Automated TAVI Planning Using 3D CT Angulation Parameters
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Solution Overview
Problem
Current transcatheter aortic valve implantation (TAVI) procedures rely on manual determination of angulation parameters for C-arm fluoroscopy, which can be inaccurate and time-consuming, lacking precise patient-specific anatomy analysis for optimal valve deployment.
Innovation Solution
An automated method and system that uses 3D computed tomography (CT) data to detect a patient-specific aortic valve model, derive angulation parameters, and determine anatomical measurements for C-arm fluoroscopy, employing a robust discriminative learning-based system to support precise TAVI planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual determination of angulation parameters is used for C-arm fluoroscopy, then the procedure can be performed with existing equipment, but the planning process is time-consuming and lacks precision
Solution Approach 1:
The patent replaces manual mechanical adjustment of C-arm fluoroscopy angulation parameters with an automated computer-based system that processes 3D CT data to calculate optimal angulation parameters automatically, eliminating time-consuming manual measurement while improving precision
Solution Approach 2:
The system automatically calculates and determines optimal angulation parameters by processing 3D CT volume data, transforming manual parameter adjustment into an automated computational process that derives parameters directly from patient-specific anatomical models
2Reliability
If manual determination of angulation parameters is used, then the system complexity remains low, but the measurement precision and reliability are insufficient
Solution Approach 1:
The patent introduces 3D CT volume data and automated computational algorithms as intermediaries between the patient's anatomy and the C-arm fluoroscopy imaging, creating a digital planning model that improves reliability while managing system complexity through standardized processing pipelines
Solution Approach 2:
The system creates a digital 3D copy of the patient's aortic valve anatomy from CT data, allowing virtual planning and simulation of valve deployment without requiring complex real-time adjustments during the actual procedure, thereby improving reliability
3Productivity
If automated detection of aortic valve model is implemented, then planning speed and precision improve, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent segments the complex task of aortic valve detection into distinct processing stages: 3D CT volume acquisition, automated valve model detection, anatomical landmark identification, and parameter calculation, making the difficult detection process manageable through systematic decomposition
Solution Approach 2:
The system replaces manual visual detection and measurement of the aortic valve with automated computer vision algorithms that process 3D CT data to automatically identify valve anatomy and calculate parameters, significantly improving productivity
Data Source
AI summary
A method and system for automated intervention planning for transcatheter aortic valve implantations using computed tomography (CT) data is disclosed. A patient-specific aortic valve model is detected in a CT volume of a patient. The patient-specific aortic valve model is detected by detecting a global location of the patient-specific aortic valve model in the CT volume, detecting aortic valve landmarks based on the detected global location, and fitting an aortic root surface model. Angulation parameters of a C-arm imaging device for acquiring intra-operative fluoroscopic images and anatomical measurements of the aortic valve are automatically determined based on the patient-specific aortic valve model.