Advanced Classification of Colon Tumors From CT Scans Using Deep Learning for Optimized Treatment Decision-making.

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Conditions studied: Colonic Neoplasm

In brief

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

Key facts

Study ID

NCT07406958

Run by

Assistance Publique - Hôpitaux de Paris

People needed

1000

Starts

2026-02-01

Expected to finish

2028-02-01

Last updated by the study team

2026-02-12

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Adults who underwent colon resection surgery at an AP-HP hospital between 01/01/2017 and 01/11/2024, with:
• A preoperative abdominopelvic CT scan available within 60 days prior to surgery.
• A corresponding pathology report (anatomopathological results) available within 90 days post-surgery.
• Colon resection identified by CCAM procedure codes:
• HHFA002, HHFA004, HHFA005, HHFA006, HHFA008, HHFA009, HHFA010, HHFA014, HHFA017, HHFA018, HHFA021, HHFA022, HHFA023, HHFA024, HHFA026, HHFA028, HHFA029, HHFA030, HHFA031, HHFC040, HHFC296.
• Confirmed diagnosis of colon tumor by ICD-10 code:
• C18* (colonic neoplasms).

You may not qualify if…

• Patients who received neoadjuvant chemotherapy prior to surgery, identified by ICD-10 codes Z511 or Z512 recorded before the surgical act.
• These exclusions will be refined and confirmed through manual medical record review to ensure accuracy.
• Absence of usable CT imaging or anatomical pathology data linked to the surgical event.

Where it is running

• Departement of radiology, saint Antoin Hospital — Paris, France

Full record on ClinicalTrials.gov

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