Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical N0 Lung Cancer
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
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Locations
-
-
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
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
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
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Prospective
What is the study measuring?
Primary Outcome Measures
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
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
Sponsor
Sponsor
Collaborators
Collaborators
Study record dates
Study Major Dates
Study Start (ACTUAL)
Study Start
Primary Completion (ANTICIPATED)
Primary Completion
Study Completion (ANTICIPATED)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (ACTUAL)
First Posted
Study Record Updates
Last Update Posted (ESTIMATE)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- DLNMS
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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