Radiomics of Hepatocellular Carcinoma

April 28, 2016 updated by: Chongwei Chi, Ph.D, Chinese Academy of Sciences

Quantitative Imaging for Evaluation of Response to Cancer Therapies

We propose a radiomics approach to identify prognostic biomarkers of HCC and provide patients with some reasonable advice for their therapies.

Study Overview

Status

Unknown

Conditions

Detailed Description

Radiomics is emerging fields that is based on quantitative analysis of medical images. Tri-phasic CT images are currently the standard imaging modality for the management of HCC. Our goal is to improve treatment decisions of HCC patients through better understanding of their prognosis based on radiomics modeling of HCC. Radiomics is defined as the extraction of quantitative image features from medical images. We will use triphasic CT data of at least 200 patients and develop a robust strategy to extract imaging features from CT. We will use deep learning in the form of a Convolutional Neural Network to segment HCC lesions and use image feature extraction algorithms with supervised classification to predict prognosis.

Study Type

Observational

Enrollment (Anticipated)

1200

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Beijing
      • Beijing, Beijing, China, 100190
        • Key Laboratory of Molecular Imaging, Chinese Academy of Sciences

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • ADULT
  • OLDER_ADULT
  • CHILD

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Currently, a cohort of 20 patients has already been collected from the collaborating hospitals. Next, the 5 hospitals will collect at least 1200 patients within 1-2 years and up to 6000 patients during the full course of the project (5 years).

Description

Inclusion Criteria:

  • The purpuse of our research is to improve treatment ,therefore we have no creteria.

Exclusion Criteria:

-

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
quantitative image features extracted from CT images can be used as imaging marker for prognosis
Time Frame: five(year)
five(year)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Chinese Academy of Sciences

Collaborators

Peking Union Medical College Hospital
West China Hospital
Guangdong Provincial People's Hospital
Henan Provincial People's Hospital
Eastern Hepatobiliary Surgery Hospital

Investigators

  • Study Director: di dong, PhD, Chinese Academy of Sciences

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

April 1, 2017

Primary Completion (ANTICIPATED)

March 1, 2022

Study Completion (ANTICIPATED)

March 1, 2022

Study Registration Dates

First Submitted

April 28, 2016

First Submitted That Met QC Criteria

April 28, 2016

First Posted (ESTIMATE)

May 2, 2016

Study Record Updates

Last Update Posted (ESTIMATE)

May 2, 2016

Last Update Submitted That Met QC Criteria

April 28, 2016

Last Verified

April 1, 2016

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 20160427ABCD

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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