Evaluation of Kinetic Entropy of Breast Masses Initially Found on MRI using Whole-lesion Curve Distribution Data: Comparison with the Standard Kinetic Analysis

Akiko Shimauchi, Hiroyuki Abe, David V. Schacht, Jian Yulei, Federico D. Pineda, Sanaz A. Jansen, Rajiv Ganesh, Gillian M. Newstead

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Objectives: To quantify kinetic heterogeneity of breast masses that were initially detected with dynamic contrast-enhanced MRI, using whole-lesion kinetic distribution data obtained from computer-aided evaluation (CAE), and to compare that with standard kinetic curve analysis. Methods: Clinical MR images from 2006 to 2011 with breast masses initially detected with MRI were evaluated with CAE. The relative frequencies of six kinetic patterns (medium-persistent, medium-plateau, medium-washout, rapid-persistent, rapid-plateau, rapid-washout) within the entire lesion were used to calculate kinetic entropy (KE), a quantitative measure of enhancement pattern heterogeneity. Initial uptake (IU) and signal enhancement ratio (SER) were obtained from the most-suspicious kinetic curve. Mann-Whitney U test and ROC analysis were conducted for differentiation of malignant and benign masses. Results: Forty benign and 37 malignant masses comprised the case set. IU and SER were not significantly different between malignant and benign masses, whereas KE was significantly greater for malignant than benign masses (p = 0.748, p = 0.083, and p < 0.0001, respectively). Areas under ROC curve for IU, SER, and KE were 0.479, 0.615, and 0.662, respectively. Conclusion: Quantification of kinetic heterogeneity of whole-lesion time-curve data with KE has the potential to improve differentiation of malignant from benign breast masses on breast MRI. Key points: • Kinetic heterogeneity can be quantified by computer-aided evaluation of breast MRI • Kinetic entropy was greater in malignant masses than benign masses • Kinetic entropy has the potential to improve differentiation of breast masses

Original languageEnglish
Pages (from-to)2470-2478
Number of pages9
JournalEuropean Radiology
Volume25
Issue number8
DOIs
Publication statusPublished - 2015 Aug 22

Keywords

  • Breast
  • Cancer
  • Computer-Assisted
  • Diagnosis
  • Imaging
  • Magnetic resonance imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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