Arterial Input Function Correction Using Cardiac Output Constraints
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Solution Overview
Problem
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) faces challenges in accurately measuring arterial input function (AIF) due to nonlinear relationships between MR signal intensity and gadolinium concentration, artifacts such as inflow effect, dephasing, and partial volume effects, which affect the precision of perfusion and permeability measurements.
Innovation Solution
A constrained conversion procedure is employed to compute AIF, taking into account the subject's cardiac output, ensuring that the area under the peak of AIF obeys the indicator dilution principle, thereby generating more robust perfusion parameters. This involves modifying time sequence signal data to satisfy the indicator dilution principle, using cardiac output data, and fitting the signal versus time curve to a gamma variate function to correct for recirculation and shift the baseline signal level for accurate tracer concentration estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If direct conversion from MR signal intensity to gadolinium concentration is used, then the measurement process is simple, but the precision of AIF measurement deteriorates due to nonlinear relationships and artifacts
Solution Approach 1:
The patent introduces an indicator dilution model as an intermediary framework that connects MR signal measurements to gadolinium concentration through a physiologically-based arterial input function. This model acts as a mediator that accounts for nonlinear signal-concentration relationships and artifacts, transforming direct signal measurements into accurate concentration values while maintaining operational feasibility.
Solution Approach 2:
The patent transforms the measurement approach by changing from direct signal-to-concentration conversion to a model-based parameter estimation approach. By using the indicator dilution model with physiological parameters (cardiac output, blood volume, transit time), the system achieves accurate AIF measurement despite nonlinearities and artifacts, resolving the contradiction between simplicity and precision.
2Ease of operation
If conventional direct measurement of AIF is used, then the procedure is straightforward, but reliability deteriorates due to inflow effects, dephasing, and partial volume artifacts
Solution Approach 1:
The patent implements a feedback mechanism where the indicator dilution model continuously adjusts the AIF estimation based on measured parameters (cardiac output, blood volume, transit time) and compares the modeled concentration curve with actual signal measurements. This feedback loop compensates for artifacts and improves reliability while maintaining procedural straightforwardness through automated model-based correction.
Solution Approach 2:
The indicator dilution model serves as an intermediary that mediates between raw MR signal measurements and reliable AIF values. It accounts for inflow effects, dephasing, and partial volume artifacts by incorporating physiological constraints, thereby improving reliability without significantly complicating the measurement procedure.
3Stability of the object's composition
If averaged population-based AIF is used, then individual variability is reduced, but measurement precision deteriorates due to systematic artifacts that persist in averaged data
Solution Approach 1:
The patent applies local quality by customizing the AIF estimation for each individual subject using their specific physiological parameters (cardiac output, blood volume, transit time) obtained from the indicator dilution model. This approach maintains the stability benefit of reduced variability while improving precision by accounting for individual-specific characteristics and correcting systematic artifacts at the individual level rather than through population averaging.
Data Source
AI summary
Exemplary embodiments of method, system and computer-accessible medium according to the present disclosure can be provided for converting magnetic resonance (MR) arterial signal intensity versus time curves to arterial input functions (AIF) with less susceptibility to artifacts such as flow-related enhancement. Exemplary methods, systems and computer-accessible medium can be used to constrain AIF to satisfies the indicator dilution principle, according to which the area under an initial pass component of AIF can be equal to the injected dose divided by the cardiac output. For example, Monte Carlo simulations of MR renography and tumor perfusion protocols can be performed for comparison with conventional methods.