AI system for assessing lung changes in viral pneumonia
Artificial Intelligence Based System for Assessing Suspected Viral Pneumonia Related Lung Changes According to Visual Pulmonary Lesion Grading System (CT 0-4): Retrospective Study
This study is testing a new AI tool that looks at chest CT scans to see if it can accurately spot lung changes caused by viral pneumonia, including COVID-19.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 563 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department Academic / other |
| Locations | 1 site (Moscow) |
| Trial ID | NCT06501599 on ClinicalTrials.gov |
What this trial studies
This observational study focuses on validating an AI-based system designed to analyze chest computed tomography (CT) images for detecting pathological patterns associated with viral pneumonia, including COVID-19. The system aims to highlight areas of concern in the images and provide quantitative indicators of lung changes based on a visual grading system. The study will collect a verified dataset of chest CT images to assess the system's clinical efficacy by measuring sensitivity, specificity, accuracy, and area under the ROC curve. The goal is to ensure that the AI system's performance aligns closely with the manufacturer's declared values.
Who should consider this trial
Good fit: Ideal candidates include adults over 18 who have undergone chest CT scans without contrast enhancement and meet specific imaging quality criteria.
Not a fit: Patients with CT scans showing infiltrative and interstitial lung changes characteristic of viral pneumonia may not benefit from this study.
Why it matters
Potential benefit: If successful, this AI-based system could enhance the accuracy of diagnosing viral pneumonia, leading to better patient management and outcomes.
How similar studies have performed: Other studies utilizing AI for medical imaging have shown promising results, indicating potential success for this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. General 1. Patients over 18 years old; 2. Patients who underwent CT without contrast enhancement; 3. Patients who underwent a CT scan according to a standardized scanning protocol: 120 kilovolts, slice thickness max. 2 mm, rigid "lung" filter (kernel) reconstruction; 4. Patients whose studies should be of acceptable quality, performed with breath-holding, without technical artifacts, and respiratory and motor artifacts; 5. 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; 6. Patients in whom the localization of changes is predominantly bilateral, in the basal and subpleural parts of the lungs, may be located peribronchial; 2. For group Normal a. Patients who do not contain COVID-19-related CT patterns; 3. For groups Mild, Moderate, Severe, and Critical 1. Patients who contain COVID-19-related CT pattern: ground glass opacities (mild, moderate, and higher intensity); 2. Patients who contain COVID-19-related CT pattern: pulmonary consolidation; 3. Patients who contain COVID-19-related CT pattern: cobblestone infiltration of the lung parenchyma; 4. Patients who contain COVID-19-related CT pattern: hydrothorax; 5. Patients who contain a combination of one or more patterns. Exclusion Criteria: * 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.
Where this trial is running
Moscow
- Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department — Moscow, Russia (Recruiting)
Study contacts
- Study coordinator: Victoria Zinchenko
- Email: ZinchenkoVV1@zdrav.mos.ru
- Phone: +7 (495) 276-04-36
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.