Clinical trial NCT02757846: Radiomics of Hepatocellular Carcinoma
Official title: Quantitative Imaging for Evaluation of Response to Cancer Therapies
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Hepatocellular Carcinoma
Keywords: Radiomics
prognosis
medical images
Hepatocellular carcinoma
Lead sponsor: Chinese Academy of Sciences
Sponsor class: OTHER_GOV
Collaborators: name: Eastern Hepatobiliary Surgery Hospital
name: Guangdong Provincial People's Hospital
name: Henan Provincial People's Hospital
name: West China Hospital
name: Peking Union Medical College Hospital
First posted: 2016-05-02
Enrollment: 1200
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
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).

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.

Eligibility criteria: Inclusion Criteria:

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

Exclusion Criteria:

-

Primary outcomes:
measure: quantitative image features extracted from CT images can be used as imaging marker for prognosis
timeFrame: five(year)
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Key Laboratory of Molecular Imaging, Chinese Academy of Sciences
state: Beijing
Study officials:
affiliation: Chinese Academy of Sciences
name: di dong, PhD
role: STUDY_DIRECTOR
References:
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