MR prostate exam is essential for the diagnosis, workup and follow-up of prostate cancer. It allows to detect subclinical prostate cancer following an increase in the level of PSA. The investigators can score the lesion according to the PIRADS classification and obtain an estimate of lesion malignancy. To perform this classification, T2 and DWI sequences are essential.

Detection and characterization of malignant lesion is important to address appropriate patient care pathway. The purpose of this project is to evaluate novel deep learning (DL) T2-weighted TSE (T2DL) and Diffusion (DWIDL) sequences for prostate MR exam and investigate its impact on diagnostic, examination time, image quality, and PI-RADS classification compared to standard T2-weighted TSE (T2S) and standard Diffusion (DWIS) sequences.

Inclusion Criteria:

• Age ≥ 18 ans
• Healthy subject without history of hepatic disease
• Patient addressed for an prostate MRI
• Ability to give consent

Exclusion Criteria:

• claustrophobia,
• major obesity (>140 kg),
• Patient under guardianship or curators
• Age < 18 years,
• Women,
• History of prostatectomy or irradiation of the prostate
• any contraindication to MRI exam