Patient-Specific Aortic Endoprosthesis Simulation for Complication Risk
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cardiovascular surgical interventions for endoprosthesis implantation in the aorta are prone to complications such as endoleaks, migration, infolding, occlusion, thrombosis, and kinks, with limited pre-operative planning capabilities.
Innovation Solution
A computer-implemented method simulates the interaction between an endoprosthesis and the patient's aorta using 3D images to reconstruct a deformable digital model, position the endoprosthesis, and compute risk indices for potential surgical complications through finite element analysis, allowing pre-operative evaluation and personalization of the surgery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional surgical planning methods are used, then the surgical procedure can be performed, but surgical complications such as endoleaks, migration, infolding, occlusion, thrombosis, and kinks cannot be predicted beforehand
Solution Approach 1:
The patent performs virtual implantation simulations and complication risk assessments before the actual surgical procedure. By reconstructing 3D patient-specific aortic models and simulating endoprosthesis deployment in advance, the system identifies potential complications (endoleaks, migration, infolding, occlusion, thrombosis, kinks) prior to surgery, allowing surgeons to adjust the plan and avoid these issues during the actual operation.
Solution Approach 2:
The patent creates a digital copy or virtual model of the patient's aorta based on medical imaging data (CT or MRI scans). This 3D digital replica allows for risk-free virtual testing of different endoprosthesis configurations and surgical approaches, eliminating the need to physically test devices on the actual patient beforehand while maintaining anatomical accuracy for reliable complication prediction.
2Adaptability or versatility
If standard endoprosthesis implantation procedures are performed, then the surgery can be completed, but complications such as endoleaks and migration occur due to lack of personalization
Solution Approach 1:
The patent analyzes specific local characteristics of the patient's aorta (aneurysm geometry, neck dimensions, wall thickness, calcifications) and uses these localized features to predict site-specific complications. The simulation focuses on critical regions where complications are most likely to occur, such as the proximal and distal attachment zones for endoleak risk, rather than treating the entire aorta uniformly, thereby personalizing the surgical plan to the patient's unique anatomy.
Solution Approach 2:
The system varies key parameters such as endoprosthesis size, shape, material properties, and deployment position in virtual simulations to find the optimal configuration for each patient. By adjusting these parameters in the digital model and assessing complication risks for each configuration, the system identifies the personalized implantation strategy that minimizes risks while accounting for the patient's specific anatomical constraints and physiological conditions.
3Measurement precision
If comprehensive simulation computations are performed to identify all risk areas, then surgical complications can be predicted, but computational resources and time are significantly consumed
Solution Approach 1:
The patent divides the aorta and endoprosthesis into discrete segments or finite elements, allowing the simulation to focus computational resources on specific high-risk regions rather than uniformly analyzing the entire structure. The system segments the analysis into critical zones (proximal attachment, aneurysm sac, distal attachment) and evaluates complication risks independently for each segment, improving both precision and computational efficiency.
Solution Approach 2:
The system performs comprehensive simulations only for the most critical parameters and high-risk regions identified from preliminary anatomical assessment, rather than exhaustively analyzing every possible parameter. By focusing computational effort on the most influential factors (such as apposition quality at attachment zones for endoleak prediction, or stent flexibility for kink prediction), the system achieves clinically relevant precision without requiring excessive computational resources.
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
Enables pre-operative prediction of surgical complications, improving surgical planning by identifying high-risk areas and enabling selection of endoprosthesis models that minimize these risks.
Implementation Method 1
the computation of the geometrical deformation is performed by finite element analysis
Data Source
AI summary
A computer-implemented method for simulating an interaction between an endoprosthesis dedicated to be implanted in a portion of a patient aorta and said portion of the patient aorta, so as to determine areas with risk of surgical complications.