Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast

Julie C DiCarlo; Angela M Jarrett; Anum S Kazerouni; John Virostko; Anna Sorace; Kalina P Slavkova; Stefanie Woodard; Sarah Avery; Debra Patt; Boone Goodgame; Thomas E Yankeelov

doi:10.1002/mrm.29511

Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast

Magn Reson Med. 2023 Mar;89(3):1134-1150. doi: 10.1002/mrm.29511. Epub 2022 Nov 2.

Authors

Julie C DiCarlo^{1

2}, Angela M Jarrett¹, Anum S Kazerouni³, John Virostko^{1

2

4}, Anna Sorace^{5

6

7}, Kalina P Slavkova⁸, Stefanie Woodard⁵, Sarah Avery^{4

9}, Debra Patt¹⁰, Boone Goodgame^{11

12

13}, Thomas E Yankeelov^{1

2

4

11

14

15}

Affiliations

¹ The Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, USA.
² Livestrong Cancer Institutes, The University of Texas at Austin, Austin, Texas, USA.
³ Department of Radiology, University of Washington, Seattle, Washington, USA.
⁴ Department of Diagnostic Medicine, The University of Texas at Austin, Austin, Texas, USA.
⁵ Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
⁶ Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA.
⁷ O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama, USA.
⁸ Department of Physics, The University of Texas at Austin, Austin, Texas, USA.
⁹ Austin Radiological Association, Austin, Texas, USA.
¹⁰ Texas Oncology, Austin, Texas, USA.
¹¹ Department of Oncology, University of Texas at Austin, Austin, Texas, USA.
¹² Department of Internal Medicine, University of Texas at Austin, Austin, Texas, USA.
¹³ Ascension Seton Medical Center, Austin, Texas, USA.
¹⁴ Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, USA.
¹⁵ Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Abstract

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 K^trans and v_e . 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 K^trans and 0.67 for v_e .

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.

Keywords: breast cancer; perfusion; pharmacokinetic modeling; sampling.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Breast Neoplasms* / diagnostic imaging
Breast* / diagnostic imaging
Contrast Media / pharmacokinetics
Female
Humans
Magnetic Resonance Imaging / methods
Retrospective Studies

Substances

Contrast Media

Abstract

Publication types

MeSH terms

Substances

Grants and funding