Computerized analysis of prostate lesions in the peripheral zone using dynamic contrast enhanced MRI

Abstract

A novel automated computerized scheme has been developed for determining a likelihood measure of malignancy for cancer suspicious regions in the prostate based on dynamic contrast-enhanced magnetic resonance imaging (MRI) (DCE-MRI) images. Our database consisted of 34 consecutive patients with histologically proven adenocarcinoma in the peripheral zone of the prostate. Both carcinoma and non-malignant tissue were annotated in consensus on MR images by a radiologist and a researcher using whole mount step-section histopathology as standard of reference. The annotations were used as regions of interest (ROIs). A feature set comprising pharmacokinetic parameters and a T1 estimate was extracted from the ROIs to train a support vector machine as classifier. The output of the classifier was used as a measure of likelihood of malignancy. Diagnostic performance of the scheme was evaluated using the area under the ROC curve. The diagnostic accuracy obtained for differentiating prostate cancer from non-malignant disorders in the peripheral zone was 0.83 (0.75-0.92). This suggests that it is feasible to develop a computer aided diagnosis system capable of characterizing prostate cancer in the peripheral zone based on DCE-MRI.

A Comprehensive Segmentation, Registration, and Cancer Detection Scheme on 3 Tesla In Vivo Prostate DCE-MRI

“…Owing to the presence of MR image intensity non-standardness we utilized a non-linear DR scheme (LLE) coupled with consensus clustering to identify cancerous image pixels. Our CaP detection results, 60.72% sensitivity, 83.24% specificity, and 77.20% accuracy compare very favourably with results obtained by Vos et al [3] and were superior compared to those obtained via the 3TP method (41.53% sensitivity, 70.04% specificity, 67.37% accuracy). Future work will focus on validating our methodology on a much larger cohort of data.…”

“…Comparatively our metrics (60.64% sensitivity, 84.54% specificity, and 77.20% accuracy) have been achieved when examining the whole of the prostate while utilizing a more rigorously registered CaP extent for evaluation. We may hypothesize that had we similarly limited our analysis to the peripheral zone alone, our results would have been markedly superior compared to those reported in [3].…”

“…It can be seen that our proposed technique has an improved performance as compared to the popular state-of-the-art 3TP method across k ∈ {3, 4, 5, 6, 7}. Comparison against existing prostate DCE CAD: Analyzing the results by Vos et al [3] in differentiating between non-malignant suspicious enhancing and malignant lesions in the prostate, reveal that their sensitivity of 83% corresponds to a 58% specificity. These values were obtained by only considering the peripheral zone of the prostate.…”

“…Lesions are then identified as benign, malignant or indeterminate based on the rate of the contrast agent uptake and wash out. Vos et al [3] described a supervised CAD scheme for analysis of the peripheral zone of the prostate. Pharmacokinetic features derived from curve fitting were used to train the model and coarse quantitative evaluation was performed based on a roughly registered spatial map of CaP on MRI.…”

Multiparametric Magnetic Resonance Imaging of Prostate Cancer: Association of Quantitative Magnetic Resonance Parameters with Histopathologic Findings

“…Increased vascularity, capillary permeability, and interstitial hypertension in tumors are considered to underlie better tumor visualization (37).…”