Habitats in DCE-MRI to Predict Clinically Significant Prostate Cancers.

Abstact

Prostate cancer identification and assessment of clinical significance continues to be a challenge. Routine multiparametric magnetic resonance imaging has shown to be useful in assessing disease progression. Although dynamic contrast-enhanced imaging (DCE) has the ability to characterize perfusion across time and has shown enormous utility, radiological assessment (Prostate Imaging-Reporting and Data System or PIRADS version 2) has limited its use owing to lack of consistency and nonquantitative nature. In our work, we propose a systematic methodology to quantify perfusion dynamics for the DCE imaging. Using these metrics, 7 different subregions or <i>perfusion habitats</i> of the targeted lesions are localized and related to clinical significance. We found that quantitative features describing the habitat based on the late area under the DCE time-activity curve was a good predictor of clinical significance disease. The best predictive feature in the habitat had an AUC of 0.82, CI [0.81-0.83].

Authors
  • Balagurunathan Y
  • Choi J
  • Gage K
  • Gillies RJ
  • Lu H
  • Parra NA
  • Pow-Sang J
Pub Med ID
Appears In
Tomography, 2019, 5 (1)