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Comparative Study of Artificial Intelligence and Radiologists in Assessing Severity of COVID19 Patient Images

Clinical Validation of LungIQ for Severity Scoring for COVID19 using Chest Computed Tomography Imaging

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2020/09/028156
Enrollment
500
Registered
2020-09-30
Start date
Unknown
Completion date
Unknown
Last updated
2021-11-24

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

Conditions

Health Condition 1: B972- Coronavirus as the cause of diseases classified elsewhere

Interventions

Intervention1: LungIQ: Artificial Intelligence Based Software Tool for COVID19 Severity Scoring from CT imaging Control Intervention1: Manual Radiologists Report: Standard of care routine radiology re

Sponsors

Predible Health Private Limited
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1. Confirmed diagnosis of COVID-19, confirmed by RT-PCR 2. Non-contrast CT scan with slice thickness < 5mm 3. Both lungs must be fully visible within the field of view

Exclusion criteria

Exclusion criteria: 1. Individuals with CT scans that have motion artefacts and/or poor image quality 2. Apices cannot be cropped

Design outcomes

Primary

MeasureTime frame
On 25 point Severity Score, Within 1 class accuracy of LungIQ with Radiologists Assessment more than 80%Timepoint: End of Study—

Secondary

MeasureTime frame
Statistical correlation of CT Severity Score with clinical severity (p) less than 0.05Timepoint: End of Study—

Countries

India

Contacts

Public ContactDr Amit Kumar Sahu

Max Healthcare

drsahuamit@gmail.com

Outcome results

None listed

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