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+title: PICUS
+title_long: Prognostic imaging of prostate cancer by ultrasound
+finished: false
+picture: projects/picus.png
+template: project-single
+groups: diag
+default_group: diag
+people: Fabian Hoitsma, Henkjan Huisman, Michiel Sedelaar
+description: PICUS aims to develop AI for multiparametric ultrasound to predict the presence, location and aggressiveness of prostate cancer.
+bibkeys: 
+type: normal
+
+## Background
+
+One in eight men is confronted with prostate cancer (PCa). The current diagnostic trajectory has many shortcomings. The Prostate-Specific Antigen (PSA) blood test has too many false alarms, causing unnecessary biopsies and missing treatable clinically significant PCa (csPCa). Ultrasound (US)‐guided biopsies are inadequate as a follow‐up to the PSA test. Due to their unreliability, these biopsies frequently result in either overdiagnosis or underdiagnosis, complicating treatment decisions. As a result, early detection is unfeasible, and prostate cancer is often detected only at a late, possibly fatal stage. Research into timely, accurate, widely available diagnostic modalities is therefore crucial. Recently, multiparametric magnetic resonance imaging (mpMRI) has evidenced clinical value in reducing unnecessary biopsies. However, MRI is costly and requires expertise both during reading and biopsy. Current MRI-US fusion biopsy improves over US-guided biopsies but still face difficulties. New technology research can result in a breakthrough. Firstly, novel US parameters show increased diagnostic accuracy, evidencing the potential for multiparametric US (mpUS) to become a valuable, cost-effective option for diagnosis and biopsy guidance. Secondly, artificial intelligence (AI) is emerging as a powerful tool to enhance medical image interpretation and reduce diagnostic and interventional workflow and costs. However, the current rise of mpMRI and MRI‐guided ultrasound provides a solid basis for generating ground‐truth data of csPCa presence to train and explore AI methodology.
+
+The PICUS project leverages these novel mpUS advances and AI assistance to predict the presence, location, and aggressiveness of PCa. PICUS is led by the Technical University Eindhoven (prof. Massimo Misschi) in collaboration with Radboudumc and various other public and private partners: Canon Medical, General Electric, Angiogenesis Analytics, Martini Klinik Hamburg, Prostaatkanker Stichting.
+
+## Aim
+
+The aim of the PICUS project at Radboudumc in terms of AI development is three-fold:
+
+- Expanding mpMRI in its ability to characterize prostate lesions in order to improve specificity.
+- Improving prostate biopsy targeting by fusing mpUS and mpMRI.
+- Enable mpUS to act as a standalone method for detection of prostate cancer as a cost-effective alternative to mpMRI. 
+
+
+## Funding
+The PICUS project is funded by [NWO](https://www.nwo.nl/en/projects/20441).