Actively Recruiting
AI-based System for Assessing Suspected Viral Pneumonia Related Lung Changes
Led by Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department · Updated on 2024-07-22
563
Participants Needed
1
Research Sites
78 weeks
Total Duration
On this page
Sponsors
R
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department
Lead Sponsor
S
Sciberia Co. Ltd
Collaborating Sponsor
AI-Summary
What this Trial Is About
The AI-based system designed to process chest computed tomography (CT) aims to 1) detect the presence of pathologic patterns associated with interstitial changes in pneumonia; 2) highlight areas on the images with the probable presence of pathologies; 3) provide the physician with the results of image processing, including quantitative indicators of suspected viral pneumonia related lung changes according to visual pulmonary lesion grading system (CT0-4). The retrospective study aims to demonstrate the clinical validation of the AI-based system. Clinical validation measures (sensitivity, specificity, accuracy, and area under the ROC curve) will be determined to provide evidence about the clinical efficacy of the AI-based system. The hypothesis is that the measures of clinical validation of the AI-based system differ by no more than 8% from those declared by the manufacturer.
CONDITIONS
Official Title
AI-based System for Assessing Suspected Viral Pneumonia Related Lung Changes
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Patients over 18 years old
- Patients who had a chest CT scan without contrast enhancement
- Chest CT scans performed with 120 kilovolts, slice thickness up to 2 mm, and rigid "lung" filter reconstruction
- Chest CT images of acceptable quality without technical, respiratory, or movement artifacts
- Chest CT images containing DICOM tags for patient orientation, position, scan size, and image parameters
- Lung changes mainly bilateral in basal and subpleural areas, possibly peribronchial
- For normal group: no COVID-19-related CT patterns
- For mild, moderate, severe, and critical groups: presence of COVID-19-related CT patterns such as ground glass opacities, pulmonary consolidation, cobblestone infiltration, hydrothorax, or combinations thereof
You will not qualify if you...
- Studies containing images with unreported CT patterns
- Examinations not in DICOM format
- Examinations missing lung region imaging
- Examinations with technical artifacts from scanner malfunctions
- Examinations with improper patient positioning
- Examinations missing DICOM tags for scan size and image parameters
- Examinations with metal artifacts on patient or clothing
- Presence of other lung diseases like neoplasms, tuberculosis, or bacterial pneumonia
- Patients under 18 years old
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department
Moscow, Russia, 127051
Actively Recruiting
Research Team
V
Victoria Zinchenko
CONTACT
A
Anton Vladzymyrskyy
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
5
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