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NCT Number: NCT07088393

Artificial Intelligence Diagnosis of Different Histopathological Growth Patterns of Colorectal Cancer Liver Metastasis

This study selected cases of colorectal cancer liver metastasis patients who underwent liver metastasis tumor resection, retrieved the pathological HE sections of the metastatic lesions, and constructed a predictive model. AI software was applied to delineate different types of regions, achieving full automation of HGP prediction and constructing a predictive model. Statistical analysis was conducted on the classification of histopathological growth patterns (HGP) of liver metastasis and the survival prognosis of patients, and the differences in prognosis among different HGP classification methods were compared. This provides a new method for judging prognosis and treatment for clinical treatment of colorectal cancer liver metastasis patients.

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This study is active but is not currently recruiting participants.

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Key information

Conditions

Liver Metastases of Colorectal Cancer

Sex eligibility

All sexes

Study type

Observational

Primary location

Sixth Affiliated Hospital, Sun Yat-sen University

Guangzhou, Guangdong, 510655, China

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients with colorectal cancer liver metastases who underwent resection of liver metastases;
  • Confirmed by a pathologist as having liver metastases from colorectal cancer;

Exclusion criteria

  • Cases of colorectal cancer liver metastasis that cannot be classified by histopathology.

Treatment and study plan

Primary outcomes

  1. The accuracy rate of the predictive model for HGP classification

    Time frame: Half a year

    We will build an AI prediction model for HGP prediction and verify the accuracy of the AI-assisted prediction model in classifying HGP.

Secondary outcomes

  1. The time for the predictive model to perform HGP classification

    Time frame: Half a year

    We will measure the time it takes for the AI-assisted predictive model to classify HGP and compare the difference in interpretation time between the model and pathologists.

  2. Progression-free survival of patients with different HGP classifications

    Time frame: Through study completion, an average of 1 year

    The time from surgery to tumor progression in patients with colorectal cancer liver metastasis of different HGP types

Sponsors and collaborators

Lead sponsor

Sun Yat-sen University

Other

Registry information

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
Jul 28, 2025
Registry last updated
Jul 28, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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