PET/CT Based Radiomics for Lung Cancer (PERL)

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

Detailed Description
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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.

Official Title
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PET/CTbased Radiomics for Lung Cancer (PERL): a Retrospective Multi-center Study

Conditions
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Lung Cancer

Intervention / Treatment
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* Other: No Interventions


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Beijing<br>No interventions | Other: No Interventions<br>* No Interventions<br>|
| Ningxia<br>No interventions | Other: No Interventions<br>* No Interventions<br>|
| Wenzhou<br>No interventions | Other: No Interventions<br>* No Interventions<br>|
| Changzhou<br>No interventions | Other: No Interventions<br>* No Interventions<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Creation of a FDG PET/CT based radiomic score for survival | 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. | Time Frame: 3 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Validation of a FDG PET/CT based radiomic score for survival | 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) | Time Frame: 3 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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lung cancer, FDG, PET/CT, radiomics