D-Lung: An Analytics Platform for Lung Cancer Based on Deep Learning Technology

Completed

• Conditions: Lung Cancer

• Registration Number: NCT04036903
• Lead Sponsor: Chinese University of Hong Kong

Brief Summary

Lung cancer is one of main cause of cancer death in worldwide, characterized of low 5-year survival rate of less than 20%. Pulmonary nodule is considered as the typical imaging manifestation in early stage of lung cancer. The National Lung Screen Trial has demonstrated that the mortality rates could decline greatly, by the utility of low-dose helical computed tomography for screen of pulmonary nodules. Thus, automatic detection, diagnosis and management of pulmonary nodules, play the vital roles in computer-aided lung cancer screening and early intervention.

Detailed Description

Not available

Study Timeline

• Study Start: 2018-07-01
• Study First Submitted: 2019-07-26
• Study First Submitted QC: 2019-07-26
• Study First Posted: 2019-07-30
• Primary Completion: 2020-06-30
• Study Completion: 2020-06-30
• Status Verified: 2023-02
• Last Update Submitted: 2023-02-07
• Last Update Posted: 2023-02-08

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 130

Inclusion Criteria

• Subjects with suspicious lung nodules.
• Thin-layer thoracic CT and pathology examination have been performed for suspicious lung nodules.

Exclusion Criteria

• Subjects with accompanied lesions on CT images that may interfere to lung nodules analysis

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
accuracy	2 years	proportion of true results(both true positives and true negatives) among whole instances
sensitivity	2 years	true positive rate in percentage(%) derived by ROC analysis
specificity	2 years	true negative rate in percentage (%) derived by ROC analysis
area under curve (AUC)	2 years	area under ROC curve in percentage (%)

Secondary Outcome Measures

Name	Time	Method
average number of false positives per scan (FPs/scan)	2 years	FPs/scan in number (N) based on free-response receiver operating characteristic (FROC) analysis
competition performance metric (CPM)	2 years	Competitive performance metric (CPM) is a criterion used for CAD system evaluation. Based on FROC paradigm, CPM score is computed as an average sensitivity at seven predefined average false positive rates. CPM score ranges from 0 to 1, with higher CPM score indicating better CAD performance.

Trial Locations

Locations (1)

The Chinese University of Hong Kong, Prince of Wale Hospital; 🇭🇰 Hong Kong, Shatin, Hong Kong