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

Non-small Cell Lung Cancer Clinical Trial

Official title:

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

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05425134
• Other study ID #: DLNMS
• Status: Recruiting
• Start date: January 1, 2022
• Est. completion date: December 31, 2023

Study information

• Verified date: February 2023
• Source: Shanghai Pulmonary Hospital, Shanghai, China
• Contact: Chang Chen, MD, PhD
• Phone: +86-021-65115006
• Email: chenthoracic[@]163.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 5000
• Est. completion date: December 31, 2023
• Est. primary completion date: December 31, 2023
• Gender: All
• Age group: 20 Years to 75 Years

Eligibility

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.

Related Conditions & MeSH terms

• Carcinoma, Non-Small-Cell Lung
• Lung Neoplasms
• Neoplasm Metastasis
• Non-small Cell Lung Cancer

Intervention

Diagnostic Test:
• PET/CT-based Deep Learning Signature
Deep Learning Signature Based on PET-CT for Predicting Occult Nodal Metastasis of Clinical N0 Non-small Cell Lung Cancer

Locations

Country	Name	City	State
China	The First Affiliated Hospital of Nanchang University	Nanchang	Jiangxi
China	Ningbo HwaMei Hospital	Ningbo	Zhejiang
China	Shanghai Pulmonary Hospital	Yangpu	Shanghai
China	Affiliated Hospital of Zunyi Medical University	Zunyi	Guizhou

Sponsors (4)

Lead Sponsor	Collaborator
Shanghai Pulmonary Hospital, Shanghai, China	Ningbo HwaMei Hospital, Zhejiang, China, The First Affiliated Hospital of Nanchang University, Jiangxi, China, Zunyi Medical College

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Area under the receiver operating characteristic curve	Area under the receiver operating characteristic curve	2022.1-2023.12
Secondary	Sensitivity Sensitivity	Sensitivity	2022.1-2023.12
Secondary	Specificity	Specificity	2022.1-2023.12
Secondary	Positive predictive value	Positive predictive value	2022.1-2023.12
Secondary	Negative predictive value	Negative predictive value	2022.1-2023.12
Secondary	Accuracy	Accuracy	2022.1-2023.12