Background: Colon tumor is a molecularly heterogeneous disease. Consequently, tissue sampling biopsy cannot be considered fully representative of tumor behaviour and molecular profile. Such limitations have led researchers to seek alternative procedures able to comprehensively assess the whole tumour heterogeneity. The "Omic" revolution has recently involved also the field of medical imaging, through radiomics. Such technology aims at extracting quantitative features from imaging studies to improve disease characterization. The possibility to merge radiomic data derived from the whole tumour with genomics, might allow to create a model that can be used to characterize colon tumors and predict their behaviors in terms of aggressiveness, relapse and risk of metastases.
Aims: The ADRENALIN (rADiogenomic in ColoREctal Cancer: aN ArtificiaL IntelligeNce approach) project will be a 2-year project with the main aim to characterize biological processes in a voxel-wise high-spatial resolution approach, extracting first, second and third order radiomics features from CT datasets of patients with colorectal tumor. Radiomic features will be subsequently computed by AI- model and integrated with clinical data to eventually generate a radiogenomic signature for personalised management of patients with colon tumor.
Experimental Design: A retrospective data sets collection of 100 patients (radiology, pathology, genomics) will be analysed in order to identify the genetic and radiomic features of colorectal tumors and the clinical endpoints as the outcomes of the predictive model. Further, a prospective population of 50 patients will be enrolled to obtain a new multicentric population for the test and validation of the AI-model.
Expected Results: AI-model including different cancer hallmarks (radiology, pathology, genomic) may represent a comprehensive assessment of colorectal tumor with increased
accuracy in terms of response to treatment and prognosis.
