A model selection framework to quantify microvascular liver function in gadoxetate‐enhanced MRI: Application to healthy liver, diseased tissue, and hepatocellular carcinoma

@article{Berks2021AMS,
  title={A model selection framework to quantify microvascular liver function in gadoxetate‐enhanced MRI: Application to healthy liver, diseased tissue, and hepatocellular carcinoma},
  author={Michael Berks and R. A Little and Yvonne Watson and Susan Cheung and Anubhav Datta and J. P. B. O'Connor and Davide Scaramuzza and Geoffrey J. M. Parker},
  journal={Magnetic Resonance in Medicine},
  year={2021},
  volume={86},
  pages={1829 - 1844}
}
We introduce a novel, generalized tracer kinetic model selection framework to quantify microvascular characteristics of liver and tumor tissue in gadoxetate‐enhanced dynamic contrast‐enhanced MRI (DCE‐MRI). 
Madym: A C++ toolkit for quantitative DCE-MRI analysis
TLDR
Quantitative DCE- MRI (DCE-MRI), in which one or more tracer-kinetic models are fitted to the contrast-agent concentration time-series, enables the estimation of clinically useful parameters of tissue microvasculature.

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