A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes

doi:10.1007/978-1-0716-2395-4_30

. 2022:2511:395-404.

doi: 10.1007/978-1-0716-2395-4_30.

A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes

Amirhossein Sahebkar^{1

2

3

4

5}, Mitra Abbasifard^{6

7}, Samira Chaibakhsh⁸, Paul C Guest⁹, Mohamad Amin Pourhoseingholi¹⁰, Amir Vahedian-Azimi¹¹, Prashant Kesharwani¹², Tannaz Jamialahmadi¹³

Affiliations

¹ Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
² Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
³ School of Medicine, The University of Western Australia, Perth, Australia. amir_saheb2000@yahoo.com.
⁴ Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
⁵ Department of Biotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
⁶ Immunology of Infectious Diseases Research Center, Research Institute of Basic Medical Sciences, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. abbasifardm@yandex.com.
⁷ Department of Internal Medicine, Ali-Ibn Abi-Talib Hospital, School of Medicine, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. abbasifardm@yandex.com.
⁸ Eye Research Center, The five Senses Institute, Rassoul Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
⁹ Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil.
¹⁰ Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
¹¹ Trauma Research Center, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran.
¹² Department of Pharmaceutics, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, India.
¹³ Surgical Oncology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.

PMID: 35838977
DOI: 10.1007/978-1-0716-2395-4_30

A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes

Amirhossein Sahebkar et al. Methods Mol Biol. 2022.

. 2022:2511:395-404.

doi: 10.1007/978-1-0716-2395-4_30.

Authors

Affiliations

¹ Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
² Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
³ School of Medicine, The University of Western Australia, Perth, Australia. amir_saheb2000@yahoo.com.
⁴ Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
⁵ Department of Biotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran. amir_saheb2000@yahoo.com.
⁶ Immunology of Infectious Diseases Research Center, Research Institute of Basic Medical Sciences, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. abbasifardm@yandex.com.
⁷ Department of Internal Medicine, Ali-Ibn Abi-Talib Hospital, School of Medicine, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. abbasifardm@yandex.com.
⁸ Eye Research Center, The five Senses Institute, Rassoul Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
⁹ Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil.
¹⁰ Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
¹¹ Trauma Research Center, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran.
¹² Department of Pharmaceutics, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, India.
¹³ Surgical Oncology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.

PMID: 35838977
DOI: 10.1007/978-1-0716-2395-4_30

Abstract

There is still an urgent need to develop effective treatments to help minimize the cases of severe COVID-19. A number of tools have now been developed and applied to address these issues, such as the use of non-contrast chest computed tomography (CT) for evaluation and grading of the associated lung damage. Here we used a deep learning approach for predicting the outcome of 1078 patients admitted into the Baqiyatallah Hospital in Tehran, Iran, suffering from COVID-19 infections in the first wave of the pandemic. These were classified into two groups of non-severe and severe cases according to features on their CT scans with accuracies of approximately 0.90. We suggest that incorporation of molecular and/or clinical features, such as multiplex immunoassay or laboratory findings, will increase accuracy and sensitivity of the model for COVID-19 -related predictions.

Keywords: COVID-19; Chest CT; Computed tomography; Deep learning; Diffuse opacities; Lesion distribution; SARS-CoV-2.

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Cited by

Predicting the COVID-19 Patients Status Using Chest CT Scan Findings: A Risk Assessment Model Based on Decision Tree Analysis.
Talebi A, Borumandnia N, Jafari R, Pourhoseingholi MA, Jafari NJ, Ashtari S, Roozpeykar S, RahimiBashar F, Karimi L, Guest PC, Jamialahmadi T, Vahedian-Azimi A, Gohari-Moghadam K, Sahebkar A. Talebi A, et al. Adv Exp Med Biol. 2023;1412:237-250. doi: 10.1007/978-3-031-28012-2_13. Adv Exp Med Biol. 2023. PMID: 37378771

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1. Zhang L, Guo H (2021) Biomarkers of COVID-19 and technologies to combat SARS-CoV-2. Adv Biomark Sci Technol 2:1–23

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[1] https://www.worldometers.info/coronavirus/ . Accessed 23 Oct 2021

[2] https://www.worldometers.info/coronavirus/ . Accessed 23 Oct 2021

[3] Johns Hopkin’s Coronavirus Resource Center. https://coronavirus.jhu.edu/map.html . Accessed 23 Oct 2021

[4] Johns Hopkin’s Coronavirus Resource Center. https://coronavirus.jhu.edu/map.html . Accessed 23 Oct 2021

[5] Our world in data. Coronavirus (COVID-19) Vaccinations. https://ourworldindata.org/covid-vaccinations . Accessed 23 Oct 2021

[6] Our world in data. Coronavirus (COVID-19) Vaccinations. https://ourworldindata.org/covid-vaccinations . Accessed 23 Oct 2021

[7] Song Q, Sun X, Dai Z et al (2021) Point-of-care testing detection methods for COVID-19. Lab Chip 21(9):1634–1660 - DOI

[8] Song Q, Sun X, Dai Z et al (2021) Point-of-care testing detection methods for COVID-19. Lab Chip 21(9):1634–1660 - DOI

[9] Zhang L, Guo H (2021) Biomarkers of COVID-19 and technologies to combat SARS-CoV-2. Adv Biomark Sci Technol 2:1–23

[10] Zhang L, Guo H (2021) Biomarkers of COVID-19 and technologies to combat SARS-CoV-2. Adv Biomark Sci Technol 2:1–23

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A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes

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A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes

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