Quantification of COVID-19 Opacities on Chest CT – Evaluation of a Fully Automatic AI-approach to Noninvasively Differentiate Critical Versus Noncritical Patients
| العنوان: | Quantification of COVID-19 Opacities on Chest CT – Evaluation of a Fully Automatic AI-approach to Noninvasively Differentiate Critical Versus Noncritical Patients |
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| المؤلفون: | Simon S. Martin, Simon Bernatz, Andreas M. Bucher, L Basten, Sabine Michalik, Thomas J. Vogl, Christian Booz, Christoph Mader, Moritz H. Albrecht, Vitali Koch, Leon D. Grünewald, Scherwin Mahmoudi |
| المصدر: | Academic Radiology |
| بيانات النشر: | The Association of University Radiologists. Published by Elsevier Inc., 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | PHO, Percentage of high opacity, GTP, Alanine aminotransferase, HR-CT, High-resolution computer tomography, HST, Urea, 030218 nuclear medicine & medical imaging, law.invention, 0302 clinical medicine, DDI, D-dimers, law, LEU, White blood cell count, Viral, DI2IN, Deep Image to Image Network, Lung, Original Investigation, COVID-19, Coronavirus disease 2019, Predictive marker, biology, RT-PCR, Real-time reverse transcription polymerase-chain-reaction, Middle Aged, Intensive care unit, PCT, Procalcitonin, ICU, Intensive care unit, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Cohort, Absolute neutrophil count, CRP, C-reactive protein, CT, Computed tomography, LAC, Lactate, LYM, Lymphocyte count, RIS, Radiology information system, TNTHS, Troponin, HU, Hounsfield units, SARS-CoV-2, Severe acute respiratory syndrome coronavirus type, WHO, World Health Organization, 03 medical and health sciences, Artificial Intelligence, PACS, Picture archiving and communication system, ARDS, Acute respiratory distress syndrome, medicine, Humans, Radiology, Nuclear Medicine and imaging, TPZ, Quick value, DICOM, Digital Imaging and Communications in Medicine, IL-6, Interleukin-6, THR, Thrombocyte count, Retrospective Studies, LDH, Lactate dehydrogenase, business.industry, VRT, Volume rendering technique, SARS-CoV-2 infection, AI, Artificial intelligence, KREA, Creatinine, GGO, Ground-glass opacities, COVID-19, Retrospective cohort study, Pneumonia, medicine.disease, Troponin, Chest-CT, BIL, Bilirubin, biology.protein, NEU, Neutrophil count, Nuclear medicine, business, Tomography, X-Ray Computed |
| الوصف: | OBJECTIVES: To evaluate the potential of a fully automatic artificial intelligence (AI)-driven computed tomography (CT) software prototype to quantify severity of COVID-19 infection on chest CT in relationship with clinical and laboratory data. METHODS: We retrospectively analyzed 50 patients with laboratory confirmed COVID-19 infection who had received chest CT between March and July 2020. Pulmonary opacifications were automatically evaluated by an AI-driven software and correlated with clinical and laboratory parameters using Spearman-Rho and linear regression analysis. We divided the patients into sub cohorts with or without necessity of intensive care unit (ICU) treatment. Sub cohort differences were evaluated employing Wilcoxon-Mann-Whitney-Test. RESULTS: We included 50 CT examinations (mean age, 57.24 years), of whom 24 (48%) had an ICU stay. Extent of COVID-19 like opacities on chest CT showed correlations (all p < 0.001 if not otherwise stated) with occurrence of ICU stay (Râ¯=â¯0.74), length of ICU stay (Râ¯=â¯0.81), lethal outcome (Râ¯=â¯0.56) and length of hospital stay (Râ¯=â¯0.33, p < 0.05). The opacities extent was correlated with laboratory parameters: neutrophil count (NEU) (Râ¯=â¯0.60), lactate dehydrogenase (LDH) (Râ¯=â¯0.60), troponin (TNTHS) (Râ¯=â¯0.55) and c-reactive protein (CRP) (Râ¯=â¯0.51). Differences (p < 0.001) between ICU group and non-ICU group concerned longer length of hospital stay (24.04 vs. 10.92 days), higher opacity score (12.50 vs. 4.96) and severity of laboratory data changes such as c-reactive protein (11.64 vs. 5.07 mg/dl, p < 0.01). CONCLUSIONS: Automatically AI-driven quantification of opacities on chest CT correlates with laboratory and clinical data in patients with confirmed COVID-19 infection and may serve as non-invasive predictive marker for clinical course of COVID-19. |
| اللغة: | English |
| تدمد: | 1878-4046 1076-6332 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4362af8e2888921c210c80a9412340b8Test http://europepmc.org/articles/PMC7936551Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....4362af8e2888921c210c80a9412340b8 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 18784046 10766332 |
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