Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical N0 Lung Cancer

February 7, 2023 updated by: Chang Chen, Shanghai Pulmonary Hospital, Shanghai, China

PET/CT-based Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical Stage N0 Non-Small Cell Lung Cancer: A Multicenter Prospective Diagnostic Trial

The purpose of this study is to evaluate the performance of a PET/CT-based deep learning signature for predicting occult nodal metastasis of clinical stage N0 non-small cell lung cancer in a multicenter prospective cohort.

Study Overview

Status

Recruiting

Conditions

Non-small Cell Lung Cancer

Intervention / Treatment

Diagnostic test: PET/CT-based Deep Learning Signature

Study Type

Observational

Enrollment (Anticipated)

5000

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
- Jiangxi
  - Nanchang, Jiangxi, China
    - Recruiting
    - The First Affiliated Hospital of Nanchang University
- Shanghai
  - Yangpu, Shanghai, China
    - Recruiting
    - Shanghai Pulmonary Hospital
- Zhejiang
  - Ningbo, Zhejiang, China
    - Recruiting
    - Ningbo HwaMei Hospital

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

N/A

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Clinica N0 Non-small Cell Lung Cancer

Description

Inclusion Criteria:

(1) Participants scheduled for surgery for radiological finding of pulmonary lesions from the preoperative thin-section CT scans; (2) The maximum short-axis diameter of N1 and N2 lymph nodes less than 1 cm on CT scan; (3) The SUVmax of N1 and N2 lymph nodes less than 2.5; (4) Pathological confirmation of primary NSCLC; (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) Participants not receiving systematic lymph node dissection; (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

Observational Models: Cohort
Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Area under the receiver operating characteristic curve Time Frame: 2022.1-2023.12	Area under the receiver operating characteristic curve	2022.1-2023.12

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity Sensitivity Time Frame: 2022.1-2023.12	Sensitivity	2022.1-2023.12
Specificity Time Frame: 2022.1-2023.12	Specificity	2022.1-2023.12
Positive predictive value Time Frame: 2022.1-2023.12	Positive predictive value	2022.1-2023.12
Negative predictive value Time Frame: 2022.1-2023.12	Negative predictive value	2022.1-2023.12
Accuracy Time Frame: 2022.1-2023.12	Accuracy	2022.1-2023.12

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)

January 1, 2022

Primary Completion (ANTICIPATED)

December 31, 2023

Study Completion (ANTICIPATED)

December 31, 2023

Study Registration Dates

First Submitted

June 15, 2022

First Submitted That Met QC Criteria