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A blinded, self-control trial to evaluate an AI based CAD system for Lung Nodule Diagnosis

A blinded, self-control trial to evaluate an AI based CAD system for Lung Nodule Diagnosis

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000029278
Enrollment
Unknown
Registered
2020-01-20
Start date
2019-08-07
Completion date
Unknown
Last updated
2020-02-03

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

Conditions

Lung Nodule

Interventions

Gold Standard:CT image evaluation by clinicians
Index test:CT&#32
image&#32
evaluation&#32
with&#32
CAD

Sponsors

Shanghai General Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. Lung CT images in Dicom Format; 2. Images cover the whole lung, from pulmonary apex to diagram; 3. Image thickness =2.5mm; 4. Images from a lung CT screening program; 5. complete patient identification information.

Exclusion criteria

Exclusion criteria: 1. Lung CT images with no lung nodule; 2. incomplete patient identification information; 3. Images that can not be imported to an image workstation; 4. Severe image artifacts due to metal implants or other reason; 5. Images with significant morphological changes other than lung nodule.

Design outcomes

Primary

MeasureTime frame
sensitivity;False Positive Rate;—

Countries

China

Contacts

Public ContactZhang Lei

Shanghai General Hospital

lei.zhang2@shgh.cn+86 13122020669

Outcome results

None listed

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