Identification of Image Phenotypes to Predict Recurrence After Resection of Hepatocellular Carcinoma (LIVERIBIOPSY)

Tumor recurrence, which occurs in 70% of patients with HCC within 5 years after hepatic resection, is a major cause of post-resection-death. This recurrence can be true recurrence (intrahepatic metastases), which occurs sooner than 2 years later, or it can be due to the development of de-novo tumors at least 2 years later. Despite this high rate of tumor recurrence, no anti-recurrence adjuvant therapies are currently recommended.

Imaging phenomics is the systematic, large scale extraction of imaging features for the characterization and classification of disease phenotypes. Combining imaging and tissue phenomics could be a solution to predict HCC recurrence. With the emergence of molecular therapies and immunotherapies, identifying patients with HCC at high risk of post-resection recurrence would help determine additional therapeutic and management strategies in clinical practice.

Study Overview

• Status: Completed
• Conditions: CT Scans Prior to Surgery With a Least 2 Years of Follow-up
• Intervention / Treatment: Other: Non intervention

Detailed Description

Hepatocellular carcinoma (HCC) is among the most lethal and prevalent cancers in the human population and it is now the third leading cause of cancer deaths worldwide, with over 500,000 people affected. Because of the high recurrence rate after curative hepatectomy, accurate prognostic assessment in HCC patients are quite important. With the emergence of molecular therapies and immunotherapies, the identification of patients at high or low risk for recurrence after hepatic resection would help determine additional therapeutic and management strategies in clinical practice. Although many immunohistochemical markers have been reported to have a prognostic value for HCC patients, there is no consensus on how these markers could add prognostic value to the clinical parameters.

In the initial step of biomarker discovery, no specific sample size is provided, however to test hypothesis, 100 patients are required.

This first study will potentially be followed by a second similar study promoted by the same investigators to increase the statistical power to improve the classification tool according to the patient's future.

Period covered by the data collection: 2011-2019 / Duration data collection: 1 year.

The primary endpoint will be built using machine learning method to obtain prediction of recurrence within 2 years. The Recurrence Free survival (RFS) within two years will be the reference outcome to evaluate the prognostic of the patients.

The secondary endpoint are following :

- A secondary endpoint which will be built using machine learning method to obtain prediction of recurrence after 2 years.

The Recurrence Free survival (RFS) after two years will be the reference outcome to evaluate the prognostic of the patients.

- A secondary endpoint will be the correlation between biomarker from CT scan and pathological biomarkers As the spectrum of HCC disease is very large, many patients to conduct conclusive validation studies for diagnostic and prognostic relevance need to be obtained.

Overall, each specific-read out endpoint will include a sample size calculation and - if appropriate - a power analysis specific to the objective of this study.

During training, phenotyping system performance assessment will be done to guide the calculation of the sample size for the validation.

• Study Type: Observational
• Enrollment (Actual): 100

Contacts and Locations

Study Locations

• France
  • Villejuif, France, 94800
    • Paul Brousse Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Data of patients who has hepatectomy (resection R0) for an HCC treatment will be collected from January 2011 to December 2019.

Description

Inclusion Criteria:

• Age ≥ 18 years old
• Patients who underwent surgery and have R0 resection after 2010
• Multiphase CT scans with contrast media should be performed within 2 months prior to surgical intervention
• At least 2 years of follow-up data on intrahepatic recurrence

Exclusion Criteria:

• Previous HCC treatment
• Combination of other anti-cancer treatment
• Other malignancies
• Patient expressly expressing opposition to the exploitation of their data as defined by the project
• Protected adults

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The main objective of this work is to identify biomarkers from CT scan (non-invasive imaging phenotypes from radiological images) which have a prognostic value for an early recurrence in patients with hepatocellular cancer.	The primary endpoint will be built using machine learning method to obtain prediction of recurrence within 2 years. The Recurrence Free survival (RFS) within two years will be the reference outcome to evaluate the prognostic of the patients.	2 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identify biomarkers from CT scan (non-invasive imaging phenotypes from radiological images) which have a prognostic value for a tardive recurrence in patients with hepatocellular cancer.	A secondary endpoint which will be built using machine learning method to obtain prediction of recurrence after 2 years. The Recurrence Free survival (RFS) after two years will be the reference outcome to evaluate the prognostic of the patients.	2 years

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
To correlate the imaging signatures predictive of recurrence with the cell population molding of tissue microenvironment (TME) and the tumor biology using tissue assessment as reference.	Correlation between biomarker from CT scan and nodule size, nodule differentiation (grade OMS), nodule capsule, macroscopie invasion, microscopic vascular invasion, macrotrabecular sub-type, satellite nodule, staging.	1 year

Collaborators and Investigators

• Sponsor: Assistance Publique - Hôpitaux de Paris
• Collaborators: Median Technologies
• Investigators: Principal Investigator: Maïté LEWIN, Professor, Paul Brousse Hospital

Study record dates

Study Major Dates

• Study Start (Actual): January 28, 2021
• Primary Completion (Actual): January 28, 2022
• Study Completion (Actual): February 9, 2022

Study Registration Dates

• First Submitted: December 20, 2021
• First Submitted That Met QC Criteria: February 10, 2022
• First Posted (Actual): February 11, 2022

Study Record Updates

• Last Update Posted (Actual): February 11, 2022
• Last Update Submitted That Met QC Criteria: February 10, 2022
• Last Verified: February 1, 2022

More Information

Terms related to this study

• Keywords: Hepatocellular Carcinoma; Prognostic value; Hepatic resection; Biomarkers from CT scan; Early recurrence with hepatocellular cancer patients
• Additional Relevant MeSH Terms: Digestive System Diseases; Pathologic Processes; Neoplasms by Histologic Type; Neoplasms; Neoplasms by Site; Adenocarcinoma; Neoplasms, Glandular and Epithelial; Disease Attributes; Digestive System Neoplasms; Liver Diseases; Liver Neoplasms; Carcinoma; Carcinoma, Hepatocellular; Recurrence
• Other Study ID Numbers: APHP191113

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No