Visceral Fat Estimation via DXA Region Segmentation
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Solution Overview
Problem
Current methods for measuring visceral fat, such as CT and MRI, are costly and involve high radiation, while dual-energy X-ray absorptiometry (DXA) struggles to distinguish between visceral and subcutaneous fat due to its two-dimensional projection technique.
Innovation Solution
A method using dual-energy X-ray measurements to estimate visceral fat by placing specific regions on a two-dimensional projection image of the abdomen, combining these regions through computer processing to differentiate visceral from subcutaneous fat, and displaying the results, with optional use of polynomial expansion and linear equations correlated with quantitative computed tomography measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT or MRI is used to measure visceral fat, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent introduces an intermediary computational model that processes standard DXA scan data to estimate visceral fat. This mediator translates ordinary 2D DXA measurements into visceral fat estimates using polynomial expansions and linear equations, avoiding the need for complex CT or MRI systems while maintaining reasonable measurement precision.
Solution Approach 2:
The patent creates a computational copy of the visceral fat measurement process by using mathematical models (polynomial expansions and linear equations) that replicate the information extraction capability of CT/MRI from simpler DXA data. This allows visceral fat estimation without directly using complex imaging equipment.
2Measurement precision
If CT is used to measure visceral fat, then measurement precision is improved, but harmful factors increase due to high radiation dosage
Solution Approach 1:
The patent employs a disposable computational approach where simple DXA scans (low radiation) are used instead of expensive, high-radiation CT scans. The computational model processes these low-cost inputs to generate visceral fat estimates, effectively replacing a high-harm measurement method with a low-harm alternative.
Solution Approach 2:
The computational algorithm acts as an intermediary that extracts visceral fat information from low-radiation DXA scans, eliminating the need for high-radiation CT scans. This mediator preserves measurement capability while removing the harmful radiation exposure.
3Ease of operation
If DXA is used to measure fat mass, then ease of operation and cost are improved, but measurement precision worsens due to inability to distinguish visceral from subcutaneous fat
Solution Approach 1:
The patent changes the parameters used in DXA analysis by applying polynomial expansions and linear equations to the standard DXA measurements. This transformation of parameters allows the system to differentiate visceral from subcutaneous fat using the same easy-to-operate DXA equipment, improving precision without sacrificing ease of use.
Solution Approach 2:
The patent adds a computational dimension to the 2D DXA images by using polynomial expansions that extract additional information from the existing data. This dimensional transformation allows differentiation of fat types without requiring complex 3D imaging or changing the basic DXA operation.
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
This approach allows for a cost-effective and radiation-efficient estimation of visceral fat, improving upon the limitations of DXA by distinguishing between visceral and subcutaneous fat, providing accurate and reliable results for health assessments.
Implementation Method 1
acquiring x-ray measurements for respective pixel positions related to a two-dimensional projection image of a portion of a subject's abdomen, wherein at least some of the measurements are dual-energy x-ray measurements
Data Source
AI summary
Dual-energy absorptiometry is used to estimate visceral fat metrics and display results, preferably as related to normative data. The process involves deriving x-ray measurements for respective pixel positions related to a two-dimensional projection image of a body slice containing visceral fat and subcutaneous fat, at least some of the measurements being dual-energy x-ray measurements, processing the measurements to derive estimates of metrics related to the visceral fat in the slice, and using the resulting estimates. Processing the measurements includes an algorithm which places boundaries of regions, e.g., a large “abdominal” region and a smaller “abdominal cavity” region. Two boundaries of the “abdominal cavity” region are placed at positions associated with the left and right innermost extent of the abdominal muscle wall by identifying inflection of % Fat values. The regions are combined in an equation that is highly correlated with VAT measured by quantitative computed tomography in order to estimate VAT.