Research progress of quantitative functional magnetic resonance imaging in prostate cancer

Prostate specific antigen (PSA), MRI examination and ultrasound-guided puncture biopsy are mainly used to diagnose prostate cancer (PCa). PSA is a specific tumor marker for PCa, but PSA is also elevated in prostate hyperplasia, prostatitis, cystoscopy, etc., which is prone to false-positive results. MRI is the main imaging technique for diagnosis, especially functional MRI plays an important value in the diagnosis of PCa. At present, the prostate imaging reporting and data system (PI-RADS) based on diffusion weighted imaging, diffusion weighted imaging (DWI), DCE and T₂WI has been widely used in the clinical diagnosis of PCa. However, the scoring of each sequence still relies on the subjective experience of the imaging physician, especially the PI-RADS score of 3 lesions cannot be determined as benign or malignant, which also leads to the uncertainty of the recommendation of puncture for such lesions. In addition, the prognosis and choice of treatment options for PCa differ among different risk strata. The aggressiveness of PCa is usually reflected by the Gleason score (GS). GS is the sum of the most common histological Gleason grade of the tumor plus the second most common histological Gleason grade. Gleason grading is divided into 1-5 grades according to the degree of differentiation of the cells, and the higher the grade, the worse the degree of cell differentiation and the worse the prognosis. In recent years, various new functional MRI techniques such as amide proton transfer imaging, intravoxel incoherent motion diffusion weighted imaging, diffusion kurtosis imaging, dynamic enhanced magnetic resonance imaging, etc. have been developed, and their quantitative parameters can accurately quantify the cytoarchitecture of prostate foci and cellular diffusion, microcirculation perfusion and angiogenesis, and molecular metabolism changes, which can help to increase the diagnostic accuracy of prostate cancer and have the potential to predict tumor. It also has the potential to predict tumor aggressiveness, which will provide more valuable objective evidence for the correct diagnosis of PCa. This article summarizes the research progress of the above new functional MRI quantitative techniques in the diagnosis of PCa.