null - FindTrial

A Radiogenomics biomarker for predicting mutation sutatus and gene expresioon in hepatocellular carcinoma

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-jRCT1070230032

Enrollment

200

Registered

2023-06-27

Start date

2023-05-08

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hepatocellular Carcinoma Radiogenomics Artificial Intelligence

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: 1. Diagnosed as HCC, and undergone surgery without any systemic therapy from April 2019 to April 2023 in Kurume univesity 2. Availabirity of contrast-enhanced CT images within 12 weeks before surgery and tumor tissue storage in Kurume university 3.Acquired informed consent form about use of tumor tissue before surgery in Kurume university

Exclusion criteria

Exclusion criteria: Not applicable participants determined by an investigator

Design outcomes

Primary

Measure	Time frame
Evaluation of machine learning model for predicting B-catenin mutation from image features	—

Secondary

Measure	Time frame
Evaluation of machine learning model for predicting p53 mutation from image features Evaluation of machine learning model for predicting TERT mutation from image features	—

Contacts

Public ContactHideki Iwamoto

Kurume University School of Medicine

iwamoto_hideki@med.kurume-u.ac.jp+81-942-31-7561

Outcome results