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Article

The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia

1
Medical Imaging Centre, Semmelweis University, 1082 Budapest, Hungary
2
MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, 1122 Budapest, Hungary
3
Department of Pulmonology, Semmelweis University, 1082 Budapest, Hungary
*
Author to whom correspondence should be addressed.
Academic Editor: Emilio Quaia
Tomography 2021, 7(4), 697-710; https://doi.org/10.3390/tomography7040058
Received: 8 September 2021 / Revised: 11 October 2021 / Accepted: 22 October 2021 / Published: 1 November 2021
We sought to analyze the prognostic value of laboratory and clinical data, and an artificial intelligence (AI)-based algorithm for Coronavirus disease 2019 (COVID-19) severity scoring, on CT-scans of patients hospitalized with COVID-19. Moreover, we aimed to determine personalized probabilities of clinical deterioration. Data of symptomatic patients with COVID-19 who underwent chest-CT-examination at the time of hospital admission between April and November 2020 were analyzed. COVID-19 severity score was automatically quantified for each pulmonary lobe as the percentage of affected lung parenchyma with the AI-based algorithm. Clinical deterioration was defined as a composite of admission to the intensive care unit, need for invasive mechanical ventilation, use of vasopressors or in-hospital mortality. In total 326 consecutive patients were included in the analysis (mean age 66.7 ± 15.3 years, 52.1% male) of whom 85 (26.1%) experienced clinical deterioration. In the multivariable regression analysis prior myocardial infarction (OR = 2.81, 95% CI = 1.12–7.04, p = 0.027), immunodeficiency (OR = 2.08, 95% CI = 1.02–4.25, p = 0.043), C-reactive protein (OR = 1.73, 95% CI = 1.32–2.33, p < 0.001) and AI-based COVID-19 severity score (OR = 1.08; 95% CI = 1.02–1.15, p = 0.013) appeared to be independent predictors of clinical deterioration. Personalized probability values were determined. AI-based COVID-19 severity score assessed at hospital admission can provide additional information about the prognosis of COVID-19, possibly serving as a useful tool for individualized risk-stratification. View Full-Text
Keywords: COVID-19; artificial intelligence; computed tomography COVID-19; artificial intelligence; computed tomography
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MDPI and ACS Style

Szabó, I.V.; Simon, J.; Nardocci, C.; Kardos, A.S.; Nagy, N.; Abdelrahman, R.-H.; Zsarnóczay, E.; Fejér, B.; Futácsi, B.; Müller, V.; Merkely, B.; Maurovich-Horvat, P. The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia. Tomography 2021, 7, 697-710. https://doi.org/10.3390/tomography7040058

AMA Style

Szabó IV, Simon J, Nardocci C, Kardos AS, Nagy N, Abdelrahman R-H, Zsarnóczay E, Fejér B, Futácsi B, Müller V, Merkely B, Maurovich-Horvat P. The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia. Tomography. 2021; 7(4):697-710. https://doi.org/10.3390/tomography7040058

Chicago/Turabian Style

Szabó, István V., Judit Simon, Chiara Nardocci, Anna S. Kardos, Norbert Nagy, Renad-Heyam Abdelrahman, Emese Zsarnóczay, Bence Fejér, Balázs Futácsi, Veronika Müller, Béla Merkely, and Pál Maurovich-Horvat. 2021. "The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia" Tomography 7, no. 4: 697-710. https://doi.org/10.3390/tomography7040058

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