Giannini V, et al. – This study aimed to correlate the performance of experienced readers in detecting prostate cancer (PCa) applying likelihood maps generated by a computer–aided detection (CAD) system with that of unassisted interpretation of multiparametric magnetic resonance imaging (mp–MRI). The data considered that experienced readers applying likelihood maps generated by a CAD scheme can detect more patients with ?10 mm prostate cancer (PCa) lesions than unassisted MRI interpretation; overall reporting time is shorter. Different reading paradigms should be investigated to gain more insight into CAD–human interaction.