Status:

RECRUITING

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

Lead Sponsor:

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

Collaborating Sponsors:

Sciberia Co. Ltd

Conditions:

Pneumonia, Viral

COVID-19 Pneumonia

Eligibility:

All Genders

18+ years

Brief Summary

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 th...

Detailed Description

The AI-based system designed to process chest CT aims to 1) detect the presence of pathologic patterns associated with interstitial changes in pneumonia; 2) highlight areas on the images with the prob...

Eligibility Criteria

Inclusion

  • General
  • Patients over 18 years old;
  • Patients who underwent CT without contrast enhancement;
  • Patients who underwent a CT scan according to a standardized scanning protocol: 120 kilovolts, slice thickness max. 2 mm, rigid "lung" filter (kernel) reconstruction;
  • Patients whose studies should be of acceptable quality, performed with breath-holding, without technical artifacts, and respiratory and motor artifacts;
  • Patients whose studies must contain DICOM tags responsible for the orientation and position of the patient in the images during the study, as well as DICOM tags responsible for the size of the scans and image parameters;
  • Patients in whom the localization of changes is predominantly bilateral, in the basal and subpleural parts of the lungs, may be located peribronchial;
  • For group Normal
  • a. Patients who do not contain COVID-19-related CT patterns;
  • For groups Mild, Moderate, Severe, and Critical
  • Patients who contain COVID-19-related CT pattern: ground glass opacities (mild, moderate, and higher intensity);
  • Patients who contain COVID-19-related CT pattern: pulmonary consolidation;
  • Patients who contain COVID-19-related CT pattern: cobblestone infiltration of the lung parenchyma;
  • Patients who contain COVID-19-related CT pattern: hydrothorax;
  • Patients who contain a combination of one or more patterns.

Exclusion

  • Patients whose studies contain images with unreported CT patterns;
  • Patients whose examinations do not conform to DICOM format;
  • Patients whose examinations do not contain imaging of the lung region
  • Patients whose examinations contain technical artifacts caused by malfunctions or features of CT scanners;
  • Patients whose examinations contain improper patient positioning;
  • Patients whose examinations contain studies with deleted DICOM tags responsible for scan size and image parameters;
  • Patients whose examinations contain metal artifacts on the patient's body and clothing;
  • Patients whose examinations contain the presence of other pathologic changes of lungs in patients - neoplastic, tuberculosis process, bacterial pneumonia, etc.;
  • Patients under 18 years old.

Key Trial Info

Start Date :

June 3 2024

Trial Type :

OBSERVATIONAL

Allocation :

ESTIMATED

End Date :

December 3 2025

Estimated Enrollment :

563 Patients enrolled

Trial Details

Trial ID

NCT06501599

Start Date

June 3 2024

End Date

December 3 2025

Last Update

July 22 2024

Active Locations (1)

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Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

Moscow, Russia, 127051