COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve
Abstract Background High-resolution computed tomography (HRCT) chest becomes a valuable diagnostic tool for identifying patients infected with Coronavirus Disease 2019 (COVID-19) in the early stage, where patients may be asymptomatic or with non-specific pulmonary symptoms. An early diagnosis of COV...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-10-01
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| Series: | The Egyptian Journal of Radiology and Nuclear Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s43055-021-00634-7 |
| _version_ | 1818930241065713664 |
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| author | Kamal Kumar Sen Roopak Dubey Mayank Goyal Humsheer Sethi Ajay Sharawat Rohit Arora |
| author_facet | Kamal Kumar Sen Roopak Dubey Mayank Goyal Humsheer Sethi Ajay Sharawat Rohit Arora |
| author_sort | Kamal Kumar Sen |
| collection | DOAJ |
| description | Abstract Background High-resolution computed tomography (HRCT) chest becomes a valuable diagnostic tool for identifying patients infected with Coronavirus Disease 2019 (COVID-19) in the early stage, where patients may be asymptomatic or with non-specific pulmonary symptoms. An early diagnosis of COVID-19 is of utmost importance, so that patients can be isolated and treated in time, eventually preventing spread of the disease, improving the prognosis and reducing the mortality. In this paper, we have highlighted our radiological experience of dealing with the pandemic crisis of 2020 through the study of HRCT thorax, lung ultrasonography, chest X-rays and artificial intelligence (AI). Results Results of CT thorax analysis have been given in detail. We had also compared CT severity score (CTSS) with clinical and laboratory parameters. Correlation of CTSS with SpO2 values and comorbidities was also studied. We also analysed manual CTSS with the CTSS scored calculated by the AI software. Conclusions CTSS and use of COVID-19 Reporting and Data System (CORADS) result in accuracy and uniform percolation of information among the clinicians. Bed-side X-rays and ultrasonography have played a role where the patients could not be shifted for CT scan. The possibility of predicting impending or progression of hypoxia was not possible when SpO2 mapping was correlated with the CTSS. AI was alternatively tried with available software (CT pneumonia analysis) which was not so appropriate considering the imaging patterns in the bulk of atypical category. |
| first_indexed | 2024-12-20T03:57:34Z |
| format | Article |
| id | doaj.art-06e88530c0b94df09df7cb1abf4e4b69 |
| institution | Directory Open Access Journal |
| issn | 2090-4762 |
| language | English |
| last_indexed | 2024-12-20T03:57:34Z |
| publishDate | 2021-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | The Egyptian Journal of Radiology and Nuclear Medicine |
| spelling | doaj.art-06e88530c0b94df09df7cb1abf4e4b692022-12-21T19:54:15ZengSpringerOpenThe Egyptian Journal of Radiology and Nuclear Medicine2090-47622021-10-0152111510.1186/s43055-021-00634-7COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curveKamal Kumar Sen0Roopak Dubey1Mayank Goyal2Humsheer Sethi3Ajay Sharawat4Rohit Arora5Department of Radiodiagnosis, Kalinga Institute of Medical SciencesDepartment of Radiodiagnosis, Kalinga Institute of Medical SciencesDepartment of Radiodiagnosis, Kalinga Institute of Medical SciencesDepartment of Radiodiagnosis, Kalinga Institute of Medical SciencesDepartment of Radiodiagnosis, Kalinga Institute of Medical SciencesDepartment of Radiodiagnosis, Kalinga Institute of Medical SciencesAbstract Background High-resolution computed tomography (HRCT) chest becomes a valuable diagnostic tool for identifying patients infected with Coronavirus Disease 2019 (COVID-19) in the early stage, where patients may be asymptomatic or with non-specific pulmonary symptoms. An early diagnosis of COVID-19 is of utmost importance, so that patients can be isolated and treated in time, eventually preventing spread of the disease, improving the prognosis and reducing the mortality. In this paper, we have highlighted our radiological experience of dealing with the pandemic crisis of 2020 through the study of HRCT thorax, lung ultrasonography, chest X-rays and artificial intelligence (AI). Results Results of CT thorax analysis have been given in detail. We had also compared CT severity score (CTSS) with clinical and laboratory parameters. Correlation of CTSS with SpO2 values and comorbidities was also studied. We also analysed manual CTSS with the CTSS scored calculated by the AI software. Conclusions CTSS and use of COVID-19 Reporting and Data System (CORADS) result in accuracy and uniform percolation of information among the clinicians. Bed-side X-rays and ultrasonography have played a role where the patients could not be shifted for CT scan. The possibility of predicting impending or progression of hypoxia was not possible when SpO2 mapping was correlated with the CTSS. AI was alternatively tried with available software (CT pneumonia analysis) which was not so appropriate considering the imaging patterns in the bulk of atypical category.https://doi.org/10.1186/s43055-021-00634-7COVID-19Artificial intelligenceLung ultrasonographyX-rays |
| spellingShingle | Kamal Kumar Sen Roopak Dubey Mayank Goyal Humsheer Sethi Ajay Sharawat Rohit Arora COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve The Egyptian Journal of Radiology and Nuclear Medicine COVID-19 Artificial intelligence Lung ultrasonography X-rays |
| title | COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve |
| title_full | COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve |
| title_fullStr | COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve |
| title_full_unstemmed | COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve |
| title_short | COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve |
| title_sort | covitale 2020 from eastern indian population imageologists perspective a learning curve |
| topic | COVID-19 Artificial intelligence Lung ultrasonography X-rays |
| url | https://doi.org/10.1186/s43055-021-00634-7 |
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