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NCT Number: NCT06536998

Exploring the Association of Imaging and Tumor Microenvironment in Liver Cancer Using Radiogenomic Approach（Radiogenomics-Liver）

This is the prospective, observational cohort study (Radiogenomics-Liver), which aims to explore the relationship between the imaging information of liver cancer patients, tumor microenvironment and the prognosis of liver cancer patients.

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Key information

Conditions

Liver Cancer Digestive System Diseases Digestive System Neoplasms Liver Diseases Liver Neoplasms Neoplasms Neoplasms by Site

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Union Hospital，Tongji Medical College，Huazhong University of Science and Technology

Wuhan, Hubei, 430000, China

Location status: Recruiting

Location contact

Lian Yang

CONTACT

[email protected]

18986273791

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Patients treated for liver cancer in Wuhan Union Hospital from August 2024 to August 2027;
  • Aged > 18 years old;
  • At least one CT scan or MRI scan before treatment;
  • Tissue biopsy pathological examination confirmed the diagnosis of the above tumors.

Exclusion criteria

：

  • Poor image quality;
  • Incomplete clinical data or loss of follow-up;
  • Presence of another primary malignancy other than liver cancer;
  • Unclear pathological diagnosis.

Treatment and study plan

Primary outcomes

  1. Correlation analysis of sequencing results and body composition

    Time frame: 0.5 year

    Conducting correlation analysis between body composition and results of multi-omics sequencing

  2. Correlation analysis of sequencing results and tumor radiomic features

    Time frame: 0.5 year

    Conducting correlation analysis between radiomic features and results of multi-omics sequencing

Secondary outcomes

  1. Constructing tumor microenvironment prediction model

    Time frame: 2 years

    Constructing radiomic model to predict tumor microenvironment. The indicator is the area under the curve (AUC) of the prediction model

  2. Constructing a multi-dimensional prognostic prediction model

    Time frame: 3 years

    A high-dimensional model was constructed to predict the prognosis of patients through multi-omics sequencing data, body composition, and tumor radiomic features. The indicator is the area under the curve (AUC) of the prediction model

Study contacts

Contact information is provided by the study sponsor or research team.

Lian Yang

CONTACT

[email protected]

18986273791

Sponsors and collaborators

Lead sponsor

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Other

Registry information

Important dates

Study start
2024
Primary completion
2027
Study completion
2027
First posted
Aug 5, 2024
Registry last updated
Aug 5, 2024

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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