ABSTRACT Prostate cancer (PCa), with an annually increasing incident rate, has become the most commonly diagnosed cancer in American men. The accurate diagnosis of aggressive PCa is critical for the survival of patients. Transrectal ultrasound (TRUS) guided biopsy, the current standard procedure for evaluating the presence and aggressiveness of PCa, suffers from low core yield, leading to under-sampling and under-grading of clinically significant tumors. To fill the long-standing technical gap in PCa diagnosis, we propose to develop a novel multimodal imaging platform which integrates the emerging photoacoustic (PA) imaging technique with the established transrectal ultrasound (TRUS) for multiparametric PCa diagnosis and grading. With the unique capability to map structural/anatomical, mechanical, functional, and molecular information reflecting pathological conditions over the entire human prostate in vivo, non-invasively, the proposed TRUS and PA (i.e. TRUSPA) multiparametric imaging can sensitively detect spatially distributed prostate tumors and, more importantly, differentiate aggressive tumors from non-aggressive ones. Hence, multiparametric TRUSPA (mpTRUSPA), when performed in the same way as in current TRUS, could largely improve the guidance of biopsy sampling by ensuring highly effective core extraction within the most aggressive malignant regions of the prostate. The central hypothesis is that real-time mpTRUSPA imaging – displaying B-mode US based structural information, Power Doppler US based vascular flow, shear wave elastography (SWE) based tissue stiffness, and spectral PA images for mapping hypoxia and angiogenesis - can sensitively characterize cancer aggressiveness in vivo by mapping a group of structural, mechanical, and functional biomarkers of PCa, and can subsequently guide the biopsy sampling. This hypothesis will be objectively and rigorously examined via the proposed studies on clinically relevant PCa animal models and human subjects using the following specific aims: Aim 1: Develop and validate mpTRUSPA imaging system using studies on durable prostate mimicking phantoms and mouse models of aggressive and non-aggressive PCa. Aim 2: Develop and validate an artificial intelligence (AI) framework capable of signal denoising and localization, prostate segmentation, artifact correction, and spectral unmixing of deep tissue PAI signals in real-time. Aim 3: Validate a set of PCa imaging biomarkers that are accessible in vivo by the AI enhanced mpTRUSPA imaging system in a clinical setting. Once the performance of mpTRUSPA imaging of PCa is validated via the proposed studies on animal models and human subjects, this affordable and user-friendly technology will be ready for appropriate phase I/II clinical trials in the next funding cycle. TRUSPA, with the unique capability of detecting and differentiating clinically significant PCa non-invasively, in real time, can seamlessly fit into the current clinical procedure of image-guide...