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

NCT ID: NCT07088393

Last Updated: 2025-07-28

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

437 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-07-09

Study Completion Date

2025-12-31

Brief Summary

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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.

Detailed Description

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Conditions

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Liver Metastases of Colorectal Cancer

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

PROSPECTIVE

Study Groups

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Colorectal cancer liver metastasis cohort

A total of 437 cases of colorectal cancer liver metastasis patients who underwent liver metastasis tumor resection were selected, with a total of 1205 tumor lesions. Pathological HE sections were retrieved and a predictive model was constructed. Among them, 301 cases were in the training set and 106 cases were in the validation set. After constructing the model, it was used to prospectively interpret 30 lesions. The interpretation result of a senior pathologist with a high professional title was taken as the standard to evaluate the accuracy and interpretation time of the model.

No interventions assigned to this group

Eligibility Criteria

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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.
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Sun Yat-sen University

OTHER

Sponsor Role lead

Responsible Party

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Yanhong Deng

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Sixth Affiliated Hospital, Sun Yat-sen University

Guangzhou, Guangdong, China

Site Status

Countries

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China

Other Identifiers

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2023ZSLYEC-256

Identifier Type: -

Identifier Source: org_study_id

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