Inter-operator variability in perfusion assessment of tumors in MRI using automated AIF detection

Med Image Comput Comput Assist Interv. 2005;8(Pt 1):451-8. doi: 10.1007/11566465_56.

Abstract

A method is presented for the calculation of perfusion parameters in dynamic contrast enhanced MRI. This method requires identification of enhancement curves for both tumor tissue and plasma. Inter-operator variability in the derived rate constant between plasma and extra-cellular extra-vascular space is assessed in both canine and human subjects using semi-automated tumor margin identification with both manual and automated arterial input function (AIF) identification. Experimental results show a median coefficient of variability (CV) for parameter measurement with manual AIF identification of 21.5% in canines and 11% in humans, with a median CV for parameter measurement with automated AIF identification of 6.7% in canines and 6% in humans.

Publication types

  • Evaluation Study

MeSH terms

  • Animals
  • Artificial Intelligence
  • Contrast Media*
  • Dogs
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods
  • Magnetic Resonance Imaging / methods*
  • Mammary Neoplasms, Animal / blood supply*
  • Mammary Neoplasms, Animal / diagnosis*
  • Neovascularization, Pathologic / diagnosis*
  • Observer Variation
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity

Substances

  • Contrast Media