Brain Amyloid PET Voxel Analysis for Gray-White Matter Interpretation

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Solution Overview

Problem

Current amyloid PET imaging for Alzheimer's disease diagnosis relies on qualitative evaluation by the naked eye, leading to inconsistent judgment results due to difficulties in distinguishing gray matter and white matter absorption, which affects diagnostic accuracy.

Innovation Solution

A brain amyloid PET processing system that includes a processor and storage device, capable of processing amyloid PET and MRI images to generate normalized brain spaces, perform tissue segmentation, and use machine learning for voxel-based interpretation to objectively assess gray and white matter absorption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If qualitative evaluation with the naked eye is used for amyloid PET image interpretation, then the operation process is simple, but the measurement precision and consistency of judgment results deteriorate

Engineering Contradiction:

Improvesimplicity of interpretation processVSAvoidaccuracy of gray matter vs white matter absorption judgment

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent replaces the manual visual evaluation method with an automated computer-based image processing system. The processor automatically performs image registration, tissue segmentation, and uptake value calculation, substituting the mechanical/visual inspection process with computational analysis to achieve both ease of operation and high measurement precision

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary processing system that includes image registration, tissue segmentation masks, and automated uptake value calculation. This intermediary layer between the raw PET image and the final interpretation provides objective, quantifiable measurements while maintaining operational simplicity through automation

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If automated image processing and machine learning are implemented, then the measurement precision and consistency improve, but the device complexity increases

Engineering Contradiction:

Improveaccuracy and consistency of amyloid uptake assessmentVSAvoidcomplexity of processing system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the brain into distinct tissue types (gray matter and white matter) using automated tissue segmentation algorithms and masks. This segmentation approach simplifies the complex task of differential uptake assessment by treating each tissue type separately, improving measurement precision while managing system complexity through modular processing

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent transforms the interpretation from qualitative visual assessment to quantitative parameter-based analysis by calculating standardized uptake values (SUV) and comparing gray matter uptake against white matter reference regions. This parameter transformation enables precise, consistent measurements using standardized metrics

Inventive Principle:

Principle #35Parameter changes

3Reliability

If voxel-based quantitative analysis is performed to compare gray matter and white matter uptake, then the diagnostic accuracy improves, but the difficulty of detecting and measuring increases

Engineering Contradiction:

Improvediagnostic accuracy for Alzheimer's diseaseVSAvoidcomplexity of voxel-wise uptake measurement

Core Design Contradiction:

ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent implements self-service through automated image processing where the system performs image registration, tissue segmentation, and uptake value calculation without manual intervention. The processor automatically identifies gray matter regions, calculates voxel-wise uptake values, and compares them against white matter reference, enabling reliable diagnostic assessment while eliminating the complexity of manual voxel-by-voxel measurement

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12514518B2Brain amyloid PET processing system and operation method thereof and non-transitory computer readable medium

Publication Date: 2026.01.06 TAIPEI MEDICAL UNIV

AI summary

An operation method of a brain amyloid PET processing system includes steps as follows. The whole brain white matter amyloid PET image is extracted from the smoothed amyloid PET image in the range of the whole brain white matter mask of the normalized brain space, and the uptake value with the preset maximum ratio in the whole brain white matter amyloid PET image is calculated; in the smoothed amyloid PET image of the normalized brain space, one or more voxels in the range of the whole brain gray matter mask are marked and counted, in which each voxel uptake value of the one or more voxels is greater than the uptake value of the preset maximum ratio of the whole brain white matter amyloid PET image, and the one or more voxels are used for interpretation training and test of the classification of the machine learning.