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Updated: Aug 23, 2025

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast
Julie C DiCarlo1,2, Angela M Jarrett1, Anum S Kazerouni3
1The Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, USA.
Purpose:
A method is presented to select the optimal time points at which to measure DCE-MRI signal intensities, leaving time in the MR exam for high-spatial resolution image acquisition.
Theory:
Simplicial complexes are generated from the Kety-Tofts model pharmacokinetic parameters Ktrans and ve . A geometric search selects optimal time points for accurate estimation of perfusion parameters.
Methods:
The DCE-MRI data acquired in women with invasive breast cancer (N = 27) were used to retrospectively compare parameter maps fit to full and subsampled time courses. Simplicial complexes were generated for a fixed range of Kety-Tofts model parameters and for the parameter ranges weighted by estimates from the fully sampled data. The largest-area manifolds determined the optimal three time points for each case. Simulations were performed along with retrospectively subsampled data fits. The agreement was computed between the model parameters fit to three points and those fit to all points.
Results:
The optimal three-point sample times were from the data-informed simplicial complex analysis and determined to be 65, 204, and 393 s after arrival of the contrast agent to breast tissue. In the patient data, tumor-median parameter values fit using all points and the three selected time points agreed with concordance correlation coefficients of 0.97 for Ktrans and 0.67 for ve .
Conclusion:
It is possible to accurately estimate pharmacokinetic parameters from three properly selected time points inserted into a clinical DCE-MRI breast exam. This technique can provide guidance on when to capture images for quantitative data between high-spatial-resolution DCE-MRI images.
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