Aortic Mesh Shape Analysis for More Accurate Disease Classification

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Solution Overview

Problem

Conventional methods for diagnosing aortic conditions, particularly ascending thoracic aortic aneurysm (aTAA), rely solely on maximal diameter measurements, which are inadequate due to variations in aortic morphology among individuals, leading to inaccurate diagnoses and treatment decisions.

Innovation Solution

A method using a mesh generator to create a mesh structure of the aorta, applying an intrinsic coordinate system, and comparing it to reference mesh structures to determine a similarity score for accurate classification of aortic conditions, considering the overall shape rather than just the maximal diameter.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If maximal diameter measurement is used for diagnosing aortic conditions, then the diagnostic method is simple and quick, but the diagnostic accuracy is insufficient due to individual variations in aortic morphology

Engineering Contradiction:

Improvediagnostic accuracyVSAvoidmethod complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The aorta is segmented into multiple measurement cross-sections along its length, with each cross-section providing local diameter measurements. This segmentation allows comprehensive assessment of aortic morphology at different locations, improving diagnostic accuracy by capturing the complete shape profile rather than relying on a single maximal diameter measurement.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The diagnosis transitions from one-dimensional maximal diameter measurement to three-dimensional shape analysis by measuring multiple cross-sections along the aortic length. This dimensional expansion enables evaluation of aortic morphology, curvature, and spatial distribution, providing a more comprehensive and accurate diagnostic assessment that accounts for individual anatomical variations.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Reliability

If maximal diameter alone is used to guide treatment decisions, then the treatment protocol is straightforward, but the treatment appropriateness is compromised due to insufficient consideration of aortic morphology variations

Engineering Contradiction:

Improvetreatment appropriatenessVSAvoiddecision-making complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

Different aortic cross-sections are evaluated for their local morphological characteristics, including diameter, curvature, and spatial relationships. This local quality assessment identifies specific regions with abnormal morphology that may require targeted treatment, improving treatment appropriateness by matching the treatment strategy to the specific anatomical abnormalities present in each patient.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

Multiple parameters beyond maximal diameter are measured and evaluated, including cross-sectional area, curvature radius, and three-dimensional shape indices. These parameter changes provide a more comprehensive picture of aortic health status, enabling more reliable treatment decisions that consider the full spectrum of aortic morphology rather than relying on a single threshold-based criterion.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If statistical shape modeling with mesh structures is applied, then the classification accuracy of aortic conditions is improved, but the computational complexity and processing time increase

Engineering Contradiction:

Improveclassification accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

Reference mesh structures representing normal and pathological aortic shapes are pre-computed and stored before actual diagnosis. During diagnosis, the patient's aortic mesh is compared against these pre-prepared references using similarity metrics, which significantly reduces processing time compared to performing complex shape analysis from scratch during each diagnostic evaluation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Instead of performing complex de novo shape analysis, the system uses pre-computed reference mesh structures as templates and compares the patient's aortic mesh against these copies. This copying approach allows rapid classification by measuring similarity to known patterns, reducing computational time while maintaining high classification accuracy through the use of detailed reference models.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20260065480A1Methods for determining aortic disease severity using statistical shape modeling and universal coordinate system mesh analysis

Publication Date: 2026.03.05 THE RGT UNIV OF MICHIGAN

AI summary

Systems and methods for classifying an aortic condition include capturing aorta image data, applying a mesh generation process, and determining an intrinsic coordinate system for the resulting mesh structure, including a plurality of vertices. The mesh structure is mapped to a reference coordinate system for generating, from the vertices, mapped vertices, which are embedded into the mesh structure to create an embedded mesh structure. The embedded mesh structure is compared to reference mesh structures including at least one normal aortic mesh structure and at least one pathology aortic mesh structure, and a similarity score is generated, and the aortic condition is classified.