An Externally Validated Fully Automated Deep Learning Algorithm to Classify COVID-19 and Other Pneumonias on Chest Computed Tomography

Overview

Journal ERJ Open Res

Specialty Pulmonary Medicine

Date 2022 May 5

PMID 35509437

Authors

Akshayaa Vaidyanathan

Julien Guiot

Fadila Zerka

Flore Belmans

Ingrid Van Peufflik

Louis Deprez

Denis Danthine

Gregory Canivet

Philippe Lambin

Sean Walsh

Mariaelena Occhipinti

Paul Meunier

Wim Vos

Pierre Lovinfosse

Ralph T H Leijenaar

Affiliations

Soon will be listed here.

Abstract

Purpose: In this study, we propose an artificial intelligence (AI) framework based on three-dimensional convolutional neural networks to classify computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19), influenza/community-acquired pneumonia (CAP), and no infection, after automatic segmentation of the lungs and lung abnormalities.

Methods: The AI classification model is based on inflated three-dimensional Inception architecture and was trained and validated on retrospective data of CT images of 667 adult patients (no infection n=188, COVID-19 n=230, influenza/CAP n=249) and 210 adult patients (no infection n=70, COVID-19 n=70, influenza/CAP n=70), respectively. The model's performance was independently evaluated on an internal test set of 273 adult patients (no infection n=55, COVID-19 n= 94, influenza/CAP n=124) and an external validation set from a different centre (305 adult patients: COVID-19 n=169, no infection n=76, influenza/CAP n=60).

Results: The model showed excellent performance in the external validation set with area under the curve of 0.90, 0.92 and 0.92 for COVID-19, influenza/CAP and no infection, respectively. The selection of the input slices based on automatic segmentation of the abnormalities in the lung reduces analysis time (56 s per scan) and computational burden of the model. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) score of the proposed model is 47% (15 out of 32 TRIPOD items).

Conclusion: This AI solution provides rapid and accurate diagnosis in patients suspected of COVID-19 infection and influenza.

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