The INCISIVE pilots will focus on the following types of cancer: lung, colorectal, breast and prostate. They will be carried out in 8 pilot sites in Greece, Italy, Spain, Cyprus and Serbia, following all applicable ethical procedures, along with privacy and security protocols.
All pilots will be deployed in two phases. In the first phase, an observational study will be performed where the INCISIVE processing pipelines will be used retrospectively to evaluate the proposed system performance, added value and identify novel, potentially valuable prognostic markers. In the second phase, a short interventional study with a small number of participants will allow the use of the INCISIVE AI tools in practice, thus providing additional summative evaluation data for the developed techniques
Lung cancer is a phenomenon with global and public health issue implications. Several epidemiological studies highlight the relative risk factors and indicate new ways of diagnosis and treatments
Colorectal cancer is considered a major health problem. Diagnosing and staging colorectal cancer patients heavily relies on medical imaging. This pilot aims at addressing several challenges in colorectal cancer associated with technical, economical and organizational issues, such as improving region-specific (low) specificity of CT, fusion of clinical and biological data with diagnostic information from different imaging modalities, and more.
In Europe, 495.000 women are newly diagnosed yearly with breast cancer. The treatment and survival rate of patients is correlated to the stage of disease upon diagnosis. Current challenges present a fertile ground for development and application of machine learning techniques in support of improved detection and classification of tissue changes, improved performance of lower-cost imaging modalities, AI-enabled recommendations and prognostic modelling for Health Care Professionals, and more.
Prostate cancer is recognized as one of the major medical problems encountered by the male population. Prostate cancer survivors face long-term side effects, thus improved treatment pathways enabled by AI, such as those targeted by INCISIVE, are urgently required. Data fusion for improved patient stratification and enhanced patient-centric treatment, improved accuracy of mpMRI, are some of the challenges that INCISIVE aims at addressing.