Multiparametric MRI for prostate cancer localization in correlation to whole-mount histopathology - Abstract

PURPOSE: To prospectively evaluate multiparametric magnetic resonance imaging (MRI) for accurate localization of intraprostatic tumor nodules, with whole-mount histopathology as the gold standard.

MATERIALS AND METHODS: Seventy-five patients with biopsy-proven, intermediate, and high-risk prostate cancer underwent preoperative T2-weighted (T2w), dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MRI at 1.5T. Localization of suspicious lesions was recorded for each of 24 standardized regions of interest on the different MR images and correlated with the pathologic findings. Generalized estimating equations (GEE) were used to estimate the sensitivity, specificity, accuracy, positive, and negative predictive value for every MRI modality, as well as to evaluate the influence of Gleason score and pT-stage. Tumor volume measurements on histopathological specimens were correlated with those on the different MR modalities (Pearson correlation).

RESULTS: DW MRI had the highest sensitivity for tumor localization (31.1% vs. 27.4% vs. 44.5% for T2w, DCE, and DW MRI, respectively; P < 0.005), with more aggressive or more advanced tumors being more easily detected with this imaging modality. Significantly higher sensitivity values were obtained for the combination of T2w, DCE, and DW MRI (58.8%) as compared to each modality alone or any combination of two modalities (P < 0.0001). Tumor volume can most accurately be assessed by means of DW MRI (r = 0.75; P < 0.0001).

CONCLUSION: Combining T2w, DCE, and DW imaging significantly improves prostate cancer localization.

Written by:
Isebaert S, Van den Bergh L, Haustermans K, Joniau S, Lerut E, De Wever L, De Keyzer F, Budiharto T, Slagmolen P, Van Poppel H, Oyen R.   Are you the author?
Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium.

Reference: J Magn Reson Imaging. 2012 Nov 21. Epub ahead of print.
doi: 10.1002/jmri.23938


PubMed Abstract
PMID: 23172614

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