King's College London

Research portal

Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Asha Singanamalli, Mirabela Rusu, Rachel E. Sparks, Natalie N.C. Shih, Amy Ziober, Li Ping Wang, John Tomaszewski, Mark Rosen, Michael Feldman, Anant Madabhushi

Original languageEnglish
Title of host publicationJournal of Magnetic Resonance Imaging
PublisherJohn Wiley and Sons Inc.
Number of pages10
ISBN (Print)0002-9297
Accepted/In press29 May 2015
E-pub ahead of print25 Jun 2015
Published1 Jan 2016

Publication series

NameJournal of Magnetic Resonance Imaging

King's Authors


Background: To identify computer extracted in vivo dynamic contrast enhanced (DCE) MRI markers associated with quantitative histomorphometric (QH) characteristics of microvessels and Gleason scores (GS) in prostate cancer. Methods: This study considered retrospective data from 23 biopsy confirmed prostate cancer patients who underwent 3 Tesla multiparametric MRI before radical prostatectomy (RP). Representative slices from RP specimens were stained with vascular marker CD31. Tumor extent was mapped from RP sections onto DCE MRI using nonlinear registration methods. Seventy-seven microvessel QH features and 18 DCE MRI kinetic features were extracted and evaluated for their ability to distinguish low from intermediate and high GS. The effect of temporal sampling on kinetic features was assessed and correlations between those robust to temporal resolution and microvessel features discriminative of GS were examined. Results: A total of 12 microvessel architectural features were discriminative of low and intermediate/high grade tumors with area under the receiver operating characteristic curve (AUC) > 0.7. These features were most highly correlated with mean washout gradient (WG) (max rho 5 20.62). Independent analysis revealed WG to be moderately robust to temporal resolution (intraclass correlation coefficient [ICC] 5 0.63) and WG variance, which was poorly correlated with microvessel features, to be predictive of low grade tumors (AUC 5 0.77). Enhancement ratio was the most robust (ICC 5 0.96) and discriminative (AUC 5 0.78) kinetic feature but was moderately correlated with microvessel features (max rho 5 20.52). Conclusion: Computer extracted features of prostate DCE MRI appear to be correlated with microvessel architecture and may be discriminative of low versus intermediate and high GS.

View graph of relations

© 2020 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454