Aortic Valve Tissue Quantification from CTA Without Extra Imaging
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Solution Overview
Problem
Current methods for assessing aortic stenosis severity, particularly in patients with low-flow low-gradient calcific aortic stenosis, fail to account for noncalcific leaflet thickening, leading to inaccurate prognosis and intervention planning, and require additional radiation exposure through non-contrast CT imaging.
Innovation Solution
A method and system for quantifying calcific and noncalcific tissue components in aortic valves using computed tomography angiography (CTA) imaging data, employing Hounsfield unit thresholds and Gaussian mixture modeling to define a region of interest and differentiate tissue types, thereby calculating tissue volumes and percentages without additional imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-contrast CT imaging is used to quantify aortic valve calcium, then measurement precision of calcific tissue is improved, but radiation exposure increases
Solution Approach 1:
The patent combines calcific and noncalcific tissue quantification into a single contrast-enhanced CT imaging session. By integrating both tissue type assessments using dual-energy CT technology, the system eliminates the need for separate non-contrast CT imaging, thereby maintaining measurement precision while reducing radiation exposure from multiple imaging sessions.
Solution Approach 2:
The contrast-enhanced CT imaging system is designed to perform multiple functions simultaneously: it quantifies both calcific and noncalcific valve tissue components, assesses aortic stenosis severity, and provides prognostic information. This multi-functional approach replaces the need for separate specialized imaging protocols.
2Measurement precision
If separate non-contrast CT imaging is performed to assess valve calcium, then diagnostic accuracy is improved, but device complexity and imaging protocol complexity increase
Solution Approach 1:
The patent merges multiple diagnostic assessments into a single imaging protocol. By using contrast-enhanced CT with dual-energy capabilities, the system simultaneously evaluates calcific and noncalcific tissue components, eliminating the need for separate non-contrast CT imaging and simplifying the overall imaging workflow.
Solution Approach 2:
The system utilizes dual-energy CT technology that measures tissue attenuation at two different energy levels. By analyzing the differential attenuation properties of calcific and noncalcific tissues across these energy spectra, the system achieves accurate tissue characterization without requiring separate imaging sessions with different protocols.
3Ease of operation
If only calcific tissue volume is measured, then measurement simplicity is maintained, but prognostic accuracy deteriorates
Solution Approach 1:
The patent segments valve tissue into distinct components: calcific tissue and noncalcific tissue. By separately quantifying each tissue type and their respective volumes, the system provides comprehensive tissue characterization while maintaining a systematic and manageable assessment approach that does not overly complicate the evaluation process.
Solution Approach 2:
The system measures multiple parameters including calcific tissue volume, noncalcific tissue volume, and total valve tissue volume. By incorporating these additional parameters into the assessment, the system enhances prognostic accuracy while maintaining a structured measurement framework that builds upon rather than completely replaces traditional single-parameter assessments.
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
Improves the prediction of severe aortic stenosis and post-intervention outcomes by providing a comprehensive assessment of aortic valve tissue composition, differentiating between high-gradient and low-flow low-gradient AS, and reducing radiation exposure.
Implementation Method 1
identifying both calcific tissue components and noncalcific tissue components within the region of interest based at least in part on the generated cross-sectional images
Implementation Method 2
employing Hounsfield unit thresholds and Gaussian mixture modeling to define a region of interest and differentiate tissue types
Data Source
AI summary
Calcific and noncalcific aortic tissue components can be quantified. Pre-intervention planning computed tomography angiography imaging data is received. A region of interest is defined between the lower coronary ostium and the virtual basal ring. Cross-sectional images of the region of interest are rendered and calcific and noncalcific tissue components are identified based on Hounsfield unit thresholds. The volumes of the identified calcific and noncalcific tissue components are calculated and used to determine a total tissue volume (e.g., fibrocalcific volume) for the valve, as well as component percentages of the total tissue volume for the calcific and noncalcific components. These volumes and/or component percentages can be leveraged to predict severe AS, identify prognosis of post-TAVI outcomes, or otherwise facilitate planning of medical intervention.