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PET/CT Based Radiomics for Lung Cancer (PERL)

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ClinicalTrials.gov Identifier: NCT03517306
Recruitment Status : Recruiting
First Posted : May 7, 2018
Last Update Posted : April 4, 2019
Sponsor:
Collaborators:
Beijing Chao Yang Hospital
General Hospital of Ningxia Medical University
Soochow University
First Affiliated Hospital of Wenzhou Medical University
Information provided by (Responsible Party):
Jianhua Yan, Second Affiliated Hospital of Wenzhou Medical University

Brief Summary:
The investigators investigate the utility of FDG PET/CT based radiomics in lung cancer, including diagnosis and prognosis.

Condition or disease Intervention/treatment
Lung Cancer Other: No Interventions

Detailed Description:

Recent studies have shown that, in addition to inter-tumor heterogeneity, tumors often display startling intratumoral heterogeneity in various features including histology, gene expression, genotype, and metastatic and proliferative potential, which is often associated with adverse tumor biology. Unfortunately, it is difficult to assess intratumoral heterogeneity with random sampling or biopsy as this does not represent the full extent of phenotypic or genetic variation within a tumor. Given the limitations of current biopsy strategies, there is an important potential for medical imaging, which has the ability to capture intratumoral heterogeneity in a non-invasive way.

Borrowed from the concept in genomics and/or proteomics, radiomics was specifically proposed for medical or radiological images. It is a promising technique for improving diagnosis, staging, prognosis, treatment response prediction and potentially allowing personalization of cancer treatment. It is a process of extraction and analysis of high-dimensional image features from radiological images obtained with CT, MR or PET, which could be either qualitative or quantitative. The basic assumption of radiomics is that tumor biology could be captured by radiomic features .

The purpose of this study is to investigate the utility of FDG PET/CT based radiomics in lung cancer. Four PET/CT centers will be involved in this study, in which more than 1000 patients diagnosed as lung cancer will be retrospectively enrolled.


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Study Type : Observational
Estimated Enrollment : 1500 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: PET/CTbased Radiomics for Lung Cancer (PERL): a Retrospective Multi-center Study
Actual Study Start Date : May 1, 2018
Estimated Primary Completion Date : May 31, 2019
Estimated Study Completion Date : September 28, 2019

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Lung Cancer

Group/Cohort Intervention/treatment
Beijing
No interventions
Other: No Interventions
No Interventions

Ningxia
No interventions
Other: No Interventions
No Interventions

Wenzhou
No interventions
Other: No Interventions
No Interventions

Changzhou
No interventions
Other: No Interventions
No Interventions




Primary Outcome Measures :
  1. Creation of a FDG PET/CT based radiomic score for survival [ Time Frame: Time Frame: 3 years ]
    Multiple quantitative radiomic features including SUV, metabolic volume, shape and texture will be measured from FDG PET/CT images. The all subjects will be randomly separated into a training and validation data. The multiple image features will be aggregated into a single combined radiomic score for survival with an appropriate machine learning method and the training data.


Secondary Outcome Measures :
  1. Validation of a FDG PET/CT based radiomic score for survival [ Time Frame: Time Frame: 3 years ]
    The created radiomic score developed in the primary outcome will be evaluated with the validation data in terms of survival(progress-free or overall survival)



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
All patients diagnosed as lung cancer patients who had a FDG PET/CT scan before treatment between 1 Jan, 2013 and 30 December, 2016 in the four collaborative hospitals.
Criteria

Inclusion Criteria:

- All patients diagnosed as lung cancer patients who had a FDG PET/CT scan before treatment between 1 Jan, 2013 and 30 December, 2016 in the four collaborative hospitals.

Exclusion Criteria:

- The patient without follow-up information


Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03517306


Locations
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China, Zhejiang
Second Affiliated Hospital of Wenzhou Medical University Recruiting
Wenzhou, Zhejiang, China, 325000
Contact: Jianhua Yan, PhD    86-15824497979    jianhua.yan@gmail.com   
Principal Investigator: Minfu Yang, MD         
Principal Investigator: Juan Li, MD         
Principal Investigator: Xiangwu Zheng, MD         
Principal Investigator: Yuetao Wang, MD         
Sponsors and Collaborators
Second Affiliated Hospital of Wenzhou Medical University
Beijing Chao Yang Hospital
General Hospital of Ningxia Medical University
Soochow University
First Affiliated Hospital of Wenzhou Medical University

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Responsible Party: Jianhua Yan, Professor, Second Affiliated Hospital of Wenzhou Medical University
ClinicalTrials.gov Identifier: NCT03517306     History of Changes
Other Study ID Numbers: SAHoWMU-CR2018-05-223
First Posted: May 7, 2018    Key Record Dates
Last Update Posted: April 4, 2019
Last Verified: April 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Plan Description: there is no plan to make individual participant data (IPD) available to other researchers.

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Jianhua Yan, Second Affiliated Hospital of Wenzhou Medical University:
lung cancer, FDG, PET/CT, radiomics

Additional relevant MeSH terms:
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Lung Neoplasms
Respiratory Tract Neoplasms
Thoracic Neoplasms
Neoplasms by Site
Neoplasms
Lung Diseases
Respiratory Tract Diseases