Radiomic features of tumor and of liver-tumor interface in patients with colorectal liver metastases Humanitas University - dott. Luca Viganò

Keywords

Statistical learning
Living Systems and Precision Medicine
MOX responsible:
F. Ieva
Team:
L. Cavinato; C. Masci
Start date:
October 2021
End date:
October 2022
Abstract:
Liver metastases (CLM) affect about half of patients with colorectal cancer and dictate patients' prognosis. Prediction of prognosis is of paramount importance for patients allocation to the most adequate treatment, but available parameters do not adequately fulfil this role. Tumor pathology and molecular data and liver-tumor interface characteristics showed a major prognostic impact, but they are not included in standard prognostic scores and standard imaging modalities are poorly informative about them. Radiomic analyses demonstrated a very good prediction of pathology data and of patients outcome in several tumor, but their application to CLM remains to explore. Hypothesis: The preoperative identification of CLM and liver-tumor interface characteristics would improve prognosis prediction and patients allocation to treatments. As in other tumors, radiomic analyses could allow a major refinement in prediction of pathology data. Radiomic features per se could have a major association with prognosis.