Deep Learning Signature for Predicting the Novel Grading System of Clinical Stage I Lung Adenocarcinoma

February 12, 2023 updated by: Chang Chen, Shanghai Pulmonary Hospital, Shanghai, China

Deep Learning Signature Based on PET-CT Images for Predicting the Novel Grading System of Clinical Stage I Lung Adenocarcinoma

The purpose of this study is to evaluate the performance of a PET/ CT-based deep learning signature for predicting the grade 3 tumors based on the novel grading system in clinical stage stage I lung adenocarcinoma based on a multicenter prospective cohort.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Anticipated)

600

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
    • Guizhou
      • Zunyi, Guizhou, China
        • Recruiting
        • Affiliated Hospital of Zunyi Medical University
        • Contact:
    • Jiangxi
      • Nanchang, Jiangxi, China
        • Recruiting
        • The First Affiliated Hospital of Nanchang University
        • Contact:
    • Shanghai
      • Yangpu, Shanghai, China
        • Recruiting
        • Shanghai Pulmonary Hospital
    • Zhejiang
      • Ningbo, Zhejiang, China
        • Recruiting
        • Ningbo HwaMei Hospital
        • Contact:

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

20 years to 75 years (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Clinical Stage I Lung Adenocarcinoma

Description

Inclusion Criteria:

(1) Participants scheduled for surgery for radiological finding of pulmonary lesions from the preoperative thin-section CT scans; (2) The maximum diameter of lesion less than 4 cm on CT scans; (3) The maximum short axis diameter of lymph nodes less than 1 cm on CT scan; (4) The SUVmax of hilar and mediastinal lymph nodes less than 2.5; (5) Pathological confirmation of primary lung adenocarcinoma; (5) Age ranging from 20-75 years; (6) Obtained written informed consent.

Exclusion Criteria:

(1) Multiple lung lesions; (2) Poor quality of PET-CT images; (3) Participants with incomplete clinical information; (4) Mucinous adenocarcinomas; (5) Participants who have received neoadjuvant therapy.

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
Area under the receiver operating characteristic curve
Time Frame: 2022.11-2023.4
Area under the receiver operating characteristic curve
2022.11-2023.4

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Sensitivity
Time Frame: 2022.11-2023.4
Sensitivity
2022.11-2023.4
Specificity
Time Frame: 2022.11-2023.4
Specificity
2022.11-2023.4
Positive predictive value
Time Frame: 2022.11-2023.4
Positive predictive value
2022.11-2023.4
Negative predictive value
Time Frame: 2022.11-2023.4
Negative predictive value
2022.11-2023.4
Accuracy
Time Frame: 2022.11-2023.4
Accuracy
2022.11-2023.4

Collaborators and Investigators

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

Sponsor

Shanghai Pulmonary Hospital, Shanghai, China

Collaborators

Zunyi Medical College
Ningbo HwaMei Hospital, Zhejiang, China
The First Affiliated Hospital of Nanchang University, Jiangxi, China

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)

November 1, 2022

Primary Completion (Anticipated)

April 30, 2023

Study Completion (Anticipated)

April 30, 2023

Study Registration Dates

First Submitted

February 7, 2023

First Submitted That Met QC Criteria

February 12, 2023

First Posted (Estimate)

February 21, 2023

Study Record Updates

Last Update Posted (Estimate)

February 21, 2023

Last Update Submitted That Met QC Criteria

February 12, 2023

Last Verified

February 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • DLGS

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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