Artificial Intelligence Algorithms for Discriminating Between COVID-19 and Influenza Pneumonitis Using Chest X-Rays

COVID-19 Clinical Trial

— AI-COVID-Xr  

Official title:

The Benefits of Artificial Intelligence Algorithms (CNNs) for Discriminating Between COVID-19 and Influenza Pneumonitis in an Emergency Department Using Chest X-Ray Examinations

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04313946
• Other study ID #: 0110
• Status: Recruiting
• Start date: March 18, 2020
• Est. completion date: August 18, 2020

Study information

• Verified date: April 2020
• Source: Grigore T. Popa University of Medicine and Pharmacy
• Contact: Alexandru Burlacu, MD, PhD
• Phone: 0040744488580
• Email: alexandru.burlacu[@]umfiasi.ro
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

This project aims to use artificial intelligence (image discrimination) algorithms, specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19. The objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza

Description:

This project aims to use artificial intelligence (image discrimination) algorithms;

• specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19;

• the objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza;

• this software will be trained by introducing X-Rays from patients with/without COVID-19 pneumonitis and/or flu pneumonitis;

• the same AI algorithm will run on future X-Ray scans for predicting possible COVID-19 pneumonitis

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 200
• Est. completion date: August 18, 2020
• Est. primary completion date: August 16, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• flu-like symptoms: myalgia, cough, fever, sputum

• Chest X-Rays

• COVID-19 biological tests

Exclusion Criteria:

• patient refusal

• uncertain radiographs

• uncertain tests results

Related Conditions & MeSH terms

• COVID-19
• Flu Like Illness
• Flu Symptom
• Influenza With Pneumonia
• Influenza, Human
• Lung Diseases, Interstitial
• Pneumonia
• Pneumonia Atypical
• Pneumonia, Interstitial
• Pneumonia, Ventilator-Associated
• Pneumonia, Viral

Intervention

Diagnostic Test:
• Scanning Chest X-rays and performing AI algorithms on images
Chest X-Rays; AI CNNs; Results

Locations

Country	Name	City	State
Italy	U.O. Multidisciplinare di Patologia Mammaria e Ricerca Traslazionale; Dipartimento Universitario Clinico di Scienze Mediche, Chirurgiche e della Salute Università degli Studi di Trieste	Cremona
Romania	University of Medicine and Pharmacy Gr T Popa	Iasi
United Kingdom	Department of Cardiology at Chelsea and Westminster NHS hospital	London

Sponsors (3)

Lead Sponsor	Collaborator
Professor Adrian Covic	Falcon Trading Iasi, Romanian Academy of Medical Sciences

Countries where clinical trial is conducted

Italy,  Romania,  United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	COVID-19 positive X-Rays	Number of participants with pneumonitis on Chest X-Ray and COVID 19 positive	6 months
Primary	COVID-19 negative X-Rays	Number of participants with pneumonitis on Chest X-Ray and COVID 19 negative	6 months