Prostate cancer: feasibility and preliminary experience of a diffusional kurtosis model for detection and assessment of aggressiveness of peripheral zone cancer

Andrew B. Rosenkrantz, Eric E. Sigmund, Glyn Johnson, James S. Babb, Thais C. Mussi, Jonathan Melamed, Samir S. Taneja, Vivian S. Lee, Jens H. Jensen

Research output: Contribution to journalArticlepeer-review

224 Citations (Scopus)


PURPOSE: To assess the feasibility of diffusional kurtosis (DK) imaging for distinguishing benign from malignant regions, as well as low- from high-grade malignant regions, within the peripheral zone (PZ) of the prostate in comparison with standard diffusion-weighted (DW) imaging. MATERIALS AND METHODS: The institutional review board approved this retrospective HIPAA-compliant study and waived informed consent. Forty-seven patients with prostate cancer underwent 3-T magnetic resonance imaging by using a pelvic phased-array coil and DW imaging (maximum b value, 2000 sec/mm2). Parametric maps were obtained for apparent diffusion coefficient (ADC); the metric DK (K), which represents non-Gaussian diffusion behavior; and corrected diffusion (D) that accounts for this non-Gaussianity. Two radiologists reviewed these maps and measured ADC, D, and K in sextants positive for cancer at biopsy. Data were analyzed by using mixed-model analysis of variance and receiver operating characteristic curves. RESULTS: Seventy sextants exhibited a Gleason score of 6; 51 exhibited a Gleason score of 7 or 8. K was significantly greater in cancerous sextants than in benign PZ (0.96+/-0.24 vs 0.57+/-0.07, P.99). K exhibited significantly greater sensitivity for differentiating sextants with low- and high-grade cancer than ADC or D (68.6% vs 51.0% and 49.0%, respectively; P
Original languageEnglish
Pages (from-to)126-135
Number of pages10
Issue number1
Early online date1 May 2012
Publication statusPublished - Jul 2012


  • Analysis of Variance
  • Bayes Theorem
  • Biopsy
  • Diagnosis
  • Differential
  • Diffusion
  • Magnetic Resonance Imaging
  • Feasibility Studies
  • Humans
  • Image Interpretation

Cite this