Multiparametric Characterization of Colorectal Cancers
Multiparametric Characterization of Colorectal Cancers
The primary goal of this observational study is to assess the predictive value of a model developed through a multiparametric analysis of clinical images, histopathological data, CT scans, and molecular analysis. This analysis will be conducted on a retrospective cohort recruited at CHU Brest (training group). The model will then be validated using external cohorts from other centers (test group).
Around 20% of patients with colorectal cancer present with synchronous liver metastases at the time of diagnosis. In recent years, there has been increasing interest in the high-throughput extraction of quantitative data from medical images, a technique known as radiomics. Radiomic analysis can involve both qualitative and quantitative imaging parameters, which may be used independently or integrated into multiparametric prediction models.
This is a multicenter, retrospective study designed to investigate the demographic, clinical, and radiological features, treatment regimens, and outcomes of patients diagnosed with colorectal cancer. The study will involve the collection of anonymized clinical data, including age, sex, diagnosis date, treatment details, results from histopathological and genetic analyses, as well as pre- and post-treatment medical imaging typically performed as part of the management of colorectal cancer patients, along with survival and tumor recurrence data.
PRIMARY EVALUATION CRITERIA Prediction of recurrence/treatment response based on the radiomic model.
SECONDARY EVALUATION CRITERIA The impact of CT scan image acquisition and reconstruction parameters on the prognostic model.
Inclusion Criteria:
Patients who have undergone surgery for colorectal cancer.
Exclusion Criteria: