Ventricular Assist Device Speed Modulation Thrombus Reduction
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Solution Overview
Problem
Ventricular assist devices (VADs) face challenges in minimizing thrombus formation, particularly red thrombi in the left ventricle, due to complex flow patterns and anatomical variability, and existing methods lack reliable data on efficacy and optimal installation conditions.
Innovation Solution
A computational method using mechanical and fluid dynamic models to determine patient-specific parameters for VAD therapy, including cannula implantation and pump operation, to predict quantities of interest such as ventricular velocity and pressure fields, and optimize speed modulation and cannula shape to reduce thrombus formation risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If VAD therapy is implemented to assist heart function, then patient survival is improved, but thrombus formation risk increases due to abnormal flow patterns
Solution Approach 1:
The patent applies dynamics by modulating pump speed to create artificial pulse patterns that disrupt stagnant flow regions. The pump speed is varied over time rather than maintained at a constant level, creating dynamic flow conditions that prevent thrombus formation while maintaining adequate cardiac support.
Solution Approach 2:
The patent changes physical parameters of the flow field by adjusting pump speed modulation patterns. By varying speed amplitude, frequency, and waveform characteristics, the patent optimizes flow patterns to eliminate stagnation zones that lead to thrombus formation, thereby reducing the harmful effect while preserving the life-saving benefit.
2Productivity
If pump speed is increased to improve cardiac output, then blood flow is enhanced, but white thrombus formation increases in the rotor vicinity
Solution Approach 1:
The patent applies periodic action through speed modulation that creates cyclic variations in pump speed. This periodic variation in rotational speed reduces the intensity and duration of high-shear regions around the rotor, thereby decreasing platelet activation and white thrombus formation while maintaining adequate mean cardiac output through the periodic flow enhancement.
3Object-affected harmful factors
If cannula alignment and placement are optimized to reduce thrombosis risk, then flow patterns improve, but determination of optimal conditions requires trial-and-error approach
Solution Approach 1:
The patent applies preliminary action by using computational fluid dynamics simulations to predict optimal cannula alignment and placement before actual implantation. This preliminary computational optimization allows clinicians to determine the best configuration in advance, avoiding the need for trial-and-error adjustments during or after implantation procedures.
Solution Approach 2:
The patent uses computational models that create virtual copies of the patient's anatomy and flow conditions. By simulating different cannula configurations in this virtual environment, the optimal placement can be identified without requiring multiple physical trial-and-error attempts on the actual patient.
4Quantity of substance
If computational simulations are used to optimize VAD parameters, then data acquisition cost is reduced and control over variables is improved, but model accuracy must be validated against clinical data
Solution Approach 1:
The patent applies feedback by validating computational model predictions against actual clinical trial data. The model results are compared with measured outcomes from patients, and the model parameters are refined based on this feedback to improve prediction accuracy. This iterative validation process ensures that the cost-effective computational approach maintains clinical relevance and precision.
Data Source
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AI summary
A method of determining effects of starting or operating a ventricular assistance therapy, such as a ventricular assist device, is described. One or more parameters of a patient heart and one or more parameters of the ventricular assistance therapy are determined. A mechanical and fluid dynamic model of at least a ventricle where the ventricular assistance therapy is or is to be used is then used to compute predicted quantities of interest for the patient heart from starting or operating the ventricular assistance therapy. This may be carried out iteratively until a predetermined configuration objective is achieved.