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Steuwe A, Kamp B, Afat S, Akinina A, Aludin S, Bas EG, Berger J, Bohrer E, Brose A, Büttner SM, Ehrengut C, Gerwing M, Grosu S, Gussew A, Güttler F, Heinrich A, Jiraskova P, Kloth C, Kottlors J, Kuennemann MD, Liska C, Lubina N, Manzke M, Meinel FG, Meyer HJ, Mittermeier A, Persigehl T, Schmill LP, Steinhardt M, The Racoon Study Group, Antoch G, Valentin B. Standardization of a CT Protocol for Imaging Patients with Suspected COVID-19-A RACOON Project. Bioengineering (Basel) 2024; 11:207. [PMID: 38534481 DOI: 10.3390/bioengineering11030207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/09/2024] [Accepted: 02/15/2024] [Indexed: 03/28/2024] Open
Abstract
CT protocols that diagnose COVID-19 vary in regard to the associated radiation exposure and the desired image quality (IQ). This study aims to evaluate CT protocols of hospitals participating in the RACOON (Radiological Cooperative Network) project, consolidating CT protocols to provide recommendations and strategies for future pandemics. In this retrospective study, CT acquisitions of COVID-19 patients scanned between March 2020 and October 2020 (RACOON phase 1) were included, and all non-contrast protocols were evaluated. For this purpose, CT protocol parameters, IQ ratings, radiation exposure (CTDIvol), and central patient diameters were sampled. Eventually, the data from 14 sites and 534 CT acquisitions were analyzed. IQ was rated good for 81% of the evaluated examinations. Motion, beam-hardening artefacts, or image noise were reasons for a suboptimal IQ. The tube potential ranged between 80 and 140 kVp, with the majority between 100 and 120 kVp. CTDIvol was 3.7 ± 3.4 mGy. Most healthcare facilities included did not have a specific non-contrast CT protocol. Furthermore, CT protocols for chest imaging varied in their settings and radiation exposure. In future, it will be necessary to make recommendations regarding the required IQ and protocol parameters for the majority of CT scanners to enable comparable IQ as well as radiation exposure for different sites but identical diagnostic questions.
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Affiliation(s)
- Andrea Steuwe
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Benedikt Kamp
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Alena Akinina
- Clinic and Outpatient Clinic for Radiology, University Hospital Halle (Saale), 06120 Halle, Germany
| | - Schekeb Aludin
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein Campus Kiel, 24105 Kiel, Germany
| | - Elif Gülsah Bas
- Department of Diagnostic and Interventional Radiology, University Hospital of Marburg, 35043 Marburg, Germany
| | - Josephine Berger
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Evelyn Bohrer
- Department of Diagnostic and Interventional Radiology, University Hospital Giessen, Justus Liebig University, Klinikstr. 33, 35392 Giessen, Germany
| | - Alexander Brose
- Department of Diagnostic and Interventional Radiology, University Hospital Giessen, Justus Liebig University, Klinikstr. 33, 35392 Giessen, Germany
| | - Susanne Martina Büttner
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Constantin Ehrengut
- Department of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103 Leipzig, Germany
| | - Mirjam Gerwing
- Clinic of Radiology, University of Münster, 48149 Münster, Germany
| | - Sergio Grosu
- Department of Radiology, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - Alexander Gussew
- Clinic and Outpatient Clinic for Radiology, University Hospital Halle (Saale), 06120 Halle, Germany
| | - Felix Güttler
- Department of Radiology, Jena University Hospital, Friedrich Schiller University, 07747 Jena, Germany
| | - Andreas Heinrich
- Department of Radiology, Jena University Hospital, Friedrich Schiller University, 07747 Jena, Germany
| | - Petra Jiraskova
- Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Jonathan Kottlors
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany
| | | | - Christian Liska
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany
| | - Nora Lubina
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany
| | - Mathias Manzke
- Institute of Diagnostic and Interventional Radiology, Paediatric Radiology and Neuroradiology, University Medical Centre Rostock, Schillingallee 36, 18057 Rostock, Germany
| | - Felix G Meinel
- Institute of Diagnostic and Interventional Radiology, Paediatric Radiology and Neuroradiology, University Medical Centre Rostock, Schillingallee 36, 18057 Rostock, Germany
| | - Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103 Leipzig, Germany
| | - Andreas Mittermeier
- Department of Radiology, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - Thorsten Persigehl
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany
| | - Lars-Patrick Schmill
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein Campus Kiel, 24105 Kiel, Germany
| | - Manuel Steinhardt
- Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany
| | | | - Gerald Antoch
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Birte Valentin
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
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Saeed MK, Alshamrani HA, Abdullah YM, Ali ASAM, Almalki Y, Alqfail KA. Chest CT utilization in COVID-19: a dosimetric and diagnostic-quality study. RADIATION PROTECTION DOSIMETRY 2023; 199:1257-1263. [PMID: 37295952 DOI: 10.1093/rpd/ncad174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 05/13/2023] [Accepted: 05/18/2023] [Indexed: 06/12/2023]
Abstract
The purpose of this study is to look at the variations in chest computed tomography (CT) use, radiation dose and image quality in the 2019 novel coronavirus (COVID-19) pneumonia patients in Saudi Arabia. This is a retrospective study of 402 patients with COVID-19, who were treated between February and October 2021. Radiation dose was estimated using metrics of volume CT dose index (CTDIvol) and size-specific dose estimate (SSDE). The imaging performance of the CT scanners was evaluated by measuring different parameters, such as resolution and CT number uniformity, with an ACR-CT accreditation phantom. Expert radiologists assessed the diagnostic quality and occurrence of artefacts. For all of the image quality parameters tested, the majority of the scanner sites (80%) were found to be within the suggested acceptance limits. Ground-glass opacities were the most common finding in our patient sample (54%). On chest CT exams with typical appearance of COVID-19 pneumonia, the most respiratory motion artefacts (56.3%) were present, followed by those with indeterminate appearance (32.2%). There were significant differences in CT utilization, CTDIvol and SSDE across the collaborated sites. The use of CT scans and radiation doses varied in the COVID-19 patients, highlighting the optimizations of CT protocols at participating sites.
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Affiliation(s)
- Mohammed K Saeed
- Department of Radiological Sciences, Faculty of Applied Medical Sciences, Najran University, Najran 1988, Saudi Arabia
| | - Hassan A Alshamrani
- Department of Radiological Sciences, Faculty of Applied Medical Sciences, Najran University, Najran 1988, Saudi Arabia
| | - Youssef M Abdullah
- Department of Radiological Science and Medical Imaging, College of Applied Medical Sciences, Majmaah University, Al-Majmaah 11952, Saudi Arabia
| | - Ali Sid Ahmed M Ali
- Faculty of Science and Technology, Al Neelain University, Medical Physics Department, Khartoum 12702, Sudan
| | - Y Almalki
- College of Medicine, Najran University, P.O Box 1988, Najran, Saudi Arabia
| | - Khaled A Alqfail
- College of Medicine, Najran University, P.O Box 1988, Najran, Saudi Arabia
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Suliman II, Khouqeer GA, Ahmed NA, Abuzaid MM, Sulieman A. Low-Dose Chest CT Protocols for Imaging COVID-19 Pneumonia: Technique Parameters and Radiation Dose. Life (Basel) 2023; 13:life13040992. [PMID: 37109522 PMCID: PMC10146316 DOI: 10.3390/life13040992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 03/29/2023] [Accepted: 04/02/2023] [Indexed: 04/29/2023] Open
Abstract
Chest computed tomography (CT) plays a vital role in the early diagnosis, treatment, and follow-up of COVID-19 pneumonia during the pandemic. However, this raises concerns about excessive exposure to ionizing radiation. This study aimed to survey radiation doses in low-dose chest CT (LDCT) and ultra-low-dose chest CT (ULD) protocols used for imaging COVID-19 pneumonia relative to standard CT (STD) protocols so that the best possible practice and dose reduction techniques could be recommended. A total of 564 articles were identified by searching major scientific databases, including ISI Web of Science, Scopus, and PubMed. After evaluating the content and applying the inclusion criteria to technical factors and radiation dose metrics relevant to the LDCT protocols used for imaging COVID-19 patients, data from ten articles were extracted and analyzed. Technique factors that affect the application of LDCT and ULD are discussed, including tube current (mA), peak tube voltage (kVp), pitch factor, and iterative reconstruction (IR) algorithms. The CTDIvol values for the STD, LDCT, and ULD chest CT protocols ranged from 2.79-13.2 mGy, 0.90-4.40 mGy, and 0.20-0.28 mGy, respectively. The effective dose (ED) values for STD, LDCT, and ULD chest CT protocols ranged from 1.66-6.60 mSv, 0.50-0.80 mGy, and 0.39-0.64 mSv, respectively. Compared with the standard (STD), LDCT reduced the dose reduction by a factor of 2-4, whereas ULD reduced the dose reduction by a factor of 8-13. These dose reductions were achieved by applying scan parameters and techniques such as iterative reconstructions, ultra-long pitches, and fast spectral shaping with a tin filter. Using LDCT, the cumulative radiation dose of serial CT examinations during the acute period of COVID-19 may have been inferior or equivalent to that of conventional CT.
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Affiliation(s)
- Ibrahim I Suliman
- Department of Physics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11642, Saudi Arabia
- Deanship of Scientific Research, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11642, Saudi Arabia
| | - Ghada A Khouqeer
- Department of Physics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11642, Saudi Arabia
| | - Nada A Ahmed
- Faculty of Science, Taibah University, Al Madinah Al Munawwarah 42353, Saudi Arabia
| | - Mohamed M Abuzaid
- Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Abdelmoneim Sulieman
- Radiology and Medical Imaging Department, College of Applied Medical Sciences, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia
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Tawk S, Mansour W, Sleiman D, Gemayel S, Lozom E, El Mendelek K, Saliba N, Mourad C. Submillisievert CT chest for COVID-19 patients in a rural hospital with limited resources. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [PMCID: PMC8894825 DOI: 10.1186/s43055-022-00737-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Background This is a secondary analysis of prospectively acquired data approved by the hospital institutional board committee. We performed a retrospective chart review of 463 patients who underwent a CT Chest for suspected COVID-19 infection between April 1st, 2020, and March 31st, 2021. Patients were grouped based on the CT chest obtained protocol: ultra-low dose or full dose. The likelihood of suspicion of COVID-19 infection was classified on a Likert scale based on the probability of pulmonary involvement. For each group, the sensitivity and specificity of CT were compared to nasopharyngeal swab as standard of reference. The median dose length product and duration of apnea were compared between both groups using two-tailed Mann–Whitney U test. The aim of this study is to share our experience of reducing radiation dose in COVID-19 patients by using an ultra-low dose CT chest protocol on a 16 row multidetector CT scan in a hospital with limited resources. Results Two hundred sixty-nine patients underwent a full dose CT and 194 patients an ultra-low dose CT. In the former group, the median dose length product was 341.11 mGy*cm [Interquartile range (IQR), 239.1–443.2] and the median duration of apnea was 13.29 s [IQR, 10.85–15.73]. In the latter group, the median dose length product was 30.8 mGy*cm [IQR, 28.9–32.7] and median duration of apnea was 8.27 s [IQR, 7.69–8.85]. The sensitivity of the ultra-low dose CT was 91.2% and that of the full dose was 94%. Conclusion A 90% reduction in estimated dose and 38% reduction in apnea duration could be achieved using an ultra-low dose CT chest protocol on a 16-row MDCT without significant loss in the sensitivity of CT to detect COVID-related parenchymal involvement.
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Thieß HM, Bressem KK, Adams L, Böning G, Vahldiek JL, Niehues SM. Do submillisievert-chest CT protocols impact diagnostic quality in suspected COVID-19 patients? Acta Radiol Open 2022; 11:20584601211073864. [PMID: 35096416 PMCID: PMC8796096 DOI: 10.1177/20584601211073864] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 12/29/2021] [Indexed: 12/21/2022] Open
Abstract
Background During the ongoing global SARS-CoV-2 pandemic, there is a high demand for quick and reliable methods for early identification of infected patients. Due to its widespread availability, chest-CT is commonly used to detect early pulmonary manifestations and for follow-ups. Purpose This study aims to analyze image quality and reproducibility of readings of scans using low-dose chest CT protocols in patients suspected of SARS-CoV-2 infection. Materials and Methods Two radiologists retrospectively analyzed 100 low-dose chest CT scans of patients suspected of SARS-CoV-2 infection using two protocols on devices from two vendors regarding image quality based on a Likert scale. After 3 weeks, quality ratings were repeated to allow for analysis of intra-reader in addition to the inter-reader agreement. Furthermore, radiation dose and presence as well as distribution of radiological features were noted. Results The exams’ effective radiation doses were in median in the submillisievert range (median of 0.53 mSv, IQR: 0.35 mSv). While most scans were rated as being of optimal quality, 38% of scans were scored as suboptimal, yet only one scan was non-diagnostic. Inter-reader and intra-reader reliability showed almost perfect agreement with Cohen’s kappa of 0.82 and 0.87. Conclusion Overall, in this study, we present two protocols for submillisievert low-dose chest CT demonstrating appropriate or better image quality with almost perfect inter-reader and intra-reader agreement in patients suspected of SARS-CoV-2 infection.
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Affiliation(s)
- Hans-Martin Thieß
- Department of Radiology, Charité Universitätsmedizin Berlin Campus Benjamin Franklin, Berlin, Germany
| | - Keno K Bressem
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Lisa Adams
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Böning
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan M Niehues
- Klinik für Radiologie, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Bernardo M, Homayounieh F, Cuter MCR, Bellegard LM, Oliveira Junior HM, Buril GO, de Melo Tapajós JS, Sales DM, de Moura Carvalho LC, Alves Pinto D, Varella R, Tapajós LL, Ebrahimian S, Vassileva J, Kalra MK, Khoury HJ. CHEST CT USAGE IN COVID-19 PNEUMONIA: MULTICENTER STUDY ON RADIATION DOSES AND DIAGNOSTIC QUALITY IN BRAZIL. RADIATION PROTECTION DOSIMETRY 2021; 197:135-145. [PMID: 34875692 PMCID: PMC8903326 DOI: 10.1093/rpd/ncab171] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 10/15/2021] [Accepted: 05/08/2021] [Indexed: 06/13/2023]
Abstract
We assessed variations in chest CT usage, radiation dose and image quality in COVID-19 pneumonia. Our study included all chest CT exams performed in 533 patients from 6 healthcare sites from Brazil. We recorded patients' age, gender and body weight and the information number of CT exams per patient, scan parameters and radiation doses (volume CT dose index-CTDIvol and dose length product-DLP). Six radiologists assessed all chest CT exams for the type of pulmonary findings and classified CT appearance of COVID-19 pneumonia as typical, indeterminate, atypical or negative. In addition, each CT was assessed for diagnostic quality (optimal or suboptimal) and presence of artefacts. Artefacts were frequent (367/841), often related to respiratory motion (344/367 chest CT exams with artefacts) and resulted in suboptimal evaluation in mid-to-lower lungs (176/344) or the entire lung (31/344). There were substantial differences in CT usage, patient weight, CTDIvol and DLP across the participating sites.
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A novel Gray-Scale spatial exploitation learning Net for COVID-19 by crawling Internet resources. Biomed Signal Process Control 2021; 73:103441. [PMID: 34899960 PMCID: PMC8645252 DOI: 10.1016/j.bspc.2021.103441] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 11/07/2021] [Accepted: 11/29/2021] [Indexed: 12/11/2022]
Abstract
Today, the earth planet suffers from the decay of active pandemic COVID-19 which motivates scientists and researchers to detect and diagnose the infected people. Chest X-ray (CXR) image is a common utility tool for detection. Even the CXR suffers from low informative details about COVID-19 patches; the computer vision helps to overcome it through grayscale spatial exploitation analysis. In turn, it is highly recommended to acquire more CXR images to increase the capacity and ability to learn for mining the grayscale spatial exploitation. In this paper, an efficient Gray-scale Spatial Exploitation Net (GSEN) is designed by employing web pages crawling across cloud computing environments. The motivation of this work are i) utilizing a framework methodology for constructing consistent dataset by web crawling to update the dataset continuously per crawling iteration; ii) designing lightweight, fast learning, comparable accuracy, and fine-tuned parameters gray-scale spatial exploitation deep neural net; iii) comprehensive evaluation of the designed gray-scale spatial exploitation net for different collected dataset(s) based on web COVID-19 crawling verse the transfer learning of the pre-trained nets. Different experiments have been performed for benchmarking both the proposed web crawling framework methodology and the designed gray-scale spatial exploitation net. Due to the accuracy metric, the proposed net achieves 95.60% for two-class labels, and 92.67% for three-class labels, respectively compared with the most recent transfer learning Google-Net, VGG-19, Res-Net 50, and Alex-Net approaches. Furthermore, web crawling utilizes the accuracy rates improvement in a positive relationship to the cardinality of crawled CXR dataset.
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Garg M, Prabhakar N, Bhalla AS. Cancer risk of CT scan in COVID-19: Resolving the dilemma. Indian J Med Res 2021; 153:568-571. [PMID: 34596597 PMCID: PMC8555607 DOI: 10.4103/ijmr.ijmr_1476_21] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Affiliation(s)
- Mandeep Garg
- Department of Radiodiagnosis & Imaging, Postgraduate Institute of Medical Education & Research, Chandigarh 160 012, India
| | - Nidhi Prabhakar
- Department of Radiodiagnosis & Imaging, Postgraduate Institute of Medical Education & Research, Chandigarh 160 012, India
| | - Ashu Seith Bhalla
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi 110 029, India
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Hosse C, Büttner L, Fleckenstein FN, Hamper CM, Jonczyk M, Scholz O, Aigner A, Böning G. CT-Based Risk Stratification for Intensive Care Need and Survival in COVID-19 Patients-A Simple Solution. Diagnostics (Basel) 2021; 11:diagnostics11091616. [PMID: 34573957 PMCID: PMC8465083 DOI: 10.3390/diagnostics11091616] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 08/27/2021] [Accepted: 08/31/2021] [Indexed: 12/11/2022] Open
Abstract
We evaluated a simple semi-quantitative (SSQ) method for determining pulmonary involvement in computed tomography (CT) scans of COVID-19 patients. The extent of lung involvement in the first available CT was assessed with the SSQ method and subjectively. We identified risk factors for the need of invasive ventilation, intensive care unit (ICU) admission and for time to death after infection. Additionally, the diagnostic performance of both methods was evaluated. With the SSQ method, a 10% increase in the affected lung area was found to significantly increase the risk for need of ICU treatment with an odds ratio (OR) of 1.68 and for invasive ventilation with an OR of 1.35. Male sex, age, and pre-existing chronic lung disease were also associated with higher risks. A larger affected lung area was associated with a higher instantaneous risk of dying (hazard ratio (HR) of 1.11) independently of other risk factors. SSQ measurement was slightly superior to the subjective approach with an AUC of 73.5% for need of ICU treatment and 72.7% for invasive ventilation. SSQ assessment of the affected lung in the first available CT scans of COVID-19 patients may support early identification of those with higher risks for need of ICU treatment, invasive ventilation, or death.
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Affiliation(s)
- Clarissa Hosse
- Institute of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; (C.H.); (F.N.F.); (C.M.H.); (M.J.); (O.S.); (G.B.)
| | - Laura Büttner
- Institute of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; (C.H.); (F.N.F.); (C.M.H.); (M.J.); (O.S.); (G.B.)
- Correspondence:
| | - Florian Nima Fleckenstein
- Institute of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; (C.H.); (F.N.F.); (C.M.H.); (M.J.); (O.S.); (G.B.)
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany;
| | - Christina Maria Hamper
- Institute of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; (C.H.); (F.N.F.); (C.M.H.); (M.J.); (O.S.); (G.B.)
| | - Martin Jonczyk
- Institute of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; (C.H.); (F.N.F.); (C.M.H.); (M.J.); (O.S.); (G.B.)
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany;
| | - Oriane Scholz
- Institute of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; (C.H.); (F.N.F.); (C.M.H.); (M.J.); (O.S.); (G.B.)
| | - Annette Aigner
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany;
- Institute of Biometry and Clinical Epidemiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Georg Böning
- Institute of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; (C.H.); (F.N.F.); (C.M.H.); (M.J.); (O.S.); (G.B.)
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Büttner L, Aigner A, Fleckenstein FN, Hamper CM, Jonczyk M, Hamm B, Scholz O, Böning G. Diagnostic Value of Initial Chest CT Findings for the Need of ICU Treatment/Intubation in Patients with COVID-19. Diagnostics (Basel) 2020; 10:E929. [PMID: 33182695 PMCID: PMC7696816 DOI: 10.3390/diagnostics10110929] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 01/08/2023] Open
Abstract
Computed tomography (CT) plays an important role in the diagnosis of COVID-19. The aim of this study was to evaluate a simple, semi-quantitative method that can be used for identifying patients in need of subsequent intensive care unit (ICU) treatment and intubation. We retrospectively analyzed the initial CT scans of 28 patients who tested positive for SARS-CoV-2 at our Level-I center. The extent of lung involvement on CT was classified both subjectively and with a simple semi-quantitative method measuring the affected area at three lung levels. Competing risks Cox regression was used to identify factors associated with the time to ICU admission and intubation. Their potential diagnostic ability was assessed with receiver operating characteristic (ROC)/area under the ROC curves (AUC) analysis. A 10% increase in the affected lung parenchyma area increased the instantaneous risk of intubation (hazard ratio (HR) = 2.00) and the instantaneous risk of ICU admission (HR 1.73). The semi-quantitative measurement outperformed the subjective assessment diagnostic ability (AUC = 85.6% for ICU treatment, 71.9% for intubation). This simple measurement of the involved lung area in initial CT scans of COVID-19 patients may allow early identification of patients in need of ICU treatment/intubation and thus help make optimal use of limited ICU/ventilation resources in hospitals.
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Affiliation(s)
- Laura Büttner
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Radiology, Charitéplatz 1, 10117 Berlin, Germany; (F.N.F.); (C.M.H.); (M.J.); (B.H.); (O.S.); (G.B.)
| | - Annette Aigner
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Biometry and Clinical Epidemiology, Charitéplatz 1, 10117 Berlin, Germany;
- Berlin Institute of Health (BIH), Anna-Louisa-Karsch 2, 10178 Berlin, Germany
| | - Florian Nima Fleckenstein
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Radiology, Charitéplatz 1, 10117 Berlin, Germany; (F.N.F.); (C.M.H.); (M.J.); (B.H.); (O.S.); (G.B.)
- Berlin Institute of Health (BIH), Anna-Louisa-Karsch 2, 10178 Berlin, Germany
| | - Christina Maria Hamper
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Radiology, Charitéplatz 1, 10117 Berlin, Germany; (F.N.F.); (C.M.H.); (M.J.); (B.H.); (O.S.); (G.B.)
| | - Martin Jonczyk
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Radiology, Charitéplatz 1, 10117 Berlin, Germany; (F.N.F.); (C.M.H.); (M.J.); (B.H.); (O.S.); (G.B.)
- Berlin Institute of Health (BIH), Anna-Louisa-Karsch 2, 10178 Berlin, Germany
| | - Bernd Hamm
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Radiology, Charitéplatz 1, 10117 Berlin, Germany; (F.N.F.); (C.M.H.); (M.J.); (B.H.); (O.S.); (G.B.)
| | - Oriane Scholz
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Radiology, Charitéplatz 1, 10117 Berlin, Germany; (F.N.F.); (C.M.H.); (M.J.); (B.H.); (O.S.); (G.B.)
| | - Georg Böning
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Radiology, Charitéplatz 1, 10117 Berlin, Germany; (F.N.F.); (C.M.H.); (M.J.); (B.H.); (O.S.); (G.B.)
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