Using Multimodal MRI Quantitative Metrics as Image Biomarkers to Predict the Tumor Malignant Degree of Prostate Cancer

Motivation: Multimodal MRI plays a crucial role in prostate examinations, offering detailed imaging. But The potential of multimodal MRI metrics to predict early prostate cancer diagnosis remains unknown. Goal(s): To identify a non-invasive and effective examination method that provide reliable reference information for early prostate cancer diagnosis. Approach: Multimodal MRI data of 107 patients was acquired. The time-signal intensity curves were obtained, and the quantitative image metrics (Tmax, SImax, Rmax and ADC) were correlated with the tumor markers (P504s). Results: Multimodal MRI quantitative metrics have the potential to serve as imaging indicators for predicting the expression levels of P504s in PCa. Impact: The ADC value, Tmax(s), SImax% and Rmax% of multimodal MRI are correlated with the expression of P504s . These metrics can serve as imaging biomarkers to predict the proliferation and metabolic ability of PCa.