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Comparison of model-based arterial input functions for dynamic contrast-enhanced MRI in tumor bearing rats
Deirdre M McGrath1, Daniel P Bradley, Jean L Tessier
1Imaging Science and Biomedical Engineering, School of Cancer and Imaging Sciences, University of Manchester, Manchester, United Kingdom. deirdre.mcgrath@rmp.uhn.on.ca
Abstract:
When using tracer kinetic modeling to analyze dynamic contrast-enhanced MRI (DCE-MRI) it is necessary to identify an appropriate arterial input function (AIF). The measured AIF is often poorly sampled in both clinical and preclinical MR systems due to the initial rapid increase in contrast agent concentration and the subsequent large-scale signal change that occurs in the arteries. However, little work has been carried out to quantify the sensitivity of tracer kinetic modeling parameters to the form of AIF. Using a preclinical experimental data set, we sought to measure the effect of varying model forms of AIF on the extended Kety compartmental model parameters (K(trans), v(e), and v(p)) through comparison with the results of experimentally acquired high temporal resolution AIFs. The AIF models examined have the potential to be parameterized on lower temporal resolution data to predict the form of the true, higher temporal resolution AIF. The models were also evaluated through application to the population average AIF. It was concluded that, in the instance of low temporal resolution or noisy data, it may be preferable to use a bi-exponential model applied to the raw data AIF, or when individual measurements are not available a bi-exponential model of the average AIF.
Insights
Accurate arterial input function (AIF) modeling is crucial for dynamic contrast-enhanced MRI (DCE-MRI) kinetic analysis. A bi-exponential model is recommended for low temporal resolution or noisy AIF data in DCE-MRI.
Area of Science:
- Medical Imaging
- Biophysics
- Pharmacokinetics
Background:
- Dynamic contrast-enhanced MRI (DCE-MRI) relies on accurate arterial input function (AIF) for tracer kinetic modeling.
- Poor AIF sampling in MR systems poses a challenge due to rapid contrast agent changes.
- Limited research quantifies AIF model sensitivity on kinetic parameters.
Purpose of the Study:
- To assess the impact of different AIF model forms on extended Kety model parameters (K(trans), v(e), v(p)).
- To compare model-derived AIFs with high temporal resolution experimental AIFs.
- To evaluate AIF models for low temporal resolution and population-averaged data.
Main Methods:
- Utilized a preclinical DCE-MRI dataset.
- Compared extended Kety model parameters derived from various AIF models against high temporal resolution experimental AIFs.
- Evaluated AIF models on population-averaged AIF data.
Main Results:
- Varying AIF model forms significantly affect tracer kinetic modeling parameters.
- A bi-exponential AIF model demonstrated robustness with low temporal resolution and noisy data.
- The bi-exponential model applied to population-averaged AIF provided reliable parameter estimation.
Conclusions:
- A bi-exponential model is preferable for AIF analysis in DCE-MRI when dealing with low temporal resolution or noisy data.
- When individual AIF measurements are unavailable, a bi-exponential model of the population average AIF is a viable alternative.
- This study provides guidance for selecting appropriate AIF models in DCE-MRI to improve kinetic parameter accuracy.
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