A Bayesian hierarchical model for the analysis of a longitudinal dynamic contrast-enhanced MRI oncology study.

@article{Schmid2009ABH,
  title={A Bayesian hierarchical model for the analysis of a longitudinal dynamic contrast-enhanced MRI oncology study.},
  author={Volker J. Schmid and Brandon Whitcher and Anwar R. Padhani and N. Jane Taylor and Guang-Zhong Yang},
  journal={Magnetic resonance in medicine},
  year={2009},
  volume={61 1},
  pages={163-74}
}
Imaging in clinical oncology trials provides a wealth of information that contributes to the drug development process, especially in early phase studies. This article focuses on kinetic modeling in DCE-MRI, inspired by mixed-effects models that are frequently used in the analysis of clinical trials. Instead of summarizing each scanning session as a single kinetic parameter--such as median k(trans) across all voxels in the tumor ROI-we propose to analyze all voxel time courses from all scans and… CONTINUE READING

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