Multifarious Kinetic Analysis for Differentiation of Prostate Cancer and Benign Prostatic Hyperplasia in DCE-MRI

Prostate cancer (PC) and benign prostatic hyperplasia (BPH) are the most common diseases diagnosed in men, early and accurate differential diagnosis of which is an important task. DCE-MRI plays an essential role for cancer detection and characterization. Previous studies have tried to characterize time-enhancement curves of malignant and benign prostate tissues, and thereby to deduce the best distinguishing parameters in DCE-MRI. However, the best diagnostic criteria still remain inexplicit due to their own analysis schemes and assumptions. The significant tissue parameters may take the form of synergistic subsets in the combinatorial space of multifarious kinetic features. In this study, we postulate that extending the individual analysis schemes of contrast enhancement kinetics to a hybrid analysis scheme and that selecting a meaningful feature subset from a combined feature pool may allow an improved performance for lesion classification. Based on this postulation, we propose a novel approach to prostate MRI computeraided diagnosis (CAD) using multifarious kinetic parameters in DCE-MR images.