Purpose: To determine the best features to discriminate prostate cancer from benign disease and its relationship to benign disease class and cancer grade.
Materials and Methods: The institutional review board approved this study and waived the need for informed consent. A retrospective cohort of 70 patients (age range, 48-70 years; median, 62 years), all of whom were scheduled to undergo radical prostatectomy and underwent preoperative 3-T multiparametric magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging, were included. The digitized prostatectomy slides were annotated for cancer and noncancerous disease and coregistered to MR imaging with an interactive deformable coregistration scheme. Computer-identified features for each of the noncancerous disease categories (eg, benign prostatic hyperplasia [BPH], prostatic intraepithelial neoplasia [PIN], inflammation, and atrophy) and prostate cancer were extracted. Feature selection was performed to identify the features with the highest discriminatory power. The performance of these five features was evaluated by using the area under the receiver operating characteristic curve (AUC).
Results: High-b-value diffusion-weighted images were more discriminative in distinguishing BPH from prostate cancer than apparent diffusion coefficient, which was most suitable for distinguishing PIN from prostate cancer. The focal appearance of lesions on dynamic contrast-enhanced images may help discriminate atrophy and inflammation from cancer. Which imaging features are discriminative for different benign lesions is influenced by cancer grade. The apparent diffusion coefficient appeared to be the most discriminative feature in identifying high-grade cancer. Classification results showed increased performance by taking into account specific benign types (AUC = 0.70) compared with grouping all noncancerous findings together (AUC = 0.62).
Conclusion: The best features with which to discriminate prostate cancer from noncancerous benign disease depend on the type of benign disease and cancer grade. Use of the best features may result in better diagnostic performance.
Radiology. 2015 Jul 17:142856. [Epub ahead of print]
Litjens GJ1, Elliott R1, Shih NN1, Feldman MD1, Kobus T1, Hulsbergen-van de Kaa C1, Barentsz JO1, Huisman HJ1, Madabhushi A1.
1From the Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands (G.J.S.L., T.K., C.H.v.d.K., J.O.B., H.J.H.); Departments of Pathology (R.E.) and Biomedical Engineering (A.M.), Case Western University Hospitals, Cleveland, Ohio; and Department of Pathology, University of Pennsylvania, Philadelphia, Pa (N.N.C.S., M.D.F.).