A multi-center, retrospective pivotal trial to evaluate the efficacy of artificial intelligence-based pulmonary nodule detection software ‘VUNO Med – Lung CAD’ in thoracic CT
- Conditions
- Diseases of th respiratory system
- Registration Number
- KCT0005065
- Lead Sponsor
- Vuno
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Completed
- Sex
- All
- Target Recruitment
- 855
1) Adults at the age 19 or above who had a thoracic CT scan within the period from Jan 2012 to Jun 2018
2) Patients whose thoracic CT scan showed no or 1 to 5 pulmonary nodules with the long-axis diameter from 4 mm to 30 mm
1) Women who was pregnant or breast-feeding on the date of the thoracic CT scan
2) Patients who had been diagnosed with cancers other than lung cancer within 5 years
3) Patients who had any of following medical records:
?-Severe pulmonary fibrosis
?-Diffuse bronchiectasis
?-Extensive pulmonary consolidation
?-Massive pleural effusion
?-Active or latent tuberculosis
4) Patients whose thoracic CT scans difficult to be read due to any reasons described as below:
?-Images not fully showing regions of interest (e.g., when it is unable to see both lungs, when at least one slice above lung apex and both adrenal glands are not included.)
?-Images with a severe artifact due to the patient movement or technical problems
?-Images of slice thickness exceeded 5 mm
?-Images with interslice gaps
?-Images not using standard reconstruction kernel
?- Images that structures of lung and mediastinum are not fully evaluated due to poor resolution
5) Patients who are otherwise considered to be not suitable for participating in the study by the investigator
Study & Design
- Study Type
- Interventional Study
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Per lesion sensitivity
- Secondary Outcome Measures
Name Time Method Per patient sensitivity;Per patient specificity;Per patient false positive;Per patient false negative;Per lesion false negative