The characterization of cancerous tissue alterations in magnetic resonance imaging (MRI) requires the acquisition of demanding gradient pulse sequences that use a high slew rate. This allows for a high temporal resolution both in the sensitivity to the movement of water molecules diffusion in tissues and to the kinetics of blood flow through vessels and capillaries, the principles of diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) examinations.
Prostate cancer is a neoplastic process usually detected by MRI using not only anatomical images, but also DWI and DCE through the quantification of parameters such as the apparent diffusion coefficient (ADC) and vascular permeability (K^trans). The combination of these imaging biomarkers quantification algorithms with novel artificial intelligence organ segmentation algorithms allow for the automation of the whole prostate gland analysis almost in real time.
These prostate MRI analysis pipelines will set the new paradigm for prostate cancer screening in clinical routine, assisted by AI, and benefiting from the fast - timing characteristics of diffusion and perfusion sequences in MRI.