KIA-Korekt: Staged Unimodal-to-Multimodal AI Evaluation for Perioperative Risk Prediction in Colorectal Cancer

NCT07537491 | Recruiting

• 1 other identifier: KIA-Korekt-2025
• Study Type: observational
• Target: 910
• Locations: 1 country
• Sites: 1

Brief Summary

Perioperative complications following surgery for colorectal cancer (CRC) represent a major cause of postoperative morbidity and mortality. Existing risk stratification tools lack the precision to capture the complex biological and morphological factors that determine individual patient vulnerability. Artificial intelligence (AI)-based analysis of medical imaging data offers a promising approach to improve preoperative risk prediction. The KIA-Korekt study investigates whether perioperative complications in CRC patients can be predicted using multimodal AI-based image analysis. Three complementary imaging modalities are integrated: digital histopathology (haematoxylin-eosin whole-slide images, H\&E-WSIs), preoperative CT and MRI radiomics, and multiplex tissue imaging (mTI) including multiplex immunohistochemistry (mIHC) and imaging mass cytometry (IMC). The study includes a retrospective cohort of approximately 750 CRC patients treated between 2011 and 2021, and a prospective validation cohort of approximately 210 patients recruited from 2026 to 2028. Deep learning and radiomic feature extraction pipelines are applied to all modalities individually and in multimodal combination. Predicted outcomes include anastomotic leakage, wound infection, sepsis, ICU admission, and in-hospital mortality within 30 days of surgery. The study is conducted at the University Hospital Brandenburg, Brandenburg Medical School Theodor Fontane, in collaboration with the Department of Computational Pathology, TU Dresden.

Conditions

Colorectal Cancer Postoperative Complications

Outcome Measures

Primary Outcomes (1)

• Prediction accuracy of perioperative complications

  Occurrence of postoperative complications including anastomotic leakage, sepsis, ICU admission, and in-hospital mortality. Outcomes are defined based on clinical documentation and assessed as binary variables (yes/no).

  30 days postoperative

Study Arms (2)

Group 1: Retrospective Training Cohort

Patients with colorectal cancer treated between 2011-2021 with available imaging and histopathology data.

Prospective Cohort

Patients with colorectal cancer enrolled prospectively between 2026-2028.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult patients (≥18 years) with histologically confirmed colorectal cancer undergoing surgical treatment at a tertiary care center. The study includes both retrospectively collected patients (2011-2021) and prospectively enrolled patients (2026-2028) with available imaging and histopathological data.

You may qualify if:

• Adult patients (≥18 years)
• Histologically confirmed colorectal adenocarcinoma
• Undergoing surgical resection (curative or palliative intent)
• Availability of H\&E-stained whole-slide images (WSIs) from the primary tumour

You may not qualify if:

• Patients not undergoing surgical treatment
• Missing H\&E-stained tissue slides of the primary tumour
• Histopathological material of insufficient quality for analysis

Sponsors & Collaborators

• Rene Mantke: lead
• Technische Universität Dresden: collaborator

Study Sites (1)

University Hospital Brandenburg an der Havel, Brandenburg an der Havel, Germany (Single-center)

Brandenburg an der Havel, Germany

RECRUITING

Central Study Contacts

Melissa Horner, MSc

CONTACT

+4915207809673; melissa.schadl@mhb-fontane.de

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Univ.-Prof. Dr. med.

Study Record Dates

• First Submitted: April 8, 2026
• First Posted: April 17, 2026
• Study Start: January 1, 2011
• Primary Completion (Estimated): December 31, 2027
• Study Completion (Estimated): June 30, 2028
• Last Updated: April 17, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will share

Locations

DE (1)