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Advanced Classification of Colon Tumors From CT Scans Using Deep Learning for Optimized Treatment Decision-making.
Sponsor: Assistance Publique - Hôpitaux de Paris
Summary
This study aims to improve the classification of colon tumors using deep learning models trained on CT scans, specifically to distinguish between T1-T2 vs. T3-T4 stages and N- vs. N+ lymph node involvement. This classification is critical to guide preoperative treatment such as chemotherapy or immunotherapy. Given the limited accuracy of radiologists in current staging practice, automated image-based AI tools could enhance diagnostic precision and reproducibility, leading to more personalized and effective treatment planning. The investigator will develop and validate convolutional and transformer-based deep learning models using a large annotated dataset from multiple centers. Secondary objectives include fine-grained staging (T1 to T4), subgroup-specific models (MSS vs MSI), and predictive models for surgical
Official title: Advanced Classification of Colon Tumors From CT Scans Using Deep Learning for Optimized Treatment Decision-making : a Multicenter Study
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
1000
Start Date
2026-02
Completion Date
2028-02
Last Updated
2026-02-12
Healthy Volunteers
No
Conditions
Locations (1)
Departement of radiology, saint Antoin Hospital
Paris, France