Multimodal AI analysis of Prostate Cancer indicators to reduce patient backlogs and improve patient care.

Prostate cancer affects 1 in 8 men throughout their lifetime. Due to increasing longevity and increased awareness the incidence and prevalence of prostate cancer is increasing. Prostate cancer is predominantly diagnosed using Magnetic Resonance Imaging (MRI) scans; however these scans require specialist interpretation and timely reporting. A lack of radiologists and particularly urology specialist radiologists can be a limiting factor, especially as demand grows lead to delays in the diagnostic pathway. An artificial intelligence (AI)/machine learning (ML) based MRI diagnostic aid for prostate cancer may support clinical decision making and reduce time to interpret MRI. JivaRDX (a class IIa medical device, pending MHRA approval) is a radiologyfacing application that predicts the presence of cancerous tissue from prostate MRI scans, and is intended for use as a diagnostic aid. Operationally, JivaRDX can integrate into the radiology workflow non-disruptively by automatically annotating imaging files and therefore requires minimal intervention and training. Jiva have previously demonstrated a proof-of-concept achieving detection and localisation of prostate cancer from MRI scans (87% sensitivity, 67% specificity); bone, tissue and organs differentiated with 96.8% specificity. It has been found to perform within reported MRI diagnostic accuracy in the clinic (58-96% sensitivity, 23-87% specificity). The JivaRDX AI/ML-based MRI platform was evaluated over eighteen months across all 4 acute hospital sites within Hywel Dda University Health Board (HDUHB).