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Artificial intelligence to codify lung CT in Covid-19 patients
The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already assumed pandemic proportions, affecting over 100 countries in few weeks. A global response is needed to prepare health systems worldwide. Covid-19 can be diagnosed both on chest X-ray and on computed tomography (C...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Milan
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7197034/ https://www.ncbi.nlm.nih.gov/pubmed/32367319 http://dx.doi.org/10.1007/s11547-020-01195-x |
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author | Belfiore, Maria Paola Urraro, Fabrizio Grassi, Roberta Giacobbe, Giuliana Patelli, Gianluigi Cappabianca, Salvatore Reginelli, Alfonso |
author_facet | Belfiore, Maria Paola Urraro, Fabrizio Grassi, Roberta Giacobbe, Giuliana Patelli, Gianluigi Cappabianca, Salvatore Reginelli, Alfonso |
author_sort | Belfiore, Maria Paola |
collection | PubMed |
description | The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already assumed pandemic proportions, affecting over 100 countries in few weeks. A global response is needed to prepare health systems worldwide. Covid-19 can be diagnosed both on chest X-ray and on computed tomography (CT). Asymptomatic patients may also have lung lesions on imaging. CT investigation in patients with suspicion Covid-19 pneumonia involves the use of the high-resolution technique (HRCT). Artificial intelligence (AI) software has been employed to facilitate CT diagnosis. AI software must be useful categorizing the disease into different severities, integrating the structured report, prepared according to subjective considerations, with quantitative, objective assessments of the extent of the lesions. In this communication, we present an example of a good tool for the radiologist (Thoracic VCAR software, GE Healthcare, Italy) in Covid-19 diagnosis (Pan et al. in Radiology, 2020. 10.1148/radiol.2020200370). Thoracic VCAR offers quantitative measurements of the lung involvement. Thoracic VCAR can generate a clear, fast and concise report that communicates vital medical information to referring physicians. In the post-processing phase, software, thanks to the help of a colorimetric map, recognizes the ground glass and differentiates it from consolidation and quantifies them as a percentage with respect to the healthy parenchyma. AI software therefore allows to accurately calculate the volume of each of these areas. Therefore, keeping in mind that CT has high diagnostic sensitivity in identifying lesions, but not specific for Covid-19 and similar to other infectious viral diseases, it is mandatory to have an AI software that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one. |
format | Online Article Text |
id | pubmed-7197034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Milan |
record_format | MEDLINE/PubMed |
spelling | pubmed-71970342020-05-04 Artificial intelligence to codify lung CT in Covid-19 patients Belfiore, Maria Paola Urraro, Fabrizio Grassi, Roberta Giacobbe, Giuliana Patelli, Gianluigi Cappabianca, Salvatore Reginelli, Alfonso Radiol Med Short Communication The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already assumed pandemic proportions, affecting over 100 countries in few weeks. A global response is needed to prepare health systems worldwide. Covid-19 can be diagnosed both on chest X-ray and on computed tomography (CT). Asymptomatic patients may also have lung lesions on imaging. CT investigation in patients with suspicion Covid-19 pneumonia involves the use of the high-resolution technique (HRCT). Artificial intelligence (AI) software has been employed to facilitate CT diagnosis. AI software must be useful categorizing the disease into different severities, integrating the structured report, prepared according to subjective considerations, with quantitative, objective assessments of the extent of the lesions. In this communication, we present an example of a good tool for the radiologist (Thoracic VCAR software, GE Healthcare, Italy) in Covid-19 diagnosis (Pan et al. in Radiology, 2020. 10.1148/radiol.2020200370). Thoracic VCAR offers quantitative measurements of the lung involvement. Thoracic VCAR can generate a clear, fast and concise report that communicates vital medical information to referring physicians. In the post-processing phase, software, thanks to the help of a colorimetric map, recognizes the ground glass and differentiates it from consolidation and quantifies them as a percentage with respect to the healthy parenchyma. AI software therefore allows to accurately calculate the volume of each of these areas. Therefore, keeping in mind that CT has high diagnostic sensitivity in identifying lesions, but not specific for Covid-19 and similar to other infectious viral diseases, it is mandatory to have an AI software that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one. Springer Milan 2020-05-04 2020 /pmc/articles/PMC7197034/ /pubmed/32367319 http://dx.doi.org/10.1007/s11547-020-01195-x Text en © Italian Society of Medical Radiology 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Short Communication Belfiore, Maria Paola Urraro, Fabrizio Grassi, Roberta Giacobbe, Giuliana Patelli, Gianluigi Cappabianca, Salvatore Reginelli, Alfonso Artificial intelligence to codify lung CT in Covid-19 patients |
title | Artificial intelligence to codify lung CT in Covid-19 patients |
title_full | Artificial intelligence to codify lung CT in Covid-19 patients |
title_fullStr | Artificial intelligence to codify lung CT in Covid-19 patients |
title_full_unstemmed | Artificial intelligence to codify lung CT in Covid-19 patients |
title_short | Artificial intelligence to codify lung CT in Covid-19 patients |
title_sort | artificial intelligence to codify lung ct in covid-19 patients |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7197034/ https://www.ncbi.nlm.nih.gov/pubmed/32367319 http://dx.doi.org/10.1007/s11547-020-01195-x |
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