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Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital

Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer t...

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Autores principales: Stoichita, Alexandru, Ghita, Maria, Mahler, Beatrice, Vlasceanu, Silviu, Ghinet, Andreea, Mosteanu, Madalina, Cioacata, Andreea, Udrea, Andreea, Marcu, Alina, Mitra, George Daniel, Ionescu, Clara Mihaela, Iliesiu, Adriana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672398/
https://www.ncbi.nlm.nih.gov/pubmed/38002725
http://dx.doi.org/10.3390/jcm12227115
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author Stoichita, Alexandru
Ghita, Maria
Mahler, Beatrice
Vlasceanu, Silviu
Ghinet, Andreea
Mosteanu, Madalina
Cioacata, Andreea
Udrea, Andreea
Marcu, Alina
Mitra, George Daniel
Ionescu, Clara Mihaela
Iliesiu, Adriana
author_facet Stoichita, Alexandru
Ghita, Maria
Mahler, Beatrice
Vlasceanu, Silviu
Ghinet, Andreea
Mosteanu, Madalina
Cioacata, Andreea
Udrea, Andreea
Marcu, Alina
Mitra, George Daniel
Ionescu, Clara Mihaela
Iliesiu, Adriana
author_sort Stoichita, Alexandru
collection PubMed
description Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30–39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology “Marius Nasta” in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation.
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spelling pubmed-106723982023-11-15 Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital Stoichita, Alexandru Ghita, Maria Mahler, Beatrice Vlasceanu, Silviu Ghinet, Andreea Mosteanu, Madalina Cioacata, Andreea Udrea, Andreea Marcu, Alina Mitra, George Daniel Ionescu, Clara Mihaela Iliesiu, Adriana J Clin Med Article Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30–39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology “Marius Nasta” in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation. MDPI 2023-11-15 /pmc/articles/PMC10672398/ /pubmed/38002725 http://dx.doi.org/10.3390/jcm12227115 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Stoichita, Alexandru
Ghita, Maria
Mahler, Beatrice
Vlasceanu, Silviu
Ghinet, Andreea
Mosteanu, Madalina
Cioacata, Andreea
Udrea, Andreea
Marcu, Alina
Mitra, George Daniel
Ionescu, Clara Mihaela
Iliesiu, Adriana
Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital
title Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital
title_full Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital
title_fullStr Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital
title_full_unstemmed Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital
title_short Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital
title_sort imagistic findings using artificial intelligence in vaccinated versus unvaccinated sars-cov-2-positive patients receiving in-care treatment at a tertiary lung hospital
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672398/
https://www.ncbi.nlm.nih.gov/pubmed/38002725
http://dx.doi.org/10.3390/jcm12227115
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