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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

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

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
CRIS
Registry ID
KCT0005065
Enrollment
855
Registered
2020-05-28
Start date
2019-06-10
Completion date
Unknown
Last updated
2020-06-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

Medical Device : Upload the subject&#39
s chest CT images to the investigational device (VUNO Med - Lung CAD software) to identify the possibility of pulmonary nodules.

Sponsors

Vuno
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 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

Exclusion criteria

Exclusion criteria: 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

Design outcomes

Primary

MeasureTime frame
Per lesion sensitivity

Secondary

MeasureTime frame
Per patient sensitivity;Per patient specificity;Per patient false positive;Per patient false negative;Per lesion false negative

Countries

Korea, Republic of

Contacts

Public Contactsangmin lee

Asan Medical Center

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026