Radiomics of Hepatocellular Carcinoma | NCT02757846

Studies
Radiomics of Hepatocellular Carcinoma

NCT02757846

Sponsor

Chinese Academy of Sciences

Status

Unknown status

Last Update Posted

May 2, 2016Estimated

Enrollment

1,200Estimated

Phase

Not provided

Conditions

Hepatocellular Carcinoma

Interventions

Not provided

Countries

China

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Apr 2016

Overall Recruitment Status or Expanded Access Status

Unknown status

Last Known Status

Enrolling by invitation

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Apr 2017

Primary Completion Date

Mar 2022Estimated

Completion Date

Mar 2022Estimated

First Submitted Date

Apr 28, 2016

First Submission Date that Met QC Criteria

Apr 28, 2016

First Posted Date

May 2, 2016Estimated

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Apr 28, 2016

Last Update Posted Date

May 2, 2016Estimated

Sponsor/Collaborators Module

Responsible Party, by Official Title

Chongwei Chi, Ph.D, Quantitative Imaging for Evaluation of Response to Cancer Therapies, Chinese Academy of SciencesPrincipal Investigator

Lead Sponsor

Chinese Academy of SciencesOTHER_GOV

Collaborators

Name	Class
Eastern Hepatobiliary Surgery Hospital	OTHER
Guangdong Provincial People's Hospital	OTHER
Henan Provincial People's Hospital	OTHER
West China Hospital

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Not provided

Is FDA Regulated Device

Not provided

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

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

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.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

1,200Estimated

Outcomes Module

Primary Outcomes

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

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

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

Exclusion Criteria:

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

Not provided

Maximum Age

Not provided

Standard Ages

ChildAdultOlder Adult

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).

Sampling Method

Probability Sample

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Name	Affiliation	Role
di dong, PhD	Chinese Academy of Sciences	Study Director

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Key Laboratory of Molecular Imaging, Chinese Academy of Sciences		Beijing	Beijing Municipality	100190	China

References Module

Citations

PubMed Identifier	Type	Citation	Retractions
26221705	Background	Shen W, Zhou M, Yang F, Yang C, Tian J. Multi-scale Convolutional Neural Networks for Lung Nodule Classification. Inf Process Med Imaging. 2015;24:588-99. doi: 10.1007/978-3-319-19992-4_46.
20427518	Background	Wilkerson MD, Hayes DN. ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics. 2010 Jun 15;26(12):1572-3. doi: 10.1093/bioinformatics/btq170. Epub 2010 Apr 28.

ID	Term
D000230	Adenocarcinoma
D002277	Carcinoma
D009375	Neoplasms, Glandular and Epithelial
D009370	Neoplasms by Histologic Type