Search for clinically relevant imaging biomarkers in a multicenter study of anal squamous cell carcinoma patients using Deep Learning and Radiomics

Project start
Institution: Department of Radiation Oncology, Technical University of Munich
Applicant: Dr. Jan Peeken
EKFS funding line: First and Second Applications
Image: Radiomics Workflow

Anal carcinoma constitutes a rare disease. Radiochemotherapy constitutes the current standard of care, but achieves only limited healing rates. So far, no clinical, molecular, or pathological parameter has been identified to adjust the given therapy to individual patients. The proposed project aims to analyze the potential of quantitative analysis of medical imaging data (“radiomics”) and artificial intelligence techniques for improved prediction of patients’ survival. The resulting image-based prediction models may be used for improved patient risk assessment in the future. This information could then be used for personalization of therapy.

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