AI-based System for Assessing Suspected Viral Pneumonia Related Lung Changes

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.

NCT Number	NCT06501599
Lead Sponsor	Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department Collaborators: Sciberia Co. Ltd
Conditions	Pneumonia, Viral, COVID-19 Pneumonia
Enrollment	563 participants
Start Date	2024-06-03
Primary Completion	2025-06-03 (estimated)
Study Completion	2025-12-03 (estimated)
Updated on ClinicalTrials.gov	2024-07-22