Influence of PET/CT Radiomic Features on the Outcome of Lung Cancer Patients

July 22, 2020 updated by: Hongwei Si, The First Affiliated Hospital of Shanxi Medical University
Radiomics is an attractive field in objectively quantifying image features, and may overcome the subjectivity of visually interpreting computed tomography (CT), or positron emission tomography (PET). It is reported that the features related to treatment response, outcomes, tumor staging, tissue identification, and cancer genetics. Therefore, the investigators try to explore the key features for the outcome of lung cancer patients.

Study Overview

Status

Completed

Conditions

Detailed Description

Radiomic Features:

PET/CT images, including other kinds of CT serials, were transported into a personal computer. Using the open source software of 3D-Slicer, volumes of interest (VOIs) for primary tumor, or even lymph nodes, was semi-automatically or manually segmented. And then, radiomic features were extracted.

PET Parameters:

Using combined CT VOIs, corresponding PET standard uptake value (SUV, no unit) were measured. For a foci (either tumor, or lymph node), mean, sum and maximum SUV were documented, and were used for training and validating models alongside radiomic features.

Feature Selection:

Data were analyzed by deep learning or random forests method, and top 20 variables were scored by their contribution to the regression (variable importance, VIMP). The generalized features were identified as the same ones between two kinds of image serials (for example, ordinary and thin-section CT, or PET and CT). Additionally, when three or more features met the criterion, a lower value of Akaike information criterion (AIC) which measures the relative quality of statistical models was used to find appropriate features with lower overfitting possibility.

Model Validation:

The developed model was validated internally and externally. The internal indices for independent continuous variable were accuracy (bias and absolute bias) and precision (correlation coefficient and R square), and that for independent classified or survival variable was c-index. The patients enrolled from another medical center were used for external validation.

Study Type

Observational

Enrollment (Actual)

1000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Anhui
      • Hefei, Anhui, China, 230022
        • First Affiliated Hospital of Anhui Medical University
    • Shanxi
      • Taiyuan, Shanxi, China, 030001
        • First Affiliated Hospital of Shanxi Medical University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

lung caner

Description

Inclusion Criteria:

  1. Pathologically diagnosed as lung caner.
  2. Accepted PET/CT scans at the hospitals either affiliated to Shanxi Medical University or Anhui Medical University
  3. Both PET and CT serials can be obtained
  4. Can be followed for treatment modalities (including chemotherapy regimens, radiotherapy dose, and et al), survival time and status, and other related information.

Exclusion Criteria:

  1. Simultaneously suffering from the cancers from other tissues and organs
  2. Have a history of diabetes, chronic heart diseases, or chronic renal failure

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Overall survival (OS) of lung cancer patients
Time Frame: The patients were followed to December 31, 2019
The time from the scan date to death for any reason
The patients were followed to December 31, 2019

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

The First Affiliated Hospital of Shanxi Medical University

Collaborators

The First Affiliated Hospital of Anhui Medical University

Investigators

  • Study Chair: Li Sijin, MD, First Affiliated Hospital of Shanxi Medical University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2010

Primary Completion (Actual)

December 31, 2019

Study Completion (Actual)

December 31, 2019

Study Registration Dates

First Submitted

August 21, 2018

First Submitted That Met QC Criteria

August 23, 2018

First Posted (Actual)

August 27, 2018

Study Record Updates

Last Update Posted (Actual)

July 23, 2020

Last Update Submitted That Met QC Criteria

July 22, 2020

Last Verified

July 1, 2020

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 20170501

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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