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Updated: Aug 11, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Comparative study into the robustness of compartmental modeling and model-free analysis in DCE-MRI studies
Caleb Roberts1, Basma Issa, Andrew Stone
1Imaging Science and Biomedical Engineering, University of Manchester, Manchester, UK.
Purpose:
To evaluate and compare the reproducibility of the preferred phenomenological parameter IAUC60 (initial area under the time-concentration curve [IAUC] defined over the first 60 seconds postenhancement) with the preferred modeling parameter (K(trans)), as derived using two simple models, in abdominal and cerebral data collected in typical Phase I clinical trial conditions.
Materials And Methods:
Dynamic contrast enhanced MRI (DCE-MRI) time series were acquired at two imaging centers from a group of patients with abdominal tumors and a group with gliomas. At both imaging centers, precontrast T1 was calculated using a variable flip angle three-dimensional spoiled gradient echo acquisition that was used to quantify tissue contrast agent concentration, allowing voxelwise definition of summary DCE-MRI parameters.
Results:
A comparison of reproducibility showed that there was no statistically significant difference in reproducibility between IAUC60 and K(trans), although there was a trend towards better reproducibility for K(trans) (P = 0.0782). The 95% confidence intervals (CIs) for individual changes showed that for IAUC60 and K(trans), changes in excess of 47% and 31%, respectively, are outside the range of normal variability.
Conclusion:
Although modeling is more complex and more computationally intensive than an IAUC parameterization, our data suggest this approach to be preferable to a model-free approach since it provides greater physiological insight without a reduction in statistical power for Phase I/II clinical drug trials.

