Deterministic Arterial Input Function selection in DCE-MRI for automation of quantitative perfusion calculation of colorectal cancer

Magn Reson Imaging. 2021 Jan:75:116-123. doi: 10.1016/j.mri.2020.09.009. Epub 2020 Sep 25.

Abstract

Development of a deterministic algorithm for automated detection of the Arterial Input Function (AIF) in DCE-MRI of colorectal cancer. Using a filter pipeline to determine the AIF region of interest. Comparison to algorithms from literature with mean squared error and quantitative perfusion parameter Ktrans. The AIF found by our algorithm has a lower mean squared error (0.0022 ± 0.0021) in reference to the manual annotation than comparable algorithms. The error of Ktrans (21.52 ± 17.2%) is lower than that of other algorithms. Our algorithm generates reproducible results and thus supports a robust and comparable perfusion analysis.

Keywords: Arterial input function; Colorectal cancer; Dynamic contrast enhanced MRI; Quantitative perfusion; Segmentation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Arteries / diagnostic imaging*
  • Arteries / physiopathology*
  • Automation
  • Blood Circulation*
  • Colorectal Neoplasms / diagnostic imaging*
  • Colorectal Neoplasms / physiopathology*
  • Contrast Media
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging*
  • Reproducibility of Results

Substances

  • Contrast Media