Visual and software-based quantitative chest CT assessment of COVID-19: correlation with clinical findings
| Autor: | Ilim Irmak, Figen Başaran Demirkazık, Serpil Öcal, Ilkay S. Idilman, Gülçin Telli, Selin Ardali Duzgun, Meltem Gulsun Akpinar, Arzu Topeli, Gamze Durhan, Erhan Akpinar, Orhan Macit Ariyurek |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Adult
Male medicine.medical_specialty Coronavirus disease 2019 (COVID-19) Pneumonia Viral Chest ct 030218 nuclear medicine & medical imaging law.invention Correlation Betacoronavirus 03 medical and health sciences 0302 clinical medicine Chest Imaging law Image Interpretation Computer-Assisted medicine Humans Radiology Nuclear Medicine and imaging In patient Lung Pandemics Retrospective Studies SARS-CoV-2 business.industry COVID-19 Retrospective cohort study Middle Aged Intensive care unit Icu admission medicine.anatomical_structure Evaluation Studies as Topic Female Radiology Coronavirus Infections Tomography X-Ray Computed Cardiology and Cardiovascular Medicine business |
| Zdroj: | Diagn Interv Radiol |
| ISSN: | 1305-3612 |
| DOI: | 10.5152/dir.2020.20407 |
| Popis: | PURPOSE: The aim of this study was to evaluate visual and software-based quantitative assessment of parenchymal changes and normal lung parenchyma in patients with coronavirus disease 2019 (COVID-19) pneumonia. The secondary aim of the study was to compare the radiologic findings with clinical and laboratory data. METHODS: Patients with COVID-19 who underwent chest computed tomography (CT) between March 11, 2020 and April 15, 2020 were retrospectively evaluated. Clinical and laboratory findings of patients with abnormal findings on chest CT and PCR-evidence of COVID-19 infection were recorded. Visual quantitative assessment score (VQAS) was performed according to the extent of lung opacities. Software-based quantitative assessment of the normal lung parenchyma percentage (SQNLP) was automatically quantified by a deep learning software. The presence of consolidation and crazy paving pattern (CPP) was also recorded. Statistical analyses were performed to evaluate the correlation between quantitative radiologic assessments, and clinical and laboratory findings, as well as to determine the predictive utility of radiologic findings for estimating severe pneumonia and admission to intensive care unit (ICU). RESULTS: A total of 90 patients were enrolled. Both VQAS and SQNLP were significantly correlated with multiple clinical parameters. While VQAS >8.5 (sensitivity, 84.2%; specificity, 80.3%) and SQNLP 9.5 (sensitivity, 93.3%; specificity, 86.5%) and SQNLP |
| Databáze: | OpenAIRE |
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