Spectral CT Adipose Tissue Identification

Solution Overview

Problem

Current imaging techniques, such as PET-CT, are complex, costly, and lack sensitivity and specificity in distinguishing between white adipose tissue (WAT) and brown adipose tissue (BAT), due to radiation exposure and subjective interpretation, making it difficult to monitor the transformation of WAT to BAT for obesity management.

Innovation Solution

The use of spectral CT scanning to differentiate between adipose tissue types based on spectrally different attenuation properties, including vascularization and carbon/oxygen ratios, through data processing techniques that generate data maps and cluster analysis, allowing for quantitative measurement and identification of WAT and BAT.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If PET-CT imaging is used to identify adipose tissue types, then metabolic activity can be visualized, but the method becomes complex and requires two imaging processes

Engineering Contradiction:

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines anatomical CT imaging with spectral analysis capabilities into a single integrated system. By merging the structural visualization of CT with spectral attenuation analysis, the method eliminates the need for separate PET imaging while maintaining adipose tissue differentiation capability through automated spectral processing

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent replaces the metabolic tracer-based PET imaging mechanism with a physical spectral analysis mechanism using X-ray attenuation properties. This substitution eliminates the need for radiotracer injection and complex PET detection systems, using instead the inherent spectral differences in X-ray attenuation between WAT and BAT

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If PET-CT is used for adipose tissue identification, then functional imaging is achieved, but radiation exposure increases

Engineering Contradiction:

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent extracts and utilizes the spectral attenuation information already present in CT imaging data, separating this functional information from the anatomical imaging. By extracting spectral characteristics directly from the CT process, the method eliminates the need for additional radiotracer-based functional imaging and associated radiation exposure

Inventive Principle:

Principle #2Taking out (Extraction)

3Ease of manufacture

If conventional CT scanning is used, then anatomical detail is provided, but differentiation between adipose tissue types is not achieved

Engineering Contradiction:

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent introduces dynamic spectral analysis to the static CT imaging process. By analyzing attenuation properties across multiple energy levels or spectral bins, the method dynamically extracts functional information from the conventional CT data, enabling adipose tissue differentiation without changing the basic CT scanning mechanism

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent changes the analysis parameters of CT data from single-energy Hounsfield units to multi-energy spectral attenuation coefficients. This parameter transformation allows differentiation of adipose tissue types by exploiting their distinct spectral signatures, maintaining imaging simplicity while enhancing measurement precision

Inventive Principle:

Principle #35Parameter changes

4Measurement precision

If spectral CT scanning is implemented, then adipose tissue differentiation is improved, but data processing complexity increases

Engineering Contradiction:

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent implements self-service through automated spectral processing algorithms that automatically differentiate adipose tissue types without requiring manual interpretation. The system performs self-analysis of spectral attenuation patterns, automatically generating tissue classification maps and reducing the need for complex manual data processing or expert review

Inventive Principle:

Principle #25Self-service

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Spectral CT scanning provides a simpler, quicker, and more accurate method for identifying adipose tissue types, reducing radiation exposure and improving sensitivity and specificity, enabling effective monitoring of adipose tissue transformation for obesity management.

Implementation Method 1

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

Methodology Applied

Scientific EffectX-ray attenuation: Absorption (EM radiation)

Data Source

PatentUS10813600B2Identifying types of adipose tissue

Publication Date: 2020.10.27

AI summary

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.