interest based on spectrally different attenuation properties of the at least two adipose tissue types; and
identifying at least one adipose tissue type from the at least two tissue types.

16. A non-transitory computer readable medium having stored a program element for controlling an apparatus, which, when being executed by processor circuitry, the apparatus is configured to perform the method according to claim 15 .

17. The method of claim 15 , further comprising:
performing data processing techniques on the spectral CT imaging data to determine at least two of the following different data maps:
a quantity of lipid content;
a quantity of contrast agent; and
a quantity of attenuation.

18. The method of claim 15 , further comprising:
performing cluster analysis on data maps to place data points in a plural dimensional space of the map quantities; and
identifying different clusters of data points based on the cluster analysis corresponding to different types of adipose tissue.

Assignees

• Koninklijke Philips Nv

Inventors

• Proksa Roland
• Daerr Heiner
• Franz Daniela

Classifications

• A61B6/481

  involving the use of contrast agents · CPC title

• A61B6/4241

  using energy resolving detectors, e.g. photon counting · CPC title

• A61B6/5211

  involving processing of medical diagnostic data · CPC title

• A61B6/032 Primary

  Transmission computed tomography [CT] · CPC title

• A61B6/50

  specially adapted for specific body parts; specially adapted for specific clinical applications · CPC title