Adaptive Contrast Injection System for Medical Imaging
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Solution Overview
Problem
Current medical imaging procedures rely on standard, fixed protocols for contrast media delivery, which can result in varying image quality and contrast due to individual patient differences, and existing injector systems lack flexibility and convenience in adapting to patient-specific needs, especially with the introduction of advanced CT scanners.
Innovation Solution
A system that determines parameters for contrast injection protocols by analyzing time enhancement curves from multiple regions of interest, using a physiological model to estimate cardiac output and blood volume, and optimizing injection flow rates and durations to achieve uniform enhancement, while considering operational limitations of the injector system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standard fixed protocols are used for contrast media delivery, then the procedure is simple and fast, but image quality and contrast vary due to individual patient differences
Solution Approach 1:
The injection protocol transitions from fixed static parameters to dynamic adaptive parameters. The system automatically adjusts injection flow rate and contrast volume based on real-time monitoring of contrast enhancement in the aorta, allowing the protocol to adapt to each patient's cardiovascular characteristics while maintaining procedural efficiency
Solution Approach 2:
The system implements closed-loop feedback control by continuously monitoring contrast concentration in the aorta during injection and using this information to adjust injection parameters. The automated feedback mechanism compares actual enhancement against target enhancement levels and modifies the injection protocol accordingly to achieve consistent image quality
2Adaptability or versatility
If manual determination of injection parameters is used, then some patient customization is possible, but the process is time-consuming and operator-dependent
Solution Approach 1:
The system performs self-determination of injection parameters by automatically calculating optimal contrast volume and flow rate based on patient-specific data (weight, height, cardiovascular metrics) and real-time monitoring during the procedure. This eliminates the need for manual parameter calculation and reduces operator dependency while maintaining high adaptability to individual patient needs
Solution Approach 2:
The system performs preliminary calculations of optimal injection parameters before the actual contrast injection begins, using patient demographic data and preliminary cardiovascular assessments. This pre-computation allows the procedure to start immediately with optimized parameters already determined, reducing preparation time while maintaining customization
3Manufacturing precision
If higher contrast volumes are used to ensure adequate enhancement, then image quality improves, but contrast medium usage increases
Solution Approach 1:
The system uses real-time feedback from aortic enhancement monitoring to determine the precise amount of contrast needed. By continuously measuring contrast concentration and comparing it against target enhancement levels, the system stops injection exactly when adequate enhancement is achieved, preventing both under-enhancement and excessive contrast usage
Solution Approach 2:
The system dynamically adjusts injection parameters including flow rate, total volume, and injection duration based on patient-specific cardiovascular characteristics and real-time enhancement feedback. This personalized parameter optimization ensures adequate image quality while minimizing contrast medium usage for each individual patient
Data Source
Figure 1~2A
Figure 2B
Figure 2C
AI summary
A method of determining at least one parameter for an imaging procedure including the injection of a contrast enhancement fluid which includes a contrast enhancing agent, includes: substituting into a model discrete point data determined from at least one contrast time enhancement curve measured using an imaging system for a first region of interest resulting from injection of a bolus of the contrast enhancement fluid. In several embodiments, a sufficient number of data points can be substituted into the model to determine values for physiological variables in the model. The variables can, for example, be related to cardiopulmonary function. At least one data point from at least a second contrast time enhancement curve for a second region of interest measured using the imaging system can also substituted into the model.