Patient-Specific Contrast Impulse Response Determination
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Solution Overview
Problem
Current methods for determining patient-specific contrast medium impulse response functions are unreliable with incomplete test bolus contrast medium behavior data, requiring high temporal resolution and complete data measurement.
Innovation Solution
A method that generates simulated test bolus contrast medium behavior functions by combining basic impulse response functions with a test bolus input function, fitting these functions to patient-specific test bolus data to determine the patient-specific impulse response function, allowing for reliable determination even with reduced data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If deconvolution method is used to determine patient function from test bolus data, then patient-specific contrast medium impulse response function can be determined, but the method requires complete test bolus contrast medium behavior data measured over sufficiently long period with high temporal resolution
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing multiple simulated test bolus contrast medium behavior functions corresponding to different patient functions before actual measurement. When determining the patient function, the system compares measured data against these pre-prepared simulated functions, avoiding the need for complex real-time deconvolution and reducing sensitivity to incomplete measurement data.
Solution Approach 2:
The patent uses copying by creating simulated test bolus contrast medium behavior functions that replicate the expected measurement outcomes for different patient functions. These simulated copies serve as reference patterns that can be matched against actual measurements, providing a more robust determination method that doesn't require complete high-resolution data.
2Reliability
If test bolus measurement is performed with high temporal resolution and complete data collection, then reliable patient function can be determined, but measurement time and complexity increase
Solution Approach 1:
The system performs preliminary action by pre-generating a library of simulated test bolus contrast medium behavior functions that cover a range of possible patient functions. This preparation work is done beforehand, allowing rapid comparison with actual measurement data without requiring lengthy high-resolution measurements during the actual patient examination.
Solution Approach 2:
The patent applies partial action by showing that complete high-resolution measurement data is not necessary. Instead, the system can use reduced or incomplete test bolus data and still reliably determine patient function by matching against the pre-computed simulated functions, thereby reducing measurement time and complexity.
3Productivity
If reduced test bolus data is used for determining patient function, then measurement time is reduced, but determination accuracy decreases with conventional methods
Solution Approach 1:
The patent uses copying by creating simulated test bolus contrast medium behavior functions that serve as reference patterns. Even when actual measurement data is reduced or incomplete, the system can accurately determine patient function by comparing against these pre-computed simulated copies, maintaining determination accuracy while improving measurement efficiency.
Solution Approach 2:
The patent applies parameter changes by transforming the approach from direct deconvolution of measured data to pattern matching against simulated functions with varying parameters. This allows the system to work effectively with reduced data by comparing key characteristics rather than requiring complete high-resolution data sets.
Data Source
AI summary
A method for determining a patient-specific contrast medium impulse response function includes providing patient-specific test bolus contrast medium behavior data and a number of basic impulse response functions on the basis of a defined test bolus input function. Simulated test bolus contrast medium behavior functions are generated by combining the basic impulse response functions with the test bolus input function. The simulated functions and the patient-specific data are fitted to one another by varying a number of fitting parameters to obtain optimum fitting parameter values, and the patient-specific contrast medium impulse response function is then created based on the basic impulse response functions and the optimum fitting parameter values. A method for predicting a likely contrast medium behavior and a method for controlling a medical imaging system are also described. Additionally a corresponding apparatus, a control device and an imaging system having such a control device are also described.


