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

This is a retrospective, non-interventional, observational study evaluating the use of deep learning methods to improve preoperative CT-based TNM staging in patients with colon cancer. The study is conducted across multiple sites within the AP-HP hospital network (Paris, France) and uses data extracted from the institutional Health Data Warehouse.

Radiologic accuracy in assessing tumor stage (T) and lymph node status (N) remains limited, despite being critical for selecting neoadjuvant treatments. Artificial intelligence models trained on annotated imaging data may provide more consistent, reproducible, and accurate classification.

The study cohort includes adult patients who underwent colon resection between January 2017 and November 2024, with a preoperative CT scan and corresponding pathology report. Eligible cases are identified using standardized diagnostic (ICD-10) and procedural (CCAM) codes. Imaging and clinical data are de-identified prior to analysis.

Several AI model architectures will be tested, including 3D convolutional neural networks and transformer-based approaches. CT scans will be pre-processed using standard pipelines; pathology labels will be extracted using natural language processing (NLP) techniques or manual review when needed. Model performance will be assessed through cross-validation and evaluated using AUC, F1-score, sensitivity, and specificity.

Exploratory analyses will include fine-grained tumor staging and the potential prognostic value of image-based features for clinical outcomes such as survival.

No study-related procedures are performed. All analyses are conducted on existing data, in compliance with French data protection and ethical regulations.

Inclusion criteria

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).

Exclusion criteria

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.