Convolutional Neural Network Model to Detect Coronavirus Disease 2019 (COVID-19) Pneumonia in Chest Radiographs (RedNeumon)

Fundacion Clinica Valle del Lili

Status: Completed

Conditions: COVID-19 (Coronavirus Disease 2019); COVID-19 Pneumonia

Treatments: Other: Categorization of chest xrays images

Study type: Observational

Funder types: Other

Identifiers

NCT05722665

1805

Details and patient eligibility

About

This study aims to design a Convolutional Neural Network (CNN) and apply an attention model to help differentiate pneumonia due to Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), pneumonia due to other viruses/bacteria, and normal chest x-ray (CXR) in clinical practice. A bank of digital chest images from a high-complexity health facility in Cali, Colombia, was used.

Full description

To differentiate coronavirus disease 2019 (COVID-19) pneumonia from other types of pneumonia, expert radiologists must analyze the chest x-ray (CXR) to identify visual, radiographic patterns associated with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. It is challenging because the findings are similar for different types of pneumonia.

Since the manual diagnosis of COVID-19 from CXR is a difficult and time-consuming process, applying deep learning (DL) models to medical image analysis is a current hot research topic. This work will develop a new Convolutional Neural Network (CNN) to detect COVID-19 radiographs. It will use a large dataset of chest radiographs classified into three classes: viral/bacterial pneumonia, COVID-19 pneumonia, and normal images. The study aims to incorporate a new attention module that applies CNNs to the linear projection operation to help differentiate COVID-19 pneumonia from other pneumonia and normal chest radiographs in clinical practice.

Enrollment: 3,599 patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Chest radiographs from patients without COVID-19 or other pneumonia took before the pandemic start date (January 2020)
• Chest radiographs from patients with COVID-19 confirmed by positive Reverse Transcriptase polymerase chain reaction (RT-PCR) and/or presence of antibodies to COVID-19 and/or positive COVID-19 viral antigen.
• Chest radiographs from patients without COVID-19 confirmed by a negative Reverse Transcriptase polymerase chain reaction (RT-PCR) and other pneumonia diagnoses taken before the pandemic start date (January 2020)

Exclusion criteria

• N/A

Trial design

3,599 participants in 3 patient groups

Normal chest radiographs

Description:

X-rays without alterations in the lung parenchyma

Treatment:

Other: Categorization of chest xrays images

COVID-19 chest radiographs

Description:

X-rays belonging to patients with a diagnosis of COVID-19 confirmed by positive Reverse Transcriptase polymerase chain reaction (RT-PCR) and/or presence of antibodies to COVID-19 and/or positive COVID-19 viral antigen.

Treatment:

Other: Categorization of chest xrays images

Other pneumonia chest radiographs

Description:

X-rays belonging to patients with a diagnosis of pneumonia other than COVID-19

Treatment:

Other: Categorization of chest xrays images