Artificially Intelligent Model for Accurate Detection of HCC

NCT06637059 | Completed DMC

• 1 other identifier: MMFAIHCC
• Study Type: observational
• Target: 1,092
• Locations: 1 country
• Sites: 1

Brief Summary

Purpose: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. The investigators aimed to develop a model with multi-modal features (MMF) using artificial intelligence (AI) approaches to enhance the performance of HCC detection. Experimental Design: A total of 1,092 participants were enrolled from 16 centers. These participants were allocated into the training, internal validation, and external validation cohorts. Peripheral blood specimens were collected prospectively and subjected to mass cytometry analysis. Clinical and radiological data were obtained from electrical medical records. Various AI methods were employed to identify pertinent features and construct single-modal models with optimal performance. The XGBoost algorithm was utilized to amalgamate these models, integrating multi-modal information and facilitating the development of a fusion model. Model evaluation and interpretability were demonstrated using the SHapley Additive exPlanations method.

Conditions

Hepatocellular Carcinoma (HCC)

Keywords

Hepatocellular carcinoma; Early detection; Multi-modal; Fusion model; Artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Diagnosis of liver disease through CT imaging

  1 month

Study Arms (3)

Training cohort

Other: observational study

Internal validation cohort

Other: observational study

External validation cohort

Other: observational study

Interventions

observational study OTHER

observation alone

External validation cohort; Internal validation cohort; Training cohort

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Benign liver diseases, including but not limited to, hemangiomas, hepatic cysts, focal nodular hyperplasia, and cirrhosis were considered in this study. Participants who had undergone previous treatment for HCC or benign liver diseases, those who had taken medications affecting the hematological system within 2 weeks, or those who had received a blood transfusion within 6 months were excluded from the study.

You may qualify if:

• Benign liver diseases, including but not limited to, hemangiomas, hepatic cysts, focal nodular hyperplasia, and cirrhosis

You may not qualify if:

• Participants who had undergone previous treatment for HCC or benign liver diseases,
• had taken medications affecting the hematological system within 2 weeks
• those who had received a blood transfusion within 6 months

Sponsors & Collaborators

• Zhejiang University: lead

Study Sites (1)

Unknown Facility

Hangzhou, Zhejiang, 310003, China

Location

MeSH Terms

Conditions

Carcinoma, Hepatocellular

Interventions

Observation

Condition Hierarchy (Ancestors)

Adenocarcinoma; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Liver Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Digestive System Diseases; Liver Diseases

Intervention Hierarchy (Ancestors)

Methods; Investigative Techniques

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: October 5, 2024
• First Posted: October 15, 2024
• Study Start: January 1, 2024
• Primary Completion: October 1, 2024
• Study Completion: October 1, 2024
• Last Updated: October 15, 2024

Record last verified: 2024-10

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)