Radiomics of Hepatocellular Carcinoma

NCT02757846 | Unknown

• 1 other identifier: 20160427ABCD
• Study Type: observational
• Target: 1,200
• Locations: 1 country
• Sites: 1

Brief Summary

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

Conditions

Hepatocellular Carcinoma

Keywords

Radiomics; prognosis; medical images; Hepatocellular carcinoma

Outcome Measures

Primary Outcomes (1)

• quantitative image features extracted from CT images can be used as imaging marker for prognosis

  five(year)

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• 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).

You may qualify if:

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

Sponsors & Collaborators

• Chinese Academy of Sciences: lead
• Eastern Hepatobiliary Surgery Hospital: collaborator
• Guangdong Provincial People's Hospital: collaborator
• Henan Provincial People's Hospital: collaborator
• West China Hospital: collaborator
• Peking Union Medical College Hospital: collaborator

Study Sites (1)

Key Laboratory of Molecular Imaging, Chinese Academy of Sciences

Beijing, Beijing Municipality, 100190, China

Location

Related Publications (5)

• 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.

  PMID: 26221705 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.

  PMID: 20427518 BACKGROUND

• Sanson M, Marie Y, Paris S, Idbaih A, Laffaire J, Ducray F, El Hallani S, Boisselier B, Mokhtari K, Hoang-Xuan K, Delattre JY. Isocitrate dehydrogenase 1 codon 132 mutation is an important prognostic biomarker in gliomas. J Clin Oncol. 2009 Sep 1;27(25):4150-4. doi: 10.1200/JCO.2009.21.9832. Epub 2009 Jul 27.

  PMID: 19636000 BACKGROUND

• Cui Y, Jia J. Update on epidemiology of hepatitis B and C in China. J Gastroenterol Hepatol. 2013 Aug;28 Suppl 1:7-10. doi: 10.1111/jgh.12220.

  PMID: 23855289 BACKGROUND

• Zhu F, Shi Z, Qin C, Tao L, Liu X, Xu F, Zhang L, Song Y, Liu X, Zhang J, Han B, Zhang P, Chen Y. Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res. 2012 Jan;40(Database issue):D1128-36. doi: 10.1093/nar/gkr797. Epub 2011 Sep 24.

  PMID: 21948793 BACKGROUND

Related Links

• A Website from Key Laboratory of Molecular Imaging, Chinese Academy of Sciences

MeSH Terms

Conditions

Carcinoma, Hepatocellular

Condition Hierarchy (Ancestors)

Adenocarcinoma; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Liver Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Digestive System Diseases; Liver Diseases

Study Officials

• di dong, PhD

  Chinese Academy of Sciences

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Quantitative Imaging for Evaluation of Response to Cancer Therapies

Study Record Dates

• First Submitted: April 28, 2016
• First Posted: May 2, 2016
• Study Start: April 1, 2017
• Primary Completion: March 1, 2022
• Study Completion: March 1, 2022
• Last Updated: May 2, 2016

Record last verified: 2016-04

Locations

CN (1)