Rao P. Gullapalli PhD, Presenter: Nothing to Disclose

Khan Mohammad Siddiqui MD, Abstract Co-Author: Partner, iVirtuoso, Inc, Baltimore, MD Medical Advisory Board, General Electric Company, Barrington, IL Research Consultant, Mercury Computer Systems, Inc, Chelmsford, MA

Bao Zhang, Abstract Co-Author: Nothing to Disclose

Danniele Holanda MD, Abstract Co-Author: Nothing to Disclose

Steven Roys, Abstract Co-Author: Nothing to Disclose

John Papadimitriou MD, PhD, Abstract Co-Author: Nothing to Disclose

James Borin PhD, Abstract Co-Author: Nothing to Disclose

Harris Yfantis MD, Abstract Co-Author: Nothing to Disclose

Michael Naslund MD, PhD, Abstract Co-Author: Nothing to Disclose

Eliot Lawrence Siegel MD, Abstract Co-Author: Nothing to Disclose

et al, Abstract Co-Author: Nothing to Disclose

et al, Abstract Co-Author: Nothing to Disclose

Advanced MRI techniques such as spectroscopy, dynamic contrast enhanced (DCE) imaging and diffusion tensor imaging (DTI) have shown to be independently effective in prostate cancer (PCa) detection. To determine the efficacy of the combined use of these techniques, we performed a multiparametric study to evaluate the sensitivity and specificity of PCa detection and compared with step section histology.

14 patients diagnosed with PCa (age 44-68; PSA 0.5-14ng/ml) that elected for radical prostatectomy were enrolled in the study. T2 weighted images, 3D-CSI covering the entire prostate, DCE-MRI, DTI with six directional diffusion weighting, and T2 mapping using a CPMG acquisition were acquired on a 1.5T Siemens system. Anatomic images of the ex-vivo prostate were obtained to assist in cancer localization with pathology findings. Ktrans maps were obtained from the DCE data. Cho+Cr/Cit map was computed from MRSI data. Apparent diffusion coefficient and fractional anisotropy maps were made from the DTI data. From continuous axial 3mm step-sections of the prostate specimen H&E stained pathology slides were made. In vivo images, ex vivo MR images & the digitized cut prostate slices were registered to each other to facilitate radiology/pathology correlation. ROC analysis was performed between the pathology findings and each of the imaging techniques and their combinations.

Focal cancer regions larger than 16mm3 were well delineated by the T2 and Ktrans maps. Although Ktrans maps revealed a significant difference between normal and abnormal tissue (p<0.001), the maps were not sensitive to changes in the grade of the tumors. DTI was able to reveal lesions larger than 40mm3. While MR spectroscopy showed excellent correlation with histology its sensitivity was low with lesions smaller than 0.3cc.

Our results demonstrate that multi-parametric MRI approach can improve the accuracy of PCa detection. The combination of each of the techniques increased the sensitivity and specificity from 72% & 80% respectively to 90% & 89% respectively when compared with normal MRI findings alone.

Addition of advanced MRI techniques improves the sensitivity and specificity of PCa detection.

Gullapalli, R, Siddiqui, K, Zhang, B, Holanda, D, Roys, S, Papadimitriou, J, Borin, J, Yfantis, H, Naslund, M, Siegel, E, et al, , et al, , Multiparametric MR Imaging of the Prostate with Step-section Histopathology Correlation.  Radiological Society of North America 2007 Scientific Assembly and Annual Meeting, November 25 - November 30, 2007 ,Chicago IL. http://archive.rsna.org/2007/5012719.html