D-Lung: An Analytics Platform for Lung Cancer Based on Deep Learning Technology
1 other identifier
observational
130
1 country
1
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for all trials
Started Jul 2018
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
July 1, 2018
CompletedFirst Submitted
Initial submission to the registry
July 26, 2019
CompletedFirst Posted
Study publicly available on registry
July 30, 2019
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 30, 2020
CompletedStudy Completion
Last participant's last visit for all outcomes
June 30, 2020
CompletedFebruary 8, 2023
February 1, 2023
2 years
July 26, 2019
February 7, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (4)
accuracy
proportion of true results(both true positives and true negatives) among whole instances
2 years
sensitivity
true positive rate in percentage(%) derived by ROC analysis
2 years
specificity
true negative rate in percentage (%) derived by ROC analysis
2 years
area under curve (AUC)
area under ROC curve in percentage (%)
2 years
Secondary Outcomes (2)
average number of false positives per scan (FPs/scan)
2 years
competition performance metric (CPM)
2 years
Interventions
thoracic CT examinations for diagnosis, and/or follow-up.
Eligibility Criteria
This is a single institutional retrospective cohort study of patients within hospitals in Hong Kong, who had undergone thoracic CT for suspicious lung nodules.
You may qualify if:
- Subjects with suspicious lung nodules.
- Thin-layer thoracic CT and pathology examination have been performed for suspicious lung nodules.
You may not qualify if:
- Subjects with accompanied lesions on CT images that may interfere to lung nodules analysis
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
The Chinese University of Hong Kong, Prince of Wale Hospital
Hong Kong, Shatin, Hong Kong
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- CASE ONLY
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor
Study Record Dates
First Submitted
July 26, 2019
First Posted
July 30, 2019
Study Start
July 1, 2018
Primary Completion
June 30, 2020
Study Completion
June 30, 2020
Last Updated
February 8, 2023
Record last verified: 2023-02
Data Sharing
- IPD Sharing
- Will not share