Computational 3D Cusp Modeling for TAVR Sizing and Alignment
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Solution Overview
Problem
Current methods for identifying coronary cuspid landmarks or nadirs in transcatheter aortic valve replacement (TAVR) procedures are prone to intra- and inter-operator errors and inconsistency, particularly in cases with significant cusp size differences or bicuspid aortic roots, affecting the accuracy of THV sizing and alignment.
Innovation Solution
A computational technique using structured 3D datasets to simultaneously determine nadirs based on 3D skeletonized datasets of coronary anatomical structures, including aortic root and cusps, to facilitate accurate THV sizing and alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of coronary cuspid landmarks is used, then the process is simple and quick, but accuracy is reduced due to intra- and inter-operator errors
Solution Approach 1:
The patent replaces manual mechanical identification with an automated computational system that processes 3D medical images to identify coronary cuspid landmarks. The system uses algorithmic analysis of 3D surface points and skeletonization to automatically determine nadir points, eliminating human operator variability while maintaining clinical workflow efficiency.
Solution Approach 2:
The system enables self-service by allowing the imaging data to speak for itself through automated feature extraction. The computational algorithm independently identifies landmarks based on geometric properties of the 3D anatomical structures without requiring manual intervention, making the process autonomous and consistent across different users.
2Reliability
If 2D planimetric technique is used, then the method is straightforward, but reliability is reduced due to inconsistency in identifying nadirs
Solution Approach 1:
The patent transitions from 2D planimetric visualization to 3D volumetric representation of coronary anatomical structures. By reconstructing and analyzing 3D surface points from multiple 2D imaging slices, the system provides comprehensive spatial information that enables reliable identification of nadir points regardless of viewing angle or projection, eliminating the limitations of 2D techniques.
Solution Approach 2:
The system segments the 3D coronary anatomical structures into distinct components including individual cusps and their corresponding nadir points. This segmentation allows independent analysis and identification of each landmark, improving reliability by treating each feature separately rather than relying on holistic 2D visual assessment that can be ambiguous.
3Measurement precision
If automated computational technique is used, then accuracy and consistency are improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary 3D reconstruction and landmark identification during the pre-procedural planning phase, allowing sufficient time for comprehensive automated analysis without impacting the actual TAVR procedure time. The computational modeling is completed in advance, so the results are ready when needed for surgical planning and device selection.
Solution Approach 2:
The system optimizes processing efficiency by adjusting computational parameters such as image resolution, sampling density, and algorithm complexity based on the specific clinical case and available hardware resources. This allows the automated technique to adapt its computational demands to balance accuracy requirements with processing time constraints.
Data Source
AI summary
Noninvasive imaging plays an important role in determining the size of the transcatheter heart valve (THV) in preparation of a transcatheter aortic valve replacement (TAVR) procedure. The identification of the coronary cuspid landmarks or nadirs of each cusp plays a key role in determining the reference points for the two-dimensional (2D) images of the THV. Rather than using nadirs that are currently identified manually upon inspection of 2D computed tomography (CT) images, the methods and systems of the present disclosure utilizing structured 3D dataset of cusps to simultaneously determine the nadirs, which are especially beneficial, particularly when the sizes of cusps have significant difference (i.e., Type 1 aortic valve with two fused leaflets) or the aortic root has a bicuspid configuration rather than a tricuspid configuration.