The PROFTH project aims at developing the robotics and AI technologies to enable focal therapies for prostate cancer (PCa) using the robotic positioned developed during the ERC-PoC PROST. PCa therapy is lagging about 10 years from e.g. kidney and breast therapies, that has shifted from invasive surgery to percutaneous ablation of the tumour. Several trials are acquiring the clinical evidence to support the shift from radical prostatectomy to PCa focal therapy, considering the multifocal aspect of PCa and the need to preserve the surrounding anatomical structures. Key to focal therapies is the ability to accurately and repeatably positioning the ablation device in the PCa area and to achieve the minimal tissue removal that satisfies the safety margins around the tumor and leaves the other structures untouched. The problem of accurately positioning a biopsy needle in the PCa area has been solved by the PROST project, thus we want to build on this capability to set the basis of PCa focal therapy. To achieve this goal, PROFTH will address three main objectives: 1. definition of the joint requirements between clinical needs, capabilities of the current ablation devices and positioning accuracy of PROST; 2. development of the digital twin of the pelvic area to integrate the medical information of the patient; and 3. develop a planning algorithm that will compute the position of the ablation devices in the patient PCa. We will test the developed algorithms with laboratory and ex-vivo experiments using the ablation systems available at the University Hospital of Verona.

The ROBIOPSY project aims at evolving the robotic device for prostate cancer (PC) biopsy demonstrated during the ERC-PoC PROST into a product prototype that will be ready for clinical trials. The focus of the project will be two-fold: the engineerization of the PROST prototype, and the accurate analysis of the business case of prostate cancer diagnosis and its potential extension to focal therapy. We will correct the shortcomings of the pre-clinical tests, meet the strict medical certification regulations, and address the Health Economics implications of our solution. ROBIOPSY will achieve better performance than current competitors because it solves the two main causes of PC diagnostic error: uncertain target identification, and inaccurate needle positioning, as demonstrated in the pre-clinical tests. A novel image fusion method will permit to significantly reduce the target uncertainty, while the robotic device will zero the positioning error.The ROBIOPSY prototype will consist of a single cart holding the robotic needle positioner, and housing all the electronic components. The electronics will be divided into two subsystems: interface and data processing, and safety critical controls. This will reduce the operational risks and will simplify the medical certification. A multi-centric study is ongoing to collect biopsy images to train the Machine Learning algorithms for prostate segmentation and lesion identification. In parallel to the technical development, we will analyze in depth the business case of prostate biopsy in selected European Countries, we will analyze the time/cost reduction due to the new device and will establish the economic foundation of focal therapy, to be ready for the expected evolution of PC treatments.