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1
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Matsushita T, Otomi Y, Okada N, Kawanaka T, Otsuka H. 177 Lu-DOTATATE Uptake in the Lungs of a Patient With COVID-19 Pneumonia. Clin Nucl Med 2024; 49:877-878. [PMID: 38968595 DOI: 10.1097/rlu.0000000000005324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2024]
Abstract
ABSTRACT A 76-year-old woman with liver and bone metastasis of a duodenal neuroendocrine tumor received peptide receptor radionuclide therapy with 177 Lu-DOTATATE. Scintigraphy with SPECT/CT performed 4 days after the treatment demonstrated 177 Lu-DOTATATE uptake as multifocal ground glass opacities in the bilateral lungs. This uptake was considered to be due to COVID-19 pneumonia because the patient was infected with the virus 7 days prior to the treatment. The lung opacities became smaller, showing a decreased uptake, 2 months later, after the second treatment. 177 Lu-DOTATATE may be taken up during the active phase of COVID-19 pneumonia.
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Affiliation(s)
- Tomoki Matsushita
- From the Department of Radiology, Tokushima University Hospital, Tokushima, Japan
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2
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Vrachliotis A, Gaitanis A, Protonotarios NE, Kastis GA, Costaridou L. Noninvasive Quantification of Glucose Metabolism in Mice Myocardium Using the Spline Reconstruction Technique. J Imaging 2024; 10:170. [PMID: 39057741 PMCID: PMC11278115 DOI: 10.3390/jimaging10070170] [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: 05/20/2024] [Revised: 06/25/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024] Open
Abstract
The spline reconstruction technique (SRT) is a fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The purpose of this study was to compare the SRT, filtered back-projection (FBP), and the Tera-Tomo 3D algorithm for various iteration numbers, using small-animal dynamic PET data obtained from a Mediso nanoScan® PET/CT scanner. For this purpose, Patlak graphical kinetic analysis was employed to noninvasively quantify the myocardial metabolic rate of glucose (MRGlu) in seven male C57BL/6 mice (n=7). All analytic reconstructions were performed via software for tomographic image reconstruction. The analysis of all PET-reconstructed images was conducted with PMOD software (version 3.506, PMOD Technologies LLC, Fällanden, Switzerland) using the inferior vena cava as the image-derived input function. Statistical significance was determined by employing the one-way analysis of variance test. The results revealed that the differences between the values of MRGlu obtained via SRT versus FBP, and the variants of he Tera-Tomo 3D algorithm were not statistically significant (p > 0.05). Overall, the SRT appears to perform similarly to the other algorithms investigated, providing a valid alternative analytic method for preclinical dynamic PET studies.
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Affiliation(s)
- Alexandros Vrachliotis
- Department of Medical Physics, School of Medicine, University of Patras, 26504 Patras, Greece; (A.V.); (L.C.)
- Clinical, Experimental Surgery & Translational Research, Biomedical Research Foundation (BRFAA), Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece;
| | - Anastasios Gaitanis
- Clinical, Experimental Surgery & Translational Research, Biomedical Research Foundation (BRFAA), Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece;
| | - Nicholas E. Protonotarios
- Mathematics Research Center, Academy of Athens, 11527 Athens, Greece;
- Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, National Center for Scientific Research “Demokritos”, 15341 Athens, Greece
| | - George A. Kastis
- Mathematics Research Center, Academy of Athens, 11527 Athens, Greece;
- Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, National Center for Scientific Research “Demokritos”, 15341 Athens, Greece
| | - Lena Costaridou
- Department of Medical Physics, School of Medicine, University of Patras, 26504 Patras, Greece; (A.V.); (L.C.)
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3
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Hamsley S, Pour-Ghaz I, Alkhatib D, Norman H, Kombathula R, Nayyar M, McCaslin DA, Khouzam RN, Yedlapati N, Dalal A. Novel Cardiovascular and Pulmonary Findings in the Noninvasive Ischemic Assessment of Patients With Coronavirus 2019 (COVID-19). Curr Probl Cardiol 2024; 49:102047. [PMID: 37640180 DOI: 10.1016/j.cpcardiol.2023.102047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 08/23/2023] [Indexed: 08/31/2023]
Abstract
In the past several years, the coronavirus pandemic has introduced multiple medical disciplines to various new forms of disease previously unknown and has shown us a unique presentation of already existing diseases. We continue to understand the long-term effects of the pandemic on the population's health and continue to find new unique features previously unknown. This paper presents the unique feature of lung uptake abnormalities discovered on nuclear stress testing for cardiac perfusion defects, a consistent finding in multiple individuals with recent COVID-19 or ongoing infection.
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Affiliation(s)
- Susanna Hamsley
- College of Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - Issa Pour-Ghaz
- Division of Cardiovascular Diseases, Department of Internal Medicine, University of Tennessee Health Science Center, Memphis, TN.
| | - Deya Alkhatib
- Division of Cardiovascular Diseases, Department of Internal Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - Hallie Norman
- Department of Internal Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - Rachana Kombathula
- Department of Internal Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - Mannu Nayyar
- Division of Cardiovascular Diseases, Department of Internal Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - David A McCaslin
- Methodist Le Bonheur Healthcare, Sutherland Cardiology, Memphis, TN
| | - Rami N Khouzam
- Heart and Vascular Care, Grand Strand Medical Center, Myrtle Beach, SC
| | - Neeraja Yedlapati
- Division of Cardiovascular Diseases, Department of Internal Medicine, University of Tennessee Health Science Center, Memphis, TN
| | - Ajay Dalal
- Methodist Le Bonheur Healthcare, Sutherland Cardiology, Memphis, TN
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Pezzutti DL, Makary MS. Role of Imaging in Diagnosis and Management of COVID-19: Evidence-Based Approaches. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1457:237-246. [PMID: 39283430 DOI: 10.1007/978-3-031-61939-7_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2025]
Abstract
Imaging has been demonstrated to play a crucial role in both the diagnosis and management of COVID-19. Depending on resources, pre-test probability, and risk factors for severe disease progression, real-time polymerase chain reaction (RT-PCR) testing may be followed by chest radiography (CXR) or chest computed tomography (CT) to further aid in diagnosis or excluding COVID-19 disease. SARS-CoV-2 has been shown not only to pathologically impact the pulmonary system, but also the cardiovascular, gastrointestinal, and neurological systems to name a few. Imaging has again proven useful in further investigating and managing extrapulmonary disease, with the use of echocardiogram, CT angiography of the cardiovascular and cerebrovascular structures, MRI of the brain, as well as ultrasound of the abdomen and CT of the abdomen and pelvis proving particularly useful. Research in artificial intelligence and its application in the diagnosis of COVID-19 and disease severity prediction is underway, and point-of-care ultrasound is an emerging bedside technique that may allow for more efficient and timely diagnosis of COVID-19.
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Affiliation(s)
- Dante L Pezzutti
- Department of Radiology, The Ohio State University Wexner Medical Center, 395 W. 12th Ave, 4th Floor, Columbus, OH, 43210, USA
| | - Mina S Makary
- Department of Radiology, The Ohio State University Wexner Medical Center, 395 W. 12th Ave, 4th Floor, Columbus, OH, 43210, USA.
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5
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Wang Y, Nardo L, Spencer BA, Abdelhafez YG, Li EJ, Omidvari N, Chaudhari AJ, Badawi RD, Jones T, Cherry SR, Wang G. Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of Coronavirus Disease 2019 Recovery. J Nucl Med 2023; 64:1821-1830. [PMID: 37591539 PMCID: PMC10626370 DOI: 10.2967/jnumed.123.265723] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/05/2023] [Indexed: 08/19/2023] Open
Abstract
Conventional whole-body static 18F-FDG PET imaging provides a semiquantitative evaluation of overall glucose metabolism without insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods: The study included 13 healthy subjects and 12 recovering COVID-19 subjects within 8 wk of confirmed diagnosis. Each subject had a 1-h dynamic 18F-FDG scan on the uEXPLORER total-body PET/CT system. Semiquantitative SUV and the SUV ratio relative to blood (SUVR) were calculated for different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify the microparametric blood-to-tissue 18F-FDG delivery rate [Formula: see text] and the phosphorylation rate k 3, as well as the macroparametric 18F-FDG net influx rate ([Formula: see text]). Statistical tests were performed to examine differences between healthy subjects and recovering COVID-19 subjects. The effect of COVID-19 vaccination was also investigated. Results: We detected no significant difference in lung SUV but significantly higher lung SUVR and [Formula: see text] in COVID-19 recovery, indicating improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k 3 but not with [Formula: see text], which suggests that glucose phosphorylation, rather than glucose delivery, drives the observed difference of glucose metabolism. Meanwhile, there was no or little difference in bone marrow 18F-FDG metabolism measured with SUV, SUVR, and [Formula: see text] but a significantly higher bone marrow [Formula: see text] in the COVID-19 group, suggesting a difference in glucose delivery. Vaccinated COVID-19 subjects had a lower lung [Formula: see text] and a higher spleen [Formula: see text] than unvaccinated COVID-19 subjects. Conclusion: Higher lung glucose metabolism and bone marrow glucose delivery were observed with total-body multiparametric 18F-FDG PET in recovering COVID-19 subjects than in healthy subjects, implying continued inflammation during recovery. Vaccination demonstrated potential protection effects. Total-body multiparametric PET of 18F-FDG can provide a more sensitive tool and more insights than conventional whole-body static 18F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.
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Affiliation(s)
- Yiran Wang
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California;
- Department of Biomedical Engineering, University of California, Davis, Davis, California; and
| | - Lorenzo Nardo
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
| | - Benjamin A Spencer
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
- Department of Biomedical Engineering, University of California, Davis, Davis, California; and
| | - Yasser G Abdelhafez
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
- Nuclear Medicine Unit, South Egypt Cancer Institute, Assiut University, Assiut, Egypt
| | - Elizabeth J Li
- Department of Biomedical Engineering, University of California, Davis, Davis, California; and
| | - Negar Omidvari
- Department of Biomedical Engineering, University of California, Davis, Davis, California; and
| | - Abhijit J Chaudhari
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
| | - Ramsey D Badawi
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
- Department of Biomedical Engineering, University of California, Davis, Davis, California; and
| | - Terry Jones
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
| | - Simon R Cherry
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
- Department of Biomedical Engineering, University of California, Davis, Davis, California; and
| | - Guobao Wang
- Department of Radiology, Davis Medical Center, University of California, Sacramento, California
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6
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Wang Y, Nardo L, Spencer BA, Abdelhafez YG, Li EJ, Omidvari N, Chaudhari AJ, Badawi RD, Jones T, Cherry SR, Wang G. Total-Body Multiparametric PET Quantification of 18 F-FDG Delivery and Metabolism in the Study of COVID-19 Recovery. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.26.23287673. [PMID: 37034643 PMCID: PMC10081414 DOI: 10.1101/2023.03.26.23287673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/23/2023]
Abstract
Conventional whole-body 18 F-FDG PET imaging provides a semi-quantitative evaluation of overall glucose metabolism without gaining insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18 F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods The study included thirteen healthy subjects and twelve recovering COVID-19 subjects within eight weeks of confirmed diagnosis. Each subject had a dynamic 18 F-FDG scan on the uEXPLORER total-body PET/CT system for one hour. Semiquantitative standardized uptake value (SUV) and SUV ratio relative to blood (SUVR) were calculated for regions of interest (ROIs) in different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify microparametric rate constants K 1 and k 3 that characterize 18 F-FDG blood-to-tissue delivery and intracellular phosphorylation, respectively, and a macroparameter K i that represents 18 F-FDG net influx rate. Statistical tests were performed to examine differences between the healthy controls and recovering COVID-19 subjects. Impact of COVID-19 vaccination was investigated. We further generated parametric images to confirm the ROI-based analysis. Results We detected no significant difference in lung SUV but significantly higher lung SUVR and K i in the recovering COVID-19 subjects, indicating an improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k 3 , but not with the delivery rate K 1 , which suggests it is glucose phosphorylation, not glucose delivery, that drives the observed difference of glucose metabolism in the lungs. Meanwhile, there was no or little difference in bone marrow metabolism measured with SUV, SUVR and K i , but a significant increase in bone-marrow 18 F-FDG delivery rate K 1 in the COVID-19 group ( p < 0.05), revealing a difference of glucose delivery in this immune-related organ. The observed differences were lower or similar in vaccinated COVID-19 subjects as compared to unvaccinated ones. The organ ROI-based findings were further supported by parametric images. Conclusions Higher lung glucose metabolism and bone-marrow glucose delivery were observed with total-body multiparametric 18 F-FDG PET in recovering COVID-19 subjects as compared to healthy subjects, which suggests continued inflammation due to COVID-19 during the early stages of recovery. Total-body multiparametric PET of 18 F-FDG delivery and metabolism can provide a more sensitive tool and more insights than conventional static whole-body 18 F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.
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Affiliation(s)
- Yiran Wang
- Department of Radiology, University of California Davis Medical Center
- Department of Biomedical Engineering, University of California, Davis
| | - Lorenzo Nardo
- Department of Radiology, University of California Davis Medical Center
| | - Benjamin A. Spencer
- Department of Radiology, University of California Davis Medical Center
- Department of Biomedical Engineering, University of California, Davis
| | - Yasser G. Abdelhafez
- Department of Radiology, University of California Davis Medical Center
- Nuclear Medicine Unit, South Egypt Cancer Institute, Assiut University, Egypt
| | - Elizabeth J. Li
- Department of Biomedical Engineering, University of California, Davis
| | - Negar Omidvari
- Department of Biomedical Engineering, University of California, Davis
| | | | - Ramsey D. Badawi
- Department of Radiology, University of California Davis Medical Center
- Department of Biomedical Engineering, University of California, Davis
| | - Terry Jones
- Department of Radiology, University of California Davis Medical Center
| | - Simon R. Cherry
- Department of Radiology, University of California Davis Medical Center
- Department of Biomedical Engineering, University of California, Davis
| | - Guobao Wang
- Department of Radiology, University of California Davis Medical Center
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7
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COVID-19 diagnostic approaches with an extensive focus on computed tomography in accurate diagnosis, prognosis, staging, and follow-up. Pol J Radiol 2023; 88:e53-e64. [PMID: 36819223 PMCID: PMC9907165 DOI: 10.5114/pjr.2023.124597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 10/12/2022] [Indexed: 02/10/2023] Open
Abstract
Although a long time has passed since its outbreak, there is currently no specific treatment for COVID-19, and it seems that the most appropriate strategy to combat this pandemic is to identify and isolate infected individuals. Various clinical diagnosis methods such as molecular techniques, serologic assays, and imaging techniques have been developed to identify suspected patients. Although reverse transcription-quantitative PCR (RT-qPCR) has emerged as a reference standard method for diagnosis of SARS-CoV-2, the high rate of false-negative results and limited supplies to meet current demand are the main shortcoming of this technique. Based on a comprehensive literature review, imaging techniques, particularly computed tomography (CT), show an acceptable level of sensitivity in the diagnosis and follow-up of COVID-19. Indeed, because lung infection or pneumonia is a common complication of COVID-19, the chest CT scan can be an alternative testing method in the early diagnosis and treatment assessment of the disease. In this review, we summarize all the currently available frontline diagnostic tools for the detection of SARS-CoV-2-infected individuals and highlight the value of chest CT scan in the diagnosis, prognosis, staging, management, and follow-up of infected patients.
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8
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Minamimoto R. Oncology and cardiology positron emission tomography/computed tomography faced with COVID-19: A review of available literature data. Front Med (Lausanne) 2022; 9:1052921. [PMID: 36341267 PMCID: PMC9626818 DOI: 10.3389/fmed.2022.1052921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 10/07/2022] [Indexed: 09/07/2024] Open
Abstract
The COVID-19 pandemic has forced people to significantly change their lifestyles and attitudes, and has greatly burdened healthcare delivery systems worldwide. The redistribution of the medical delivery system to maintain normal medical care while responding generously to COVID-19 is a continuing challenge that weighs heavily on medical institutions. Among imaging modalities, chest X-rays and computed tomography (CT) examinations have clearly made a large contribution to treatment of COVID-19. In contrast, it is difficult to express the standpoint of nuclear medicine examinations in a straightforward manner, as the greatest emphasis in this modality has been on how necessary medical care can continue to be provided. Many clinical reports of nuclear medicine examinations related to COVID-19 have been published, and knowledge continues to accumulate. This review provides a summary of the current state of oncology and cardiology positron emission tomography (PET) examinations related to COVID-19, and includes preparation of the nuclear medicine department, trends in PET examinations, specific imaging findings on 18F-fluorodeoxyglucose (FDG) PET/CT, imaging of complications of COVID-19, PET tracers other than FDG, and the effects of vaccines on PET imaging findings.
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Affiliation(s)
- Ryogo Minamimoto
- Division of Nuclear Medicine, National Center for Global Health and Medicine, Tokyo, Japan
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9
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Dhingra VK, Khan D, Kumar R, Basu S. Nonmalignant Thoracic Disorders: An Appraisal of Fluorodeoxyglucose and Non-fluorodeoxyglucose PET/Computed Tomography Applications. PET Clin 2022; 17:495-515. [PMID: 35717104 DOI: 10.1016/j.cpet.2022.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
PET/computed tomography (CT) with fluorodeoxyglucose and nonfluorodeoxyglucose PET tracers has established itself in the management of malignant disorders. Its role in the assessment of nonmalignant conditions, such as infectious and noninfectious inflammatory diseases and other benign conditions, has emerged independently and alongside its role being evaluated in malignancy and continues to evolve. It is evident that PET/CT has the potential to play a significant role in various nonmalignant disorders of the thorax. This review highlights current developments and areas where PET/CT has a potential to impact the clinical management of nonmalignant thoracic conditions with special focus on nonfluorodeoxyglucose tracers.
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Affiliation(s)
- Vandana Kumar Dhingra
- Department of Nuclear Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand 249203, India
| | - Dikhra Khan
- Department of Nuclear Medicine, All India Institute of Medical Sciences, Sri Aurobindo Marg, Ansari Nagar, Ansari Nagar East, New Delhi, Delhi 110029, India
| | - Rakesh Kumar
- Department of Nuclear Medicine, All India Institute of Medical Sciences, Sri Aurobindo Marg, Ansari Nagar, Ansari Nagar East, New Delhi, Delhi 110029, India
| | - Sandip Basu
- Radiation Medicine Centre (B.A.R.C), Tata Memorial Hospital Annexe, Jerbai Wadia Road, Parel, Mumbai, Maharashtra 400012, India; Homi Bhabha National Institute, 2nd floor, BARC Training School Complex, Anushaktinagar, Mumbai, Maharashtra 400094, India.
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10
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Review of Thoracic Imaging Manifestations of COVID-19 and Other Pathologic Coronaviruses. Radiol Clin North Am 2022; 60:359-369. [PMID: 35534124 PMCID: PMC8747969 DOI: 10.1016/j.rcl.2022.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an easily transmissible coronavirus that emerged in late 2019 and has caused a global pandemic characterized by acute respiratory disease named coronavirus disease 2019 (COVID-19). Diagnostic imaging can be helpful as a complementary tool in supporting the diagnosis of COVID-19 and identifying alternative pathology. This article presents an overview of acute and postacute imaging findings in COVID-19.
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11
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Matsui J, Kandathil A, Peng F. FDG PET/CT findings and post-treatment changes of COVID-19 pneumonia in a patient with lymphoma: A case report. Mol Clin Oncol 2022; 16:56. [PMID: 35111322 PMCID: PMC8771307 DOI: 10.3892/mco.2021.2489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 12/08/2021] [Indexed: 11/05/2022] Open
Abstract
A 29-year-old male with a history of Hodgkin's lymphoma presented for evaluation of response to chemotherapy with positron emission tomography/computed tomography using fluorine-18-fluoro-2-deoxy-d-glucose (18F-FDG PET/CT). Follow-up 18F-FDG PET/CT imaging demonstrated resolution of previously noted FDG avid axillary lymphadenopathy. However, multiple opacities with increased FDG uptake were noted in the lungs bilaterally, which were suspicious for pulmonary infection, including viral pneumonia. The patient tested positive for coronavirus disease 2019 (COVID-19) virus infection by reverse transcription-polymerase chain reaction (RT-PCR). Additional cycles of chemotherapy were delayed until the patient became negative for COVID-19 virus infection on follow-up RT-PCR test 2 weeks later. The patient received two additional cycles of chemotherapy. Follow-up 18F-FDG PET/CT post chemotherapy demonstrated a decrease in the size of the previously seen mediastinal lymphadenopathy, reduction of FDG uptake by the previously seen mediastinal lymphadenopathy, and reduction of FDG uptake by the previously seen pulmonary opacities, at 2 months after COVID-19 diagnosis. The findings of this case report demonstrated the importance of recognition of pulmonary abnormalities caused by COVID-19 pneumonia on 18F-FDG PET/CT imaging for clinical management of patients with lymphoma.
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Affiliation(s)
- Joy Matsui
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9140, USA
| | - Asha Kandathil
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9140, USA
| | - Fangyu Peng
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9140, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX 75390-9140, USA
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12
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Protonotarios NE, Katsamenis I, Sykiotis S, Dikaios N, Kastis GA, Chatziioannou SN, Metaxas M, Doulamis N, Doulamis A. A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging. Biomed Phys Eng Express 2022; 8. [PMID: 35144242 DOI: 10.1088/2057-1976/ac53bd] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 02/10/2022] [Indexed: 11/12/2022]
Abstract
Over the past few years, positron emission tomography/computed tomography (PET/CT) imaging for computer-aided diagnosis has received increasing attention. Supervised deep learning architectures are usually employed for the detection of abnormalities, with anatomical localization, especially in the case of CT scans. However, the main limitations of the supervised learning paradigm include (i) large amounts of data required for model training, and (ii) the assumption of fixed network weights upon training completion, implying that the performance of the model cannot be further improved after training. In order to overcome these limitations, we apply a few-shot learning (FSL) scheme. Contrary to traditional deep learning practices, in FSL the model is provided with less data during training. The model then utilizes end-user feedback after training to constantly improve its performance. We integrate FSL in a U-Net architecture for lung cancer lesion segmentation on PET/CT scans, allowing for dynamic model weight fine-tuning and resulting in an online supervised learning scheme. Constant online readjustments of the model weights according to the user's feedback, increase the detection and classification accuracy, especially in cases where low detection performance is encountered. Our proposed method is validated on the Lung-PET-CT-DX TCIA database. PET/CT scans from 87 patients were included in the dataset and were acquired 60 minutes after intravenous18F-FDG injection. Experimental results indicate the superiority of our approach compared to other state of the art methods.
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Affiliation(s)
- Nicholas E Protonotarios
- Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge, University of Cambridge, Cambridge, CB3 0WA, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Iason Katsamenis
- School of Rural and Surveying Engineering, National Technical University of Athens, 9, Heroon Polytechniou, Zografou, Attica, 157 73, GREECE
| | - Stavros Sykiotis
- School of Rural and Surveying Engineering, National Technical University of Athens, 9, Heroon Polytechniou, Zografou, Attica, 157 73, GREECE
| | - Nikolaos Dikaios
- Mathematics Research Center, Academy of Athens, 4, Soranou Efesiou, Athens, 115 27, GREECE
| | - George Anthony Kastis
- Mathematics Research Center, Academy of Athens, 4, Soranou Efesiou, Athens, Attica, 115 27, GREECE
| | - Sofia N Chatziioannou
- PET/CT, Biomedical Research Foundation of the Academy of Athens, 4, Soranou Efesiou, Athens, Attica, 115 27, GREECE
| | - Marinos Metaxas
- PET/CT, Biomedical Research Foundation of the Academy of Athens, 4, Soranou Efesiou, Athens, Attica, 115 27, GREECE
| | - Nikolaos Doulamis
- School of Rural and Surveying Engineering, National Technical University of Athens, 9, Heroon Polytechniou, Zografou, Attica, 157 73, GREECE
| | - Anastasios Doulamis
- School of Rural and Surveying Engineering, National Technical University of Athens, 9, Heroon Polytechniou, Zografou, Attica, 157 73, GREECE
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13
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Subesinghe M, Bhuva S, Dunn JT, Hammers A, Cook GJ, Barrington SF, Fischer BM. A case-control evaluation of pulmonary and extrapulmonary findings of incidental asymptomatic COVID-19 infection on FDG PET-CT. Br J Radiol 2022; 95:20211079. [PMID: 34930037 PMCID: PMC8822569 DOI: 10.1259/bjr.20211079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/02/2021] [Accepted: 12/13/2021] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES To describe the findings of incidental asymptomatic COVID-19 infection on FDG PET-CT using a case-control design. METHODS Incidental pulmonary findings suspicious of asymptomatic COVID-19 infection on FDG PET-CT were classified as a confirmed (positive RT-PCR test) or suspected case (no/negative RT-PCR test). Control cases were identified using a 4:1 control:case ratio. Pulmonary findings were re-categorised by two reporters using the BSTI classification. SUV metrics in ground glass opacification (GGO)/consolidation (where present), background lung, intrathoracic nodes, liver, spleen and bone marrow were measured. RESULTS 7/9 confirmed and 11/15 suspected cases (COVID-19 group) were re-categorised as BSTI 1 (classic/probable COVID-19) or BSTI 2 (indeterminate COVID-19); 0/96 control cases were categorised as BSTI 1. Agreement between two reporters using the BSTI classification was almost perfect (weighted κ = 0.94). SUVmax GGO/consolidation (5.1 vs 2.2; p < 0.0001) and target-to-background ratio, normalised to liver SUVmean (2.4 vs 1.0; p < 0.0001) were higher in the BSTI 1 & 2 group vs BSTI 3 (non-COVID-19) cases. SUVmax GGO/consolidation discriminated between the BSTI 1 & 2 group vs BSTI 3 (non-COVID-19) cases with high accuracy (AUC = 0.93). SUV metrics were higher (p < 0.05) in the COVID-19 group vs control cases in the lungs, intrathoracic nodes and spleen. CONCLUSION Asymptomatic COVID-19 infection on FDG PET-CT is characterised by bilateral areas of FDG avid (intensity > x2 liver SUVmean) GGO/consolidation and can be identified with high interobserver agreement using the BSTI classification. There is generalised background inflammation within the lungs, intrathoracic nodes and spleen. ADVANCES IN KNOWLEDGE Incidental asymptomatic COVID-19 infection on FDG PET-CT, characterised by bilateral areas of ground glass opacification and consolidation, can be identified with high reproducibility using the BSTI classification. The intensity of associated FDG uptake (>x2 liver SUVmean) provides high discriminative ability in differentiating such cases from pulmonary findings in a non-COVID-19 pattern. Asymptomatic COVID-19 infection causes a generalised background inflammation within the mid-lower zones of the lungs, hilar and central mediastinal nodal stations, and spleen on FDG PET-CT.
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14
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Eshet Y, Avigdor A, Kedmi M, Tau N. Imaging of Hematological Patients in the Era of COVID-19. Acta Haematol 2022; 145:267-274. [PMID: 35100592 PMCID: PMC9059043 DOI: 10.1159/000522323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 01/23/2022] [Indexed: 11/19/2022]
Abstract
The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulted in changes in management and imaging routines for patients with hematological malignancies. Treating physicians had to familiarize themselves with a new disease, with distinct imaging manifestations, sometimes overlapping with other infections prevalent in this patient population. In some aspects, infected hematological patients might exhibit a different disease course, and routine imaging in asymptomatic hematological patients may result in unexpected COVID-19 findings, implying covert infection, that should be further explored. Furthermore, some complications of hematological diseases and treatments may present with findings similar to COVID-19 manifestations, and treating physicians must consider both possibilities in the differential diagnosis. In this review, we aimed to present the influence the COVID-19 pandemic had on hematological malignancy imaging.
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Affiliation(s)
- Yael Eshet
- Department of Nuclear Medicine, Sheba Medical Center, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Abraham Avigdor
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Hematology Division, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Meirav Kedmi
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Hematology Division, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Noam Tau
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel
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15
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Han Y, Luo Y. Primary lung invasive adenocarcinoma misdiagnosed as infectious pneumonia in 18F-FDG PET/CT:A case report. Radiol Case Rep 2022; 17:808-811. [PMID: 35024081 PMCID: PMC8733036 DOI: 10.1016/j.radcr.2021.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 11/24/2022] Open
Abstract
A 64-year-old woman presented to our hospital with cough and a large amount of white foam sputum, F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) showed diffuse ground-glass opacities in both lungs, which was considered as infectious pneumonia. However, after ineffective anti-infection, the primary invasive mucinous adenocarcinoma was finally diagnosed. Pulmonary invasive mucinous adenocarcinoma is rare and special subtype of lung adenocarcinoma, it has a variety of imaging manifestations. When intense tracer uptake, air bronchial sign, honeycomb sign present in diffuse ground-glass opacities in F-FDG PET/CT, lung invasive mucinous adenocarcinoma should be highly suspected.
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Affiliation(s)
- Yuping Han
- Department of Nuclear Medicine, Lanzhou University Second Hospital, Lanzhou University, Lanzhou, 730030, China
| | - Yongjun Luo
- Department of Nuclear Medicine, Lanzhou University Second Hospital, Lanzhou University, Lanzhou, 730030, China
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16
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Javaid A, Saleh Y, Ahmed AI, Saad JM, Malahfji M, Al-Mallah MH. Noninvasive Imaging for Patients with COVID-19 and Acute Chest Pain. Methodist Debakey Cardiovasc J 2022; 17:5-15. [PMID: 34992719 PMCID: PMC8680163 DOI: 10.14797/mdcvj.1040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 10/15/2021] [Indexed: 12/19/2022] Open
Abstract
Acute chest pain is a common presentation in patients with COVID-19. Although noninvasive cardiac imaging modalities continue to be important cornerstones of management, the pandemic has brought forth difficult and unprecedented challenges in the provision of timely care while ensuring the safety of patients and providers. Clinical practice has adapted to these challenges, with several recommendations and societal guidelines emerging on the appropriate use of imaging modalities. In this review, we summarize the current evidence base on the use of noninvasive cardiac imaging modalities in COVID-19 patients with acute chest pain, with a focus on acute coronary syndromes.
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Affiliation(s)
- Awad Javaid
- Kirk Kerkorian School of Medicine at the University of Nevada Las Vegas School of Medicine, Las Vegas, NV, US
| | - Yehia Saleh
- Houston Methodist DeBakey Heart & Vascular Center, Houston, TX, US
| | | | - Jean Michel Saad
- Houston Methodist DeBakey Heart & Vascular Center, Houston, TX, US
| | - Maan Malahfji
- Houston Methodist DeBakey Heart & Vascular Center, Houston, TX, US
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17
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Eibschutz LS, Rabiee B, Asadollahi S, Gupta A, Assadi M, Alavi A, Gholamrezanezhad A. FDG-PET/CT of COVID-19 and Other Lung Infections. Semin Nucl Med 2022; 52:61-70. [PMID: 34246449 PMCID: PMC8216878 DOI: 10.1053/j.semnuclmed.2021.06.017] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
While not conventionally used as the first-line modality, [18F]-2-fluoro-2-deoxy-D-glucose (FDG) - positron emission tomography/computed tomography (PET/CT) can identify infection and inflammation both earlier and with higher sensitivity than anatomic imaging modalities [including chest X-ray (CXR), computed tomography (CT), and magnetic resonance imaging (MRI)]. The extent of inflammation and, conversely, recovery within the lungs, can be roughly quantified on FDG-PET/CT using maximum standardized uptake value (SUVmax) values. The Coronavirus disease 2019 (COVID-19) pandemic has highlighted the value of FDG-PET/CT in diagnosis, elucidation of acute pulmonary and extrapulmonary manifestations, and long-term follow up. Similarly, many other pulmonary infections such as previously documented coronaviruses, aspergillosis, blastomycosis, candidiasis, coccidioidomycosis, cryptococcosis, histoplasmosis, mucormycosis, and typical/atypical mycobacterial infections have all been identified and characterized using FDG-PET/CT imaging. The goal of this review is to summarize the actual and potential benefits of FDG-PET/CT in the imaging of COVID-19 and other lung infections. Further research is necessary to determine the best indications and clinical applications of FDG-PET/CT, improve its specificity, and ultimately ascertain how this modality can best be utilized in the diagnostic work up of infectious pathologies.
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Affiliation(s)
- Liesl S. Eibschutz
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA
| | - Behnam Rabiee
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA,Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY
| | - Shadi Asadollahi
- Professor of Radiology, Director of Research Education, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Amit Gupta
- Department of Radiology, University Hospital Cleveland Medical Center, Cleveland, OH
| | - Majid Assadi
- Department of Nuclear Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Abass Alavi
- Professor of Radiology, Director of Research Education, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Ali Gholamrezanezhad
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA,Address reprint requests to Ali Gholamrezanezhad, MD, Department of Radiology, Division of Emergency Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo Street, Los Angeles, CA 90033
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18
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Campagnano S, Angelini F, Fonsi GB, Novelli S, Drudi FM. Diagnostic imaging in COVID-19 pneumonia: a literature review. J Ultrasound 2021; 24:383-395. [PMID: 33590456 PMCID: PMC7884066 DOI: 10.1007/s40477-021-00559-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 01/15/2021] [Indexed: 02/07/2023] Open
Abstract
In December 2019 in Wuhan (China), a bat-origin coronavirus (2019-nCoV), also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified, and the World Health Organization named the related disease COVID-19. Its most severe manifestations are pneumonia, systemic and pulmonary thromboembolism, acute respiratory distress syndrome (ARDS), and respiratory failure. A swab test is considered the gold standard for the diagnosis of COVID-19 despite the high number of false negatives. Radiologists play a crucial role in the rapid identification and early diagnosis of pulmonary involvement. Lung ultrasound (LUS) and computed tomography (CT) have a high sensitivity in detecting pulmonary interstitial involvement. LUS is a low-cost and radiation-free method, which allows a bedside approach and needs disinfection of only a small contact area, so it could be particularly useful during triage and in intensive care units (ICUs). High-resolution computed tomography (HRCT) is particularly useful in evaluating disease progression or resolution, being able to identify even the smallest changes.
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Affiliation(s)
- Sarah Campagnano
- Department of Radiological, Oncological and Path Sciences, Sapienza University of Rome, Rome, Italy
| | - Flavia Angelini
- Department of Radiological, Oncological and Path Sciences, Sapienza University of Rome, Rome, Italy
| | | | - Simone Novelli
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy
| | - Francesco Maria Drudi
- Department of Radiological, Oncological and Path Sciences, Sapienza University of Rome, Rome, Italy.
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19
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Rabiee B, Eibschutz LS, Asadollahi S, Gupta A, Akhlaghpoor S, Gholamrezanezhad A. The role of imaging techniques in understanding and evaluating the long-term pulmonary effects of COVID-19. Expert Rev Respir Med 2021; 15:1525-1537. [PMID: 34730039 DOI: 10.1080/17476348.2021.2001330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Limited data exist regarding the long-term pulmonary sequelae of COVID-19. Identifying features utilizing multiple imaging modalities engenders a clearer picture of the illness's long-term consequences. AREAS COVERED This review encompasses the common pulmonary findings associated with different imaging modalities during acute and late remission stages of COVID-19 pneumonia. EXPERT OPINION Chest x-ray, a common preliminary diagnostic imaging technique, is not optimal for extended care due to limited tissue contrast resolution providing suboptimal assessment of pulmonary pathology and subtle interval changes. Ultrasound may be utilized on a case-by-case basis in certain patient populations, or in countries with limited resources. Chest CT's accessibility, high tissue contrast and spatial resolution make it the foremost modality for long-term COVID-19 follow-up. While MRI can viably monitor extrapulmonary disease due to its lack of radiation and high inherent soft-tissue contrast, it has limited pulmonary utility due to motion artifact and alveolar gas decreasing lung signal. Although 18F-FDG-PET/CT is costly and has limited specificity, it can provide molecular level data and inflammation quantification. Lung perfusion scintigraphy may also explain COVID-19 induced thromboembolic events and persistent dyspnea despite normal structural imaging and testing results. Correlating the long-term pulmonary findings of COVID-19 with each imaging modality is essential in elucidating the post-recovery course.
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Affiliation(s)
- Behnam Rabiee
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA.,Trinity Health Mid-Atlantic Nazareth Hospital, Philadelphia, PA, USA
| | - Liesl S Eibschutz
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA
| | - Shadi Asadollahi
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Amit Gupta
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Shahram Akhlaghpoor
- Department of Interventional Radiology, Pardis Noor Medical Center, Tehran, Iran
| | - Ali Gholamrezanezhad
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA
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20
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Varadarajan V, Shabani M, Ambale Venkatesh B, Lima JAC. Role of Imaging in Diagnosis and Management of COVID-19: A Multiorgan Multimodality Imaging Review. Front Med (Lausanne) 2021; 8:765975. [PMID: 34820400 PMCID: PMC8606587 DOI: 10.3389/fmed.2021.765975] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 10/04/2021] [Indexed: 01/08/2023] Open
Abstract
In this pandemic of Coronavirus disease 2019 (COVID-19), a vast proportion of healthcare resources, including imaging tools, have been dedicated to the management of affected patients; yet, the frequent reports of unknown presentations and complications of disease over time have been changing the usual standard of care and resource allocation in health centers. As of now, we have witnessed multisystemic symptoms requiring the collaboration of different clinical teams in COVID-19 patients' care. Compared to previous viral pandemics, imaging modalities are now playing an essential role in the diagnosis and management of patients. This widespread utility of imaging modalities calls for a deeper understanding of potential radiologic findings in this disease and identifying the most compatible imaging protocol with safety precautions. Although initially used for respiratory tract evaluation, imaging modalities have also been used for cardiovascular, neurologic, and gastrointestinal evaluation of patients with COVID-19. In this narrative review article, we provide multimodality and multisystemic review of imaging techniques and features that can aid in the diagnosis and management of COVID-19 patients.
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Affiliation(s)
| | | | | | - Joao A. C. Lima
- Department of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, United States
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21
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Jin C, Luo X, Qian S, Zhang K, Gao Y, Zhou R, Cen P, Xu Z, Zhang H, Tian M. Positron emission tomography in the COVID-19 pandemic era. Eur J Nucl Med Mol Imaging 2021; 48:3903-3917. [PMID: 34013405 PMCID: PMC8134823 DOI: 10.1007/s00259-021-05347-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 03/29/2021] [Indexed: 12/24/2022]
Abstract
Coronavirus disease 2019 (COVID-19) has become a major public health problem worldwide since its outbreak in 2019. Currently, the spread of COVID-19 is far from over, and various complications have roused increasing awareness of the public, calling for novel techniques to aid at diagnosis and treatment. Based on the principle of molecular imaging, positron emission tomography (PET) is expected to offer pathophysiological alternations of COVID-19 in the molecular/cellular perspectives and facilitate the clinical management of patients. A number of PET-related cases and research have been reported on COVID-19 over the past one year. This article reviews the current studies of PET in the diagnosis and treatment of COVID-19, and discusses potential applications of PET in the development of management strategy for COVID-19 patients in the pandemic era.
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Affiliation(s)
- Chentao Jin
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Xiaoyun Luo
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Shufang Qian
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Kai Zhang
- Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, Japan
| | - Yuanxue Gao
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Peili Cen
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Zhoujiao Xu
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China.
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China.
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.
| | - Mei Tian
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China.
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China.
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22
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COVID-19 and Aspiration Pneumonia: Similar Pulmonary Findings with Different Diagnoses—a Pitfall in [18F]FDG PET/CT. SN COMPREHENSIVE CLINICAL MEDICINE 2021; 3:2322-2325. [PMID: 34345767 PMCID: PMC8321507 DOI: 10.1007/s42399-021-01030-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/18/2021] [Indexed: 11/20/2022]
Abstract
Since December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a worldwide pandemic. Especially in the centers most affected by the pandemic, symptoms (such as fever, cough, myalgia, or fatigue) and/or radiological signs (such as ground-glass opacity) typically related to COVID-19 often diverted clinicians’ attention from other diseases. Despite the urgency to recognize and cure SARS-CoV-2 infection, a plethora of differential diagnoses must be considered, and other diseases must be equally and promptly treated, as described in this case report.
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23
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Churruca M, Martínez-Besteiro E, Couñago F, Landete P. COVID-19 pneumonia: A review of typical radiological characteristics. World J Radiol 2021; 13:327-343. [PMID: 34786188 PMCID: PMC8567439 DOI: 10.4329/wjr.v13.i10.327] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/08/2021] [Accepted: 09/14/2021] [Indexed: 02/06/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) was first discovered after unusual cases of severe pneumonia emerged by the end of 2019 in Wuhan (China) and was declared a global public health emergency by the World Health Organization in January 2020. The new pathogen responsible for the infection, genetically similar to the beta-coronavirus family, is known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), and the current gold standard diagnostic tool for its detection in respiratory samples is the reverse transcription-polymerase chain reaction test. Imaging findings on COVID-19 have been widely described in studies published throughout last year, 2020. In general, ground-glass opacities and consolidations, with a bilateral and peripheral distribution, are the most typical patterns found in COVID-19 pneumonia. Even though much of the literature focuses on chest computed tomography (CT) and X-ray imaging and their findings, other imaging modalities have also been useful in the assessment of COVID-19 patients. Lung ultrasonography is an emerging technique with a high sensitivity, and thus useful in the initial evaluation of SARS-CoV-2 infection. In addition, combined positron emission tomography-CT enables the identification of affected areas and follow-up treatment responses. This review intends to clarify the role of the imaging modalities available and identify the most common radiological manifestations of COVID-19.
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Affiliation(s)
- María Churruca
- Pulmonology Department, Hospital Universitario de La Princesa, Madrid 28006, Spain
| | | | - Felipe Couñago
- Department of Radiation Oncology, Hospital Universitario Quirónsalud Madrid, Madrid 28223, Spain
- Department of Radiation Oncology, Hospital La Luz, Madrid 28003, Spain
- Clinical Department, Faculty of Biomedicine,Universidad Europea de Madrid, Madrid 28670, Spain
| | - Pedro Landete
- Department of Pneumology, Hospital Universitario de la Princesa, Universidad Autónoma de Madrid, Madrid 28006, Spain
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24
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Kaur J, Kaur P. Outbreak COVID-19 in Medical Image Processing Using Deep Learning: A State-of-the-Art Review. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING : STATE OF THE ART REVIEWS 2021; 29:2351-2382. [PMID: 34690493 PMCID: PMC8525064 DOI: 10.1007/s11831-021-09667-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 10/01/2021] [Indexed: 06/13/2023]
Abstract
From the month of December-19, the outbreak of Coronavirus (COVID-19) triggered several deaths and overstated every aspect of individual health. COVID-19 has been designated as a pandemic by World Health Organization. The circumstances placed serious trouble on every country worldwide, particularly with health arrangements and time-consuming responses. The increase in the positive cases of COVID-19 globally spread every day. The quantity of accessible diagnosing kits is restricted because of complications in detecting the existence of the illness. Fast and correct diagnosis of COVID-19 is a timely requirement for the prevention and controlling of the pandemic through suitable isolation and medicinal treatment. The significance of the present work is to discuss the outline of the deep learning techniques with medical imaging such as outburst prediction, virus transmitted indications, detection and treatment aspects, vaccine availability with remedy research. Abundant image resources of medical imaging as X-rays, Computed Tomography Scans, Magnetic Resonance imaging, formulate deep learning high-quality methods to fight against the pandemic COVID-19. The review presents a comprehensive idea of deep learning and its related applications in healthcare received over the past decade. At the last, some issues and confrontations to control the health crisis and outbreaks have been introduced. The progress in technology has contributed to developing individual's lives. The problems faced by the radiologists during medical imaging techniques and deep learning approaches for diagnosing the COVID-19 infections have been also discussed.
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Affiliation(s)
- Jaspreet Kaur
- Department of Computer Engineering & Technology, Guru Nanak Dev University, Amritsar, Punjab India
| | - Prabhpreet Kaur
- Department of Computer Engineering & Technology, Guru Nanak Dev University, Amritsar, Punjab India
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25
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Chao Z, Xu W. A New General Maximum Intensity Projection Technology via the Hybrid of U-Net and Radial Basis Function Neural Network. J Digit Imaging 2021; 34:1264-1278. [PMID: 34508300 PMCID: PMC8432629 DOI: 10.1007/s10278-021-00504-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/16/2021] [Accepted: 08/05/2021] [Indexed: 11/29/2022] Open
Abstract
Maximum intensity projection (MIP) technology is a computer visualization method that projects three-dimensional spatial data on a visualization plane. According to the specific purposes, the specific lab thickness and direction can be selected. This technology can better show organs, such as blood vessels, arteries, veins, and bronchi and so forth, from different directions, which could bring more intuitive and comprehensive results for doctors in the diagnosis of related diseases. However, in this traditional projection technology, the details of the small projected target are not clearly visualized when the projected target is not much different from the surrounding environment, which could lead to missed diagnosis or misdiagnosis. Therefore, it is urgent to develop a new technology that can better and clearly display the angiogram. However, to the best of our knowledge, research in this area is scarce. To fill this gap in the literature, in the present study, we propose a new method based on the hybrid of convolutional neural network (CNN) and radial basis function neural network (RBFNN) to synthesize the projection image. We first adopted the U-net to obtain feature or enhanced images to be projected; subsequently, the RBF neural network performed further synthesis processing for these data; finally, the projection images were obtained. For experimental data, in order to increase the robustness of the proposed algorithm, the following three different types of datasets were adopted: the vascular projection of the brain, the bronchial projection of the lung parenchyma, and the vascular projection of the liver. In addition, radiologist evaluation and five classic metrics of image definition were implemented for effective analysis. Finally, compared to the traditional MIP technology and other structures, the use of a large number of different types of data and superior experimental results proved the versatility and robustness of the proposed method.
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Affiliation(s)
- Zhen Chao
- College of Artificial Intelligence and Big Data for Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Huaiyin District, 6699 Qingdao Road, Jinan, 250117, Shandong, China.
- Research Lab for Medical Imaging and Digital Surgery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
- Department of Radiation Convergence Engineering, College of Health Science, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwon, 26493, South Korea.
| | - Wenting Xu
- Department of Radiation Convergence Engineering, College of Health Science, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwon, 26493, South Korea
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Perrone F, Balbi M, Casartelli C, Buti S, Milanese G, Sverzellati N, Bersanelli M. Differential diagnosis of COVID-19 at the chest computed tomography scan: A review with special focus on cancer patients. World J Radiol 2021; 13:243-257. [PMID: 34567434 PMCID: PMC8422906 DOI: 10.4329/wjr.v13.i8.243] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 05/18/2021] [Accepted: 08/02/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Given the several radiological features shared by coronavirus disease 2019 pneumonia and other infective or non-infective diseases with lung involvement, the differential diagnosis is often tricky, and no unequivocal tool exists to help the radiologist in the proper diagnosis. Computed tomography is considered the gold standard in detecting pulmonary illness caused by severe acute respiratory syndrome coronavirus 2.
AIM To conduct a systematic review including the available studies evaluating computed tomography similarities and discrepancies between coronavirus disease 2019 pneumonia and other pulmonary illness, then providing a discussion focus on cancer patients.
METHODS Using pertinent keywords, we performed a systematic review using PubMed to select relevant studies published until October 30, 2020.
RESULTS Of the identified 133 studies, 18 were eligible and included in this review.
CONCLUSION Ground-glass opacity and consolidations are the most common computed tomography lesions in coronavirus disease 2019 pneumonia and other respiratory diseases. Only two studies included cancer patients, and the differential diagnosis with early lung cancer and radiation pneumonitis was performed. A single lesion associated with pleural effusion and lymphadenopathies in lung cancer and the onset of the lesions in the radiation field in the case of radiation pneumonitis allowed the differential diagnosis. Nevertheless, the studies were heterogeneous, and the type and prevalence of lesions, distributions, morphology, evolution, and additional signs, together with epidemiological, clinical, and laboratory findings, are crucial to help in the differential diagnosis.
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Affiliation(s)
- Fabiana Perrone
- Medical Oncology Unit, University Hospital of Parma, Parma 43126, Italy
- Department of Medicine and Surgery, University of Parma, Parma 43126, Italy
| | - Maurizio Balbi
- Department of Surgical Sciences, Institute of Diagnostic and Interventional Radiology, University of Parma, Parma 43126, Italy
| | - Chiara Casartelli
- Medical Oncology Unit, University Hospital of Parma, Parma 43126, Italy
- Department of Medicine and Surgery, University of Parma, Parma 43126, Italy
| | - Sebastiano Buti
- Medical Oncology Unit, University Hospital of Parma, Parma 43126, Italy
| | - Gianluca Milanese
- Department of Surgical Sciences, Institute of Diagnostic and Interventional Radiology, University of Parma, Parma 43126, Italy
| | - Nicola Sverzellati
- Department of Surgical Sciences, Institute of Diagnostic and Interventional Radiology, University of Parma, Parma 43126, Italy
| | - Melissa Bersanelli
- Medical Oncology Unit, University Hospital of Parma, Parma 43126, Italy
- Department of Medicine and Surgery, University of Parma, Parma 43126, Italy
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Fang H, Younis MH, Cai W, Lan X, Jiang D. New wine in old bottles: 68Ga-PSMA-11 PET/CT reveals COVID-19 in patients with prostate cancer. AMERICAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 2021; 11:332-336. [PMID: 34513287 PMCID: PMC8414401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 07/25/2021] [Indexed: 06/13/2023]
Abstract
The COVID-19 pandemic continues to influence every aspect of human life across the globe. It was reported that vascular angiogenesis of COVID-19 was elevated in patients with equally severe influenza virus infection. In this issue of AJNMMI, Farolfi et al. reported that there was lung uptake not related to prostate cancer in almost all COVID-19 patients who performed 68Ga-PSMA-11 PET/CT scans and most of the lung uptake lesions were matched with typical CT patterns of COVID-19. With the advantages of having various tracers for whole-body imaging, PET provides opportunities to study the mechanism of COVID-19 from different aspects and obtain patterns of extrapulmonary lesions in COVID-19, which helps explore more effective treatments for the patients. This case series opened the door to many future studies. Furthermore, such a multi-national/multi-institutional collaboration in the pandemic truly encouraged us that science is indeed without borders.
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Affiliation(s)
- Hanyi Fang
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhan 430022, Hubei, China
- Hubei Key Laboratory of Molecular ImagingWuhan 430022, Hubei, China
| | - Muhsin H Younis
- Departments of Radiology and Medical Physics, University of Wisconsin-MadisonMadison 53705, WI, USA
| | - Weibo Cai
- Departments of Radiology and Medical Physics, University of Wisconsin-MadisonMadison 53705, WI, USA
| | - Xiaoli Lan
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhan 430022, Hubei, China
- Hubei Key Laboratory of Molecular ImagingWuhan 430022, Hubei, China
| | - Dawei Jiang
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhan 430022, Hubei, China
- Hubei Key Laboratory of Molecular ImagingWuhan 430022, Hubei, China
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Rivera-Sotelo N, Vargas-Del-Angel RG, Ternovoy SK, Roldan-Valadez E. Global research trends in COVID-19 with MRI and PET/CT: a scoping review with bibliometric and network analyses. Clin Transl Imaging 2021; 9:625-639. [PMID: 34414137 PMCID: PMC8364406 DOI: 10.1007/s40336-021-00460-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 08/04/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVE To identify and evaluate the indexed studies that allow us to understand the implications of imaging studies in MRI and PET/CT related to COVID-19 research. METHODS Scoping review. Articles in PubMed, Scopus, and Web of Science (WoS) were scanned from 2019 to 2021 with COVID-19, MRI, and PET-CT as keywords. EndNote software and manual checking removed the duplicated references. Our assessment includes citation, bibliometric, keyword network, and statistical analyses using descriptive statistics and correlations. Highlighted variables were publication year, country, journals, and authorship. RESULTS Only 326 papers were included. The most cited article reached 669 cites; this number represented 21.71% of 3081 citations. The top-15 cited authors received 1787 citations, which represented 58% of the total cites. These authors had affiliations from ten countries (Belgium, China, France, Italy, Japan, Spain, Sweden, Turkey, United Kingdom (UK), and the USA). The top-30 journals were cited 2762 times, representing 89.65% of the total cites. Only five journals were cited more than 100 times; Int J Infect Dis had the most significant number of citations (674). Some of the unexpected keywords were encephalitis, stroke, microbleeds, myocarditis. CONCLUSION COVID-19 pandemic is still spreading worldwide, and the knowledge about its different facets continues advancing. MRI and PET/CT are being used in more than 50% of the selected studies; research trends span seven categories, no only the diagnostic but others like socio-economic impact and pathogenesis Developed countries had an advantage by having hospitals with more resources, including MRI and PET/CT facilities in the same institution to supplement basic assessment in patients with COVID-19. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40336-021-00460-x.
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Affiliation(s)
- Nathaly Rivera-Sotelo
- Directorate of Research, Hospital General de Mexico “Dr Eduardo Liceaga”, 06720 Mexico City, Mexico
| | | | - Sergey K. Ternovoy
- Department of Radiology, A.L. Myasnikov Research Institute of Clinical Cardiology of National Medical Research Center, Moscow, Russia
- Department of Radiology, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119992 Moscow, Russia
| | - Ernesto Roldan-Valadez
- Directorate of Research, Hospital General de Mexico “Dr Eduardo Liceaga”, 06720 Mexico City, Mexico
- Department of Radiology, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119992 Moscow, Russia
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Nabavi S, Ejmalian A, Moghaddam ME, Abin AA, Frangi AF, Mohammadi M, Rad HS. Medical imaging and computational image analysis in COVID-19 diagnosis: A review. Comput Biol Med 2021; 135:104605. [PMID: 34175533 PMCID: PMC8219713 DOI: 10.1016/j.compbiomed.2021.104605] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 06/21/2021] [Accepted: 06/21/2021] [Indexed: 12/11/2022]
Abstract
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The disease presents with symptoms such as shortness of breath, fever, dry cough, and chronic fatigue, amongst others. The disease may be asymptomatic in some patients in the early stages, which can lead to increased transmission of the disease to others. This study attempts to review papers on the role of imaging and medical image computing in COVID-19 diagnosis. For this purpose, PubMed, Scopus and Google Scholar were searched to find related studies until the middle of 2021. The contribution of this study is four-fold: 1) to use as a tutorial of the field for both clinicians and technologists, 2) to comprehensively review the characteristics of COVID-19 as presented in medical images, 3) to examine automated artificial intelligence-based approaches for COVID-19 diagnosis, 4) to express the research limitations in this field and the methods used to overcome them. Using machine learning-based methods can diagnose the disease with high accuracy from medical images and reduce time, cost and error of diagnostic procedure. It is recommended to collect bulk imaging data from patients in the shortest possible time to improve the performance of COVID-19 automated diagnostic methods.
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Affiliation(s)
- Shahabedin Nabavi
- Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran.
| | - Azar Ejmalian
- Anesthesiology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Ahmad Ali Abin
- Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran
| | - Alejandro F Frangi
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, UK
| | - Mohammad Mohammadi
- Department of Medical Physics, Royal Adelaide Hospital, Adelaide, South Australia, Australia; School of Physical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Hamidreza Saligheh Rad
- Quantitative MR Imaging and Spectroscopy Group (QMISG), Tehran University of Medical Sciences, Tehran, Iran
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Cicco S, Vacca A, Cariddi C, Carella R, Altamura G, Solimando AG, Lauletta G, Pappagallo F, Cirulli A, Stragapede A, Susca N, Grasso S, Ria R. Imaging Evaluation of Pulmonary and Non-Ischaemic Cardiovascular Manifestations of COVID-19. Diagnostics (Basel) 2021; 11:1271. [PMID: 34359355 PMCID: PMC8304239 DOI: 10.3390/diagnostics11071271] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/06/2021] [Accepted: 07/12/2021] [Indexed: 02/06/2023] Open
Abstract
Coronavirus Disease 2019 (COVID-19) has been a pandemic challenge for the last year. Cardiovascular disease is the most described comorbidity in COVID-19 patients, and it is related to the disease severity and progression. COVID-19 induces direct damage on cardiovascular system, leading to arrhythmias and myocarditis, and indirect damage due to endothelial dysfunction and systemic inflammation with a high inflammatory burden. Indirect damage leads to myocarditis, coagulation abnormalities and venous thromboembolism, Takotsubo cardiomyopathy, Kawasaki-like disease and multisystem inflammatory syndrome in children. Imaging can support the management, assessment and prognostic evaluation of these patients. Ultrasound is the most reliable and easy to use in emergency setting and in the ICU as a first approach. The focused approach is useful in management of these patients due its ability to obtain quick and focused results. This tool is useful to evaluate cardiovascular disease and its interplay with lungs. However, a detailed echocardiography evaluation is necessary in a complete assessment of cardiovascular involvement. Computerized tomography is highly sensitive, but it might not always be available. Cardiovascular magnetic resonance and nuclear imaging may be helpful to evaluate COVID-19-related myocardial injury, but further studies are needed. This review deals with different modalities of imaging evaluation in the management of cardiovascular non-ischaemic manifestations of COVID-19, comparing their use in emergency and in intensive care.
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Affiliation(s)
- Sebastiano Cicco
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Antonio Vacca
- Division of Internal Medicine, Department of Medicine, Building 8, University of Udine, I-33100 Udine, Italy;
| | - Christel Cariddi
- Anesthesiology and Intensive Care Unit, Department of Emergency and Organ Transplantation (DETO) Ospedale Policlinico, University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (C.C.); (G.A.); (S.G.)
| | - Rossella Carella
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Gianluca Altamura
- Anesthesiology and Intensive Care Unit, Department of Emergency and Organ Transplantation (DETO) Ospedale Policlinico, University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (C.C.); (G.A.); (S.G.)
| | - Antonio Giovanni Solimando
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Gianfranco Lauletta
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Fabrizio Pappagallo
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Anna Cirulli
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Assunta Stragapede
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Nicola Susca
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
| | - Salvatore Grasso
- Anesthesiology and Intensive Care Unit, Department of Emergency and Organ Transplantation (DETO) Ospedale Policlinico, University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (C.C.); (G.A.); (S.G.)
| | - Roberto Ria
- Internal Medicine Unit “Guido Baccelli”, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari Aldo Moro, Azienda Ospedaliero-Universitaria Policlinico, Piazza G. Cesare 11, I-70124 Bari, Italy; (R.C.); (A.G.S.); (G.L.); (F.P.); (A.C.); (A.S.); (N.S.); (R.R.)
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Discovery of potential imaging and therapeutic targets for severe inflammation in COVID-19 patients. Sci Rep 2021; 11:14151. [PMID: 34239034 PMCID: PMC8266867 DOI: 10.1038/s41598-021-93743-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 06/30/2021] [Indexed: 12/15/2022] Open
Abstract
The Coronavirus disease 2019 (COVID-19) has been spreading worldwide with rapidly increased number of deaths. Hyperinflammation mediated by dysregulated monocyte/macrophage function is considered to be the key factor that triggers severe illness in COVID-19. However, no specific targeting molecule has been identified for detecting or treating hyperinflammation related to dysregulated macrophages in severe COVID-19. In this study, previously published single-cell RNA-sequencing data of bronchoalveolar lavage fluid cells from thirteen COVID-19 patients were analyzed with publicly available databases for surface and imageable targets. Immune cell composition according to the severity was estimated with the clustering of gene expression data. Expression levels of imaging target molecules for inflammation were evaluated in macrophage clusters from single-cell RNA-sequencing data. In addition, candidate targetable molecules enriched in severe COVID-19 associated with hyperinflammation were filtered. We found that expression of SLC2A3, which can be imaged by [18F]fluorodeoxyglucose, was higher in macrophages from severe COVID-19 patients. Furthermore, by integrating the surface target and drug-target binding databases with RNA-sequencing data of severe COVID-19, we identified candidate surface and druggable targets including CCR1 and FPR1 for drug delivery as well as molecular imaging. Our results provide a resource in the development of specific imaging and therapy for COVID-19-related hyperinflammation.
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Abstract
Soon after reports of a novel coronavirus capable of causing severe pneumonia surfaced in late 2019, expeditious global spread of the Severe Acute Respiratory Distress Syndrome Coronavirus 2 (SARS-CoV-2) forced the World Health Organization to declare an international state of emergency. Although best known for causing symptoms of upper respiratory tract infection in mild cases and fulminant pneumonia in severe disease, Coronavirus Disease 2019 (COVID-19) has also been associated with gastrointestinal, neurologic, cardiac, and hematologic presentations. Despite concerns over poor specificity and undue radiation exposure, chest imaging nonetheless remains central to the initial diagnosis and monitoring of COVID-19 progression, as well as to the evaluation of complications. Classic features on chest CT include ground-glass and reticular opacities with or without superimposed consolidations, frequently presenting in a bilateral, peripheral, and posterior distribution. More recently, studies conducted with MRI have shown excellent concordance with chest CT in visualizing typical features of COVID-19 pneumonia. For patients in whom exposure to ionizing radiation should be avoided, particularly pregnant patients and children, pulmonary MRI may represent a suitable alternative to chest CT. Although PET imaging is not typically considered among first-line investigative modalities for the diagnosis of lower respiratory tract infections, numerous reports have noted incidental localization of radiotracer in parenchymal regions of COVID-19-associated pulmonary lesions. These findings are consistent with data from Middle East Respiratory Syndrome-CoV cohorts which suggested an ability for 18F-FDG PET to detect subclinical infection and lymphadenitis in subjects without overt clinical signs of infection. Though highly sensitive, use of PET/CT for primary detection of COVID-19 is constrained by poor specificity, as well as considerations of cost, radiation burden, and prolonged exposure times for imaging staff. Even still, decontamination of scanner bays is a time-consuming process, and proper ventilation of scanner suites may additionally require up to an hour of downtime to allow for sufficient air exchange. Yet, in patients who require nuclear medicine investigations for other clinical indications, PET imaging may yield the earliest detection of nascent infection in otherwise asymptomatic individuals. Especially for patients with concomitant malignancies and other states of immunocompromise, prompt recognition of infection and early initiation of supportive care is crucial to maximizing outcomes and improving survivability.
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Key Words
- sars-cov, severe acute respiratory syndrome coronavirus
- covid-19, coronavirus disease 2019
- ct, computed tomography
- mri, magnetic resonance imaging
- pet, positron emission tomography
- ggo, ground-glass opacity
- rt-pcr, reverse transcription polymerase chain reaction
- 18f-fdg, 18f-labelled fluorodeoxyglucose
- suvmax, maximum standardized uptake
- mip, maximum intensity projection
- 68ga-psma, 68ga-labelled prostate-specific membrane antigen
- 18f-choline, 18f-labelled choline
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Affiliation(s)
- Brandon K K Fields
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Natalie L Demirjian
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America; Department of Integrative Anatomical Sciences, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Habibollah Dadgar
- Razavi Cancer Research Center, RAZAVI Hospital, Imam Reza International University, Mashhad, Iran
| | - Ali Gholamrezanezhad
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America; Department of Radiology, University of Southern California, Los Angeles, CA 90033, United States of America.
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Bello Martinez R, Ghesani M, Ghesani N, Gavane S. Asymptomatic SARS-CoV-2 infection: Incidental findings on FDG PET/CT. J Med Imaging Radiat Sci 2021; 52:179-185. [PMID: 33820742 PMCID: PMC7962587 DOI: 10.1016/j.jmir.2021.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 03/06/2021] [Accepted: 03/09/2021] [Indexed: 12/18/2022]
Abstract
RATIONALE AND OBJECTIVES Identify the incidental findings of Covid-19 pneumonitis on 18F-FDG PET/CT scan in asymptomatic oncologic patients. The goal was to detect clinically unsuspected Covid-19 infections to prevent community spread. MATERIALS AND METHODS Retrospective analysis was conducted to recognize the pattern of metabolic and radiographic alterations on 18F-FDG PET/CT scans in Covid-19 patients. 492 18F-FDG PET/CT scans were reviewed for pulmonary and systemic abnormalities. RESULTS 18F-FDG PET/CT demonstrated new lung infiltrates in 29 asymptomatic patients. 13/29 patients had Covid-19 infection confirmed by nasopharyngeal nucleic acid PCR test. The most common lung abnormality was pure ground-glass opacity (GGO) (90%) in peripheral distribution (100%), involving 1 lobe in four patients (30.8%), 2-3 lobes in four patients, and 4-5 lobes in five patients (38.4%). Mean SUVmax was 4.7 (range 1.3-13.1). Ten patients developed symptoms, mainly fever, fatigue, and dry cough, within 6.4 ± 7.8 days (range 1-24). Of the available laboratory data of 12 patients, eight developed lymphopenia, and five patients had neutrophilia. Five patients required hospitalization, and two died of complications. CONCLUSION For a given geographic region in the later stage of a pandemic, such as Covid-19, community spread of the disease is common. Therefore, it is not surprising to find it in asymptomatic being imaged for other indications. Recognition of its manifestation and effectively mounting mitigation protocols is essential to further reduce SARS-CoV-2 spread, especially to susceptible groups, predominantly the elderly and people with comorbidities.
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Affiliation(s)
- Ricardo Bello Martinez
- Division of Nuclear Medicine; Department of Radiology, Icahn School of Medicine at Mount Sinai; 1 Gustave L. Levy Pl, New York, NY 10029, United States
| | - Munir Ghesani
- Division of Nuclear Medicine; Department of Radiology, Icahn School of Medicine at Mount Sinai; 1 Gustave L. Levy Pl, New York, NY 10029, United States
| | - Nasrin Ghesani
- Division of Nuclear Medicine; Department of Radiology, Icahn School of Medicine at Mount Sinai; 1 Gustave L. Levy Pl, New York, NY 10029, United States
| | - Somali Gavane
- Division of Nuclear Medicine; Department of Radiology, Icahn School of Medicine at Mount Sinai; 1 Gustave L. Levy Pl, New York, NY 10029, United States.
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Stasiak CES, Nigri DH, Cardoso FR, de Mattos RSDAR, Gonçalves Martins PA, Carvalho ARS, Altino de Almeida S, Rodrigues RS, Rosado-de-Castro PH. Case Report: Incidental Finding of COVID-19 Infection after Positron Emission Tomography/CT Imaging in a Patient with a Diagnosis of Histoplasmosis and Recurring Fever. Am J Trop Med Hyg 2021; 104:1651-1654. [PMID: 33798100 PMCID: PMC8103480 DOI: 10.4269/ajtmh.20-0952] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 02/28/2021] [Indexed: 12/14/2022] Open
Abstract
This is a case report of a 37-year-old woman evaluated with 18F-fludeoxyglucose (18F-FDG) positron emission computed tomography/CT with recurrent fever after treatment with itraconazole for 6 weeks for histoplasmosis. The examination demonstrated a decrease in the dimensions of the pulmonary opacities previously identified in the left lower lobe and attributed to histoplasmosis. In addition to these pulmonary opacities, increased FDG uptake was also observed in lymph nodes present in the cervical region, mediastinum, left lung hilum, and hepatic hilum. Notably, other pulmonary opacities with ground-glass pattern that were not present in the previous computed tomography were detected in the right lower lobe, with mild 18F-FDG uptake. Nasal swab performed shortly after the examination was positive for COVID-19. In this case, the 18F-FDG positron emission computed tomography/CT study demonstrated findings consistent with active COVID-19 infection coexisting with inflammatory changes associated with histoplasmosis infection.
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Affiliation(s)
| | | | - Fabrícius Rocha Cardoso
- Department of Radiology, D’Or Institute for Research and Education, Botafogo, Rio de Janeiro, Brazil
| | | | | | - Alysson Roncally Silva Carvalho
- Cardiovascular R&D Centre (UnIC), Department of Surgery and Physiology, Faculty of Medicine, University of Porto, Porto, Portugal;,Laboratory of Pulmonary Engineering, Biomedical Engineering Program, Alberto Luiz Coimbra Institute of Post-Graduation, Research in Engineering, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil;,Laboratory of Respiration Physiology, Carlos Chagas Filho Institute of Biophysics, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Sérgio Altino de Almeida
- Department of Radiology, D’Or Institute for Research and Education, Botafogo, Rio de Janeiro, Brazil
| | | | - Paulo Henrique Rosado-de-Castro
- Department of Radiology, D’Or Institute for Research and Education, Botafogo, Rio de Janeiro, Brazil;,Department of Radiology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;,Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil,Address correspondence to Paulo Henrique Rosado-de-Castro, D’Or Institute for Research and Education, Rua Diniz Cordeiro 30, Botafogo, 22281-100, Rio de Janeiro/RJ, Brazil. E-mail:
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Ferraro E, Germanò M, Mollace R, Mollace V, Malara N. HIF-1, the Warburg Effect, and Macrophage/Microglia Polarization Potential Role in COVID-19 Pathogenesis. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2021; 2021:8841911. [PMID: 33815663 PMCID: PMC7987467 DOI: 10.1155/2021/8841911] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 01/07/2021] [Accepted: 03/03/2021] [Indexed: 02/07/2023]
Abstract
Despite the international scientific community's commitment to improve clinical knowledge about coronavirus disease 2019 (COVID-19), knowledge regarding molecular details remains limited. In this review, we discuss hypoxia's potential role in the pathogenesis of the maladaptive immune reaction against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The state of infection, with serious respiratory dysfunction, causes tissues to become hypoxic due to a discrepancy between cellular O2 uptake and consumption similar to that seen within tumor tissue during the progression of numerous solid cancers. In this context, the heterogeneous clinical behavior and the multiorgan deterioration of COVID-19 are discussed as a function of the upregulated expression of the hypoxia-inducible factor-1 (HIF-1) and of the metabolic reprogramming associated with HIF-1 and with a proinflammatory innate immune response activation, independent of the increase in the viral load of SARS-CoV-2. Possible pharmacological strategies targeting O2 aimed to improve prognosis are suggested.
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36
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Rafiee F, Keshavarz P, Katal S, Assadi M, Nejati SF, Ebrahimian Sadabad F, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19) in Molecular Imaging: A Systematic Review of Incidental Detection of SARS-CoV-2 Pneumonia on PET Studies. Semin Nucl Med 2021; 51:178-191. [PMID: 33509374 PMCID: PMC7598766 DOI: 10.1053/j.semnuclmed.2020.10.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
There have been several reports of the incidental detection of severe acute respiratory syndrome coronavirus 2 pneumonia on positron emission tomography/computed tomography (PET/CT) studies, which represent the potential role of molecular imaging in the detection and management of coronavirus disease 2019. Here, we systematically review the value of PET/CT in this setting. We conducted a systematic search on June 23, 2020, for PET studies with findings suggestive of coronavirus disease 2019. Web of Science, PubMed, Scopus, EMBASE, and Google Scholar databases were used. Patients with at least one PET/CT imaging evaluation were included in the study. Fifty-two patients in 30 publications with a mean age of 60 ± 12.74 (age range; 27-87) were included in this study, of which 28 (53.8%) were male, and 19 (36.5%) were female. In 5 (9.7%) patients, gender was not reported. PET/CT was performed with 18F-fluorodeoxyglucose for 48 (92.3%), 18F-choline for 3 (5.8%), and 68Ga-PSMA for 1 (1.9%) patients. The mean SUV max of pulmonary lesions with 18F-fluorodeoxyglucose uptake was 4.9 ± 2.3. Moreover, 39 (75%) cases had an underlying malignancy, including 18 different type of primary cancers and 6 (11.5%) patients with metastatic disease. The most common pulmonary findings in PET/CT were bilateral hypermetabolic ground-glass opacities in 39 (75%), consolidation in 18 (34.6%), and interlobular thickening in 4 (7.6%). In addition, mediastinal 14 (27%) and hilar 10 (19.2%) lymph node involvement with increased metabolic activity was frequently identified. Early diagnosis of severe acute respiratory syndrome coronavirus 2 pneumonia is not only crucial for both appropriate patient management but also helps to ensure appropriate postexposure precautions are implemented for the department and hospital staff and those who have been in contact with the patient.
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Affiliation(s)
- Faranak Rafiee
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Pedram Keshavarz
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran; Department of Radiology, Tbilisi State Medical University (TSMU), Tbilisi, Georgia
| | - Sanaz Katal
- Department of Nuclear Medicine/PET-CT, Kowsar Hospital, Shiraz, Iran
| | - Majid Assadi
- Department of Molecular Imaging and Radionuclide Therapy (MIRT), The Persian Gulf Nuclear Medicine Research Center, Bushehr Medical University Hospital, School of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Seyed Faraz Nejati
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Faranak Ebrahimian Sadabad
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ali Gholamrezanezhad
- Department of Radiology, Keck School of Medicine, University of Sothern California (USC), Los Angeles, CA.
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Razek A, Fouda N, Fahmy D, Tanatawy MS, Sultan A, Bilal M, Zaki M, Abdel-Aziz M, Sobh D. Computed tomography of the chest in patients with COVID-19: what do radiologists want to know? Pol J Radiol 2021; 86:e122-e135. [PMID: 33758638 PMCID: PMC7976235 DOI: 10.5114/pjr.2021.104049] [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: 08/02/2020] [Accepted: 08/15/2020] [Indexed: 12/14/2022] Open
Abstract
We aim in the current study to review pulmonary and extra-pulmonary imaging features in patients infected with COVID-19. COVID-19 appears to be a highly contagious viral disease that attacks the respiratory system causing pneumonia. Since the beginning of the outbreak, several reports have been published describing various radiological patterns related to COVID-19. Radiological features of COVID-19 are classified into; pulmonary signs of which ground glass opacities are considered the characteristic followed by consolidation, and extra-pulmonary signs such as pulmonary embolism and pneumothorax, which are far less common and appear later in progressive disease. We review the different structured reporting systems that are published by different groups of radiologists using simple unified terms to enable good communication between the radiologist and the referring physician. Computed tomography of the chest is beneficial for early diagnosis of COVID-19 pneumonia, assessment of disease progression and guide to therapy, surveillance of patients with response to therapy, prediction of overlying bacterial infection, differentiation from simulating lesions, and screening with prevention and controls of the disease.
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Affiliation(s)
- Ahmed Razek
- Correspondence address: Ahmed Razek, MD, Mansoura University Hospital, Egypt, e-mail:
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Bhattacharya S, Reddy Maddikunta PK, Pham QV, Gadekallu TR, Krishnan S SR, Chowdhary CL, Alazab M, Jalil Piran M. Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey. SUSTAINABLE CITIES AND SOCIETY 2021; 65:102589. [PMID: 33169099 PMCID: PMC7642729 DOI: 10.1016/j.scs.2020.102589] [Citation(s) in RCA: 169] [Impact Index Per Article: 42.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many death cases and affected all sectors of human life. With gradual progression of time, COVID-19 was declared by the world health organization (WHO) as an outbreak, which has imposed a heavy burden on almost all countries, especially ones with weaker health systems and ones with slow responses. In the field of healthcare, deep learning has been implemented in many applications, e.g., diabetic retinopathy detection, lung nodule classification, fetal localization, and thyroid diagnosis. Numerous sources of medical images (e.g., X-ray, CT, and MRI) make deep learning a great technique to combat the COVID-19 outbreak. Motivated by this fact, a large number of research works have been proposed and developed for the initial months of 2020. In this paper, we first focus on summarizing the state-of-the-art research works related to deep learning applications for COVID-19 medical image processing. Then, we provide an overview of deep learning and its applications to healthcare found in the last decade. Next, three use cases in China, Korea, and Canada are also presented to show deep learning applications for COVID-19 medical image processing. Finally, we discuss several challenges and issues related to deep learning implementations for COVID-19 medical image processing, which are expected to drive further studies in controlling the outbreak and controlling the crisis, which results in smart healthy cities.
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Affiliation(s)
- Sweta Bhattacharya
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | | | - Quoc-Viet Pham
- Research Institute of Computer, Information and Communication, Pusan National University, Busan 46241, Republic of Korea
| | - Thippa Reddy Gadekallu
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Siva Rama Krishnan S
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Chiranji Lal Chowdhary
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Mamoun Alazab
- College of Engineering, IT & Environment, Charles Darwin University, Australia
| | - Md Jalil Piran
- Department of Computer Science and Engineering, Sejong University, 05006, Seoul, Republic of Korea
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Dong D, Tang Z, Wang S, Hui H, Gong L, Lu Y, Xue Z, Liao H, Chen F, Yang F, Jin R, Wang K, Liu Z, Wei J, Mu W, Zhang H, Jiang J, Tian J, Li H. The Role of Imaging in the Detection and Management of COVID-19: A Review. IEEE Rev Biomed Eng 2021; 14:16-29. [PMID: 32356760 DOI: 10.1109/rbme.2020.2990959] [Citation(s) in RCA: 162] [Impact Index Per Article: 40.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.
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Jain A, Patankar S, Kale S, Bairy A. Imaging of coronavirus disease (COVID-19): a pictorial review. Pol J Radiol 2021; 86:e4-e18. [PMID: 33708269 PMCID: PMC7934747 DOI: 10.5114/pjr.2021.102609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 07/20/2020] [Indexed: 02/06/2023] Open
Abstract
Coronavirus disease (COVID-19), caused by a highly contagious novel coronavirus, has seen a rapid surge of cases over the past 6 months spreading to more than 215 countries and posing a global threat to mankind. Reverse transcriptase-polymerase chain reaction (RT-PCR) from pharyngeal swabs is considered the gold standard for diagnosis of this disease. Portable chest radiography (CXR), point of care ultrasound, and computed tomography (CT) are crucial modalities in diagnosis and follow-up. Portable CXR can help in patients who are clinically unstable, and also to prevent the cumbersome process of steriliastion after every CT scan. However, chest CT is useful as a problem-solving tool, to look for progression and complications associated with the disease. In a few cases, in our experience (as has also been documented by others), RT-PCR was negative in early disease, and CT chest was able to detect the radiologi-cal findings raising suspicion of COVID-19. With this pictorial review, we aim to describe and illustrate the typical, and a few atypical, radiological findings of this disease.
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Affiliation(s)
| | | | | | - Abhishek Bairy
- Correspondence address: Dr. Abhishek Bairy, Department of Radiology, Seth G.S. Medical College & K.E.M. Hospital, Acharya Donde Marg, Parel East, Parel, Mumbai, Maharashtra 400012, India, e-mail:
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Halsey R, Priftakis D, Mackenzie S, Wan S, Davis LM, Lilburn D, Thornton A, Papathanasiou N, Gnanasegaran G, Bomanji J. COVID-19 in the act: incidental 18F-FDG PET/CT findings in asymptomatic patients and those with symptoms not primarily correlated with COVID-19 during the United Kingdom coronavirus lockdown. Eur J Nucl Med Mol Imaging 2021; 48:269-281. [PMID: 32761260 PMCID: PMC7406218 DOI: 10.1007/s00259-020-04972-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 07/23/2020] [Indexed: 11/12/2022]
Abstract
PURPOSE The emergence of the novel SARS-CoV-2 pathogen and lethal COVID-19 disease pandemic poses major diagnostic challenges. The study aims to describe the spectrum and prevalence of thoracic and extrathoracic incidental findings in patients who have undergone 18F-FDG PET/CT during the first 3 weeks of the COVID-19 UK lockdown. METHODS This is a single-centre retrospective controlled observational study. 18F-FDG PET/CT scans (n = 160) acquired from 23/3/2020 to 9/4/2020 were retrospectively reviewed for incidental findings in the lungs and extrapulmonary sites (heart, nasal sinuses, parotid and salivary glands, colon, large vessels, renal cortex, brain, spleen and testes). A date-matched control group (n = 205) of patients from 2019 was used for comparison. RESULTS The total prevalence of suspicious findings was 26/160 (16.25%). Fifteen patients presented with incidental findings in the lungs, while eleven patients had only non-pulmonary incidental findings. There was a significant increase in the appearance of incidental 18F-FDG PET/CT findings during the 2nd week (OR = 3.8) and 3rd week (OR = 7.6) in relation to the 1st week. There was a significant increase in the average maximum standardised uptake values (SUVmax) in the parotid/salivary glands of patients scanned during week 2 in relation to week 1 (p = 0.036). There was no significant difference in the prevalence of incidental findings compared to the control group, but the number of pulmonary vs. extrathoracic findings was different between the two populations. CONCLUSION The study provides a novel base of evidence to identify asymptomatic patients and those without symptoms strongly associated with COVID-19 with incidental 18F-FDG PET/CT findings suspicious of SARS-CoV-2 infection during the initial stages of the pandemic.
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Affiliation(s)
- Richard Halsey
- Institute of Nuclear Medicine, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
| | - Dimitrios Priftakis
- Institute of Nuclear Medicine, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
| | - Strachan Mackenzie
- Department Haematology, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
| | - Simon Wan
- Institute of Nuclear Medicine, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
| | - Laura M. Davis
- Institute of Nuclear Medicine, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
| | - David Lilburn
- Institute of Nuclear Medicine, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
| | - Andrew Thornton
- Institute of Nuclear Medicine, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
| | - Nikolaos Papathanasiou
- Nuclear Medicine and PET/CT Department, University Hospital of Patras, Rio, 265 04 Patras, Greece
| | - Gopinath Gnanasegaran
- Department of Nuclear Medicine, Royal Free Hospital, Pond Street, Hampstead, London, NW3 2QG UK
| | - Jamshed Bomanji
- Institute of Nuclear Medicine, University College London Hospital NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK
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Pillenahalli Maheshwarappa R, Graham MM. Asymptomatic COVID-19 Infection Detected on 18F-FDG PET/CT Scan Done for Multiple Myeloma. Clin Nucl Med 2021; 46:e57-e58. [PMID: 32956130 PMCID: PMC7740275 DOI: 10.1097/rlu.0000000000003314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 08/24/2020] [Indexed: 12/01/2022]
Abstract
A 69-year-old woman with multiple myeloma came to our department for F-FDG PET/CT scan for routine surveillance. The patient denied any history of fever, cough, shortness of breath, or body aches. F-FDG PET/CT scan from vertex to knees was performed. PET/CT images revealed extensive peripheral ground-glass opacities showing intense FDG uptake (SUVmax 12) involving bilateral lower lobes. Possibility of an infective etiology including novel coronavirus (COVID-19) infection was raised. The patient's oropharyngeal swab for COVID-19 by polymerase chain reaction amplification test came back positive for COVID-19 infection. The patient and her husband were advised home quarantine for 14 days.
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Dietz M, Chironi G, Claessens YE, Farhad RL, Rouquette I, Serrano B, Nataf V, Hugonnet F, Paulmier B, Berthier F, Keita-Perse O, Giammarile F, Perrin C, Faraggi M. COVID-19 pneumonia: relationship between inflammation assessed by whole-body FDG PET/CT and short-term clinical outcome. Eur J Nucl Med Mol Imaging 2021; 48:260-268. [PMID: 32712702 PMCID: PMC7382557 DOI: 10.1007/s00259-020-04968-8] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 07/19/2020] [Indexed: 12/23/2022]
Abstract
PURPOSE [18F]-2-Fluoro-2-deoxy-D-glucose PET/CT (FDG PET/CT) is a sensitive and quantitative technic for detecting inflammatory process. Glucose uptake is correlated with an increased anaerobic glycolysis seen in activated inflammatory cells such as monocytes, lymphocytes, and granulocytes. The aim of the study was to assess the inflammatory status at the presumed peak of the inflammatory phase in non-critically ill patients requiring admission for COVID-19. METHODS Patients admitted with COVID-19 were prospectively enrolled. FDG PET/CT was performed from day 6 to day 14 of the onset of symptoms. Depending on FDG PET/CT findings, patients' profiles were classified as "inflammatory" or "low inflammatory." FDG PET/CT data were compared with chest CT evolution and short-term clinical outcome. All inflammatory sites were reported to screen potential extra-pulmonary tropism. RESULTS Thirteen patients were included. Maximum standardized uptake values ranged from 4.7 to 16.3 in lungs. All patients demonstrated increased mediastinal lymph nodes glucose uptake. Three patients (23%) presented mild nasopharyngeal, two patients (15%) bone marrow, and five patients (38%) splenic mild increase in glucose uptake. No patient had significant digestive focal or segmental glucose uptake. There was no significant physiological myocardial glucose uptake in all patients except one. There was no correlation between PET lung inflammatory status and chest CT evolution or short-term clinical outcome. CONCLUSION Inflammatory process at the presumed peak of the inflammatory phase in COVID-19 patients is obvious in FDG PET/CT scans. Glucose uptake is heterogeneous and typically focused on lungs. TRIAL REGISTRATION NCT04441489. Registered 22 June 2020 (retrospectively registered).
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Affiliation(s)
- Matthieu Dietz
- Nuclear Medicine Department, Centre Hospitalier Princesse Grace, 1 Avenue Pasteur, 98000, Monaco, Monaco
| | - Gilles Chironi
- Check-up Unit, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Yann-Erick Claessens
- Department of Emergency Medicine, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Ryan Lukas Farhad
- Pulmonary Department, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Isabelle Rouquette
- Department of Intensive Care Medicine, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Benjamin Serrano
- Medical Physics Department, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Valérie Nataf
- Nuclear Medicine Department, Centre Hospitalier Princesse Grace, 1 Avenue Pasteur, 98000, Monaco, Monaco
| | - Florent Hugonnet
- Nuclear Medicine Department, Centre Hospitalier Princesse Grace, 1 Avenue Pasteur, 98000, Monaco, Monaco
| | - Benoît Paulmier
- Nuclear Medicine Department, Centre Hospitalier Princesse Grace, 1 Avenue Pasteur, 98000, Monaco, Monaco
| | - Frédéric Berthier
- Department of Biostatistics, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Olivia Keita-Perse
- Infection disease Department, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Francesco Giammarile
- Division of Human Health, International Atomic Energy Agency, Vienna, Austria
- Centre Leon Berard, Lyon, France
| | - Christophe Perrin
- Pulmonary Department, Centre Hospitalier Princesse Grace, Monaco, Monaco
| | - Marc Faraggi
- Nuclear Medicine Department, Centre Hospitalier Princesse Grace, 1 Avenue Pasteur, 98000, Monaco, Monaco.
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Katal S, Amini H, Gholamrezanezhad A. PET in the diagnostic management of infectious/inflammatory pulmonary pathologies: a revisit in the era of COVID-19. Nucl Med Commun 2021; 42:3-8. [PMID: 32991395 PMCID: PMC7720808 DOI: 10.1097/mnm.0000000000001299] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 09/01/2020] [Indexed: 12/25/2022]
Affiliation(s)
- Sanaz Katal
- Department of Diagnostic Radiology, Keck School of Medicine, University of Southern California (USC), Los Angles, California, USA
| | - Hamidreza Amini
- Department of Diagnostic Radiology, Keck School of Medicine, University of Southern California (USC), Los Angles, California, USA
| | - Ali Gholamrezanezhad
- Department of Diagnostic Radiology, Keck School of Medicine, University of Southern California (USC), Los Angles, California, USA
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Mathew RP, Jose M, Jayaram V, Joy P, George D, Joseph M, Sleeba T, Toms A. Current status quo on COVID-19 including chest imaging. World J Radiol 2020; 12:272-288. [PMID: 33510852 PMCID: PMC7802080 DOI: 10.4329/wjr.v12.i12.272] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/07/2020] [Accepted: 12/16/2020] [Indexed: 02/06/2023] Open
Abstract
With each day the number coronavirus disease 2019 (COVID-19) cases continue to rise rapidly and our imaging knowledge of this disease is expeditiously evolving. The role of chest computed tomography (CT) in the screening or diagnosis of COVID-19 remains the subject of much debate. Despite several months having passed since identifying the disease, and numerous studies related to it, controversy and concern still exists regarding the widespread use of chest CT in the evaluation and management of COVID-19 suspect patients. Several institutes and organizations around the world have released guidelines, recommendations and statements against the use of CT for diagnosing or screening COVID-19 infection and advocating its use only for those cases with a strong clinical suspicion of complication or an alternate diagnosis. However, these guidelines and recommendations are in disagreement with majority of the widely available literature, which strongly favour CT as a pivotal tool in the early diagnosis, management and even follow-up of COVID-19 infection. This article besides comprehensively reviewing the current status quo on COVID-19 disease in general, also writes upon the current consensus statements/recommendations on the use of diagnostic imaging in COVID-19 as well as highlighting the precautions and various disinfection procedures being employed world-wide at the workplace to prevent the spread of infection.
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Affiliation(s)
| | - Merin Jose
- Department of Radiology, Rajagiri Hospital, Kochi 683112, Kerala, India
| | - Vinayak Jayaram
- Department of Radiology, Rajagiri Hospital, Kochi 683112, Kerala, India
| | - Paul Joy
- Department of Radiology, Rajagiri Hospital, Kochi 683112, Kerala, India
| | - Danny George
- Department of Radiology, Rajagiri Hospital, Kochi 683112, Kerala, India
| | - Maria Joseph
- Department of Radiology, Rajagiri Hospital, Kochi 683112, Kerala, India
| | - Teena Sleeba
- Department of Radiology, Rajagiri Hospital, Kochi 683112, Kerala, India
| | - Ajith Toms
- Department of Radiology, Rajagiri Hospital, Kochi 683112, Kerala, India
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Tafti D, Kluckman M, Dearborn MC, Hunninghake J, Clayton S. COVID-19 in Patients With Hematologic-Oncologic Risk Factors: Complications in Three Patients. Cureus 2020; 12:e12064. [PMID: 33489484 PMCID: PMC7805421 DOI: 10.7759/cureus.12064] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/11/2020] [Indexed: 12/13/2022] Open
Abstract
The novel COVID-19 infection has demonstrated a spectrum of complications involving vascular, inflammatory, infectious, and metabolic conditions. These complications range from mild loss of smell to more severe acute respiratory distress syndrome (ARDS). Patients with more severe complications often require sedation and mechanical ventilation. Growing research has revealed the role of active malignancy and disease-in-remission status as possible risk factors contributing to the morbidity and mortality in COVID-19 patients. In our descriptive case series, we present three unique cases of complicated COVID-19 infection in patients with hematologic-oncologic risk factors and review the imaging features of their complications. The first patient was a 33-year-old male with sickle cell trait who developed rhabdomyolysis and myonecrosis of the paraspinal muscle in the setting of a physical fitness test; he subsequently developed an abscess at this site, presumably exacerbated by the hypoxemic state of his COVID-19 pneumonia. Our second patient was a 37-year-old male with COVID-19 pneumonia and a history of stage IV Non-Hodgkin's lymphoma in remission who developed spontaneous pneumomediastinum in the absence of positive pressure ventilation. The third COVID-positive patient was a 54-year-old male with a past medical history significant for grade 1 follicular non-Hodgkin's lymphoma in remission with sputum culture positive for mycobacterium avium complex and bronchoscopy positive for candida growth. 18-FDG/PET imaging was performed and demonstrated diffuse intense uptake throughout the lungs reflecting both the COVID-19 pneumonia and the multimicrobial superinfection.
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Affiliation(s)
- Dawood Tafti
- Radiology, Brooke Army Medical Center, Fort Sam Houston, USA
| | | | | | - John Hunninghake
- Critical Care Medicine, Brooke Army Medical Center, Fort Sam Houston, USA
| | - Sara Clayton
- Radiology, Brooke Army Medical Center, Fort Sam Houston, USA
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Landete P, Loaiza CAQ, Aldave-Orzaiz B, Muñiz SH, Maldonado A, Zamora E, Cerna ACS, Cerro ED, Alonso RC, Couñago F. Clinical features and radiological manifestations of COVID-19 disease. World J Radiol 2020; 12:247-260. [PMID: 33362916 PMCID: PMC7745468 DOI: 10.4329/wjr.v12.i11.247] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 08/24/2020] [Accepted: 10/26/2020] [Indexed: 02/06/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) was discovered after unusual cases of severe pneumonia emerged in December 2019 in Wuhan Province (China). Coronavirus is a family of single-stranded RNA viruses. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted from person to person. Although asymptomatic individuals can transmit the virus, symptomatic patients are more contagious. The incubation period ranges from 3-7 d and symptoms are mainly respiratory, including pneumonia or pulmonary embolism in severe cases. Elevated serum levels of interleukins (IL)-2, IL-6, IL-7 indicate the presence of cytokine release syndrome, which is associated with disease severity. The disease has three main phases: Viral infection, pulmonary involvement, and hyperinflammation. To date, no treatment has proved to be safe or effective. Chest X-ray and computed tomography (CT) are the primary imaging tests for diagnosis of SARS-CoV-2 pneumonia, follow-up, and detection of complications. The main radiological findings are ground-glass opacification and areas of consolidation. The long-term clinical course is unknown, although some patients may develop pulmonary fibrosis. Positron emission tomography-computed tomography (PET-CT) is useful to assess pulmonary involvement, to define the affected areas, and to assess treatment response. The pathophysiology and clinical course of COVID-19 infection remain poorly understood. However, patterns detected on CT and PET-CT may help to diagnose and guide treatment. In this mini review, we analyze the clinical manifestations and radiological findings of COVID-19 infection.
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Affiliation(s)
- Pedro Landete
- Department ofPulmonology, H. U. La Princesa, Madrid 28006, Spain
| | | | | | | | - Antonio Maldonado
- Department of Nuclear Medicine, Hospital Universitario Quironsalud Madrid, Madrid 28223, Spain
| | - Enrique Zamora
- Department ofPulmonology, H. U. La Princesa, Madrid 28006, Spain
| | | | - Elia del Cerro
- Department of Radiation Oncology, Hospital Universitario Quirónsalud Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Department of Radiation Oncology, Hospital La Luz, Madrid 28003, Spain
- Department of Radiation Oncology, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid 28670, Spain
| | - Raquel Cano Alonso
- Department of Diagnostic Imaging, Hospital Universitario Quirón Madrid, Madrid 28223, Spain
| | - Felipe Couñago
- Department of Radiation Oncology, Hospital Universitario Quirónsalud Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Department of Radiation Oncology, Hospital La Luz, Madrid 28003, Spain
- Department of Radiation Oncology, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid 28670, Spain
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Ali SA, Abdelkawi MM. Incidentally recognized COVID-19 pneumonia in routine oncologic 18F-FDG PET/CT examinations: a local experience during pandemic era. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020. [PMCID: PMC7610243 DOI: 10.1186/s43055-020-00333-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Background CT chest findings of COVID-19 pneumonia can be detected before the clinical symptoms become evident in many cases. In this work, we presented our experience in incidental detection of COVID-19-associated pneumonia in asymptomatic patients coming for routine oncologic 18F-FDG PET/CT examinations during the COVID-19 pandemic, which contribute in the detection of the affected patients early to be isolated and properly managed. We reported the cases with incidental finding of COVID-19 pneumonia among 764 asymptomatic patients who were referred for whole-body 18F-FDG PET/CT examinations for routine oncologic indications in the period between 15 March and 15 June 2020, and RT-PCR testing for them was requested for confirmation. Results Among the 764 scanned patients, we had recognized 87 patients (11.3%) having features of COVID-19 pneumonia. RT-PCR testing of them confirmed COVID-19 infection in 78 cases, yet 3 were negative and no RT-PCR testing was performed in 6 cases (only isolated and carefully monitored). Conclusion 18F-FDG PET/CT is sensitive for early COVID-19 detection, even in asymptomatic patients that guide proper management and also highlight the key role of a radiologist and the importance of applying safety measures in clinical services during the pandemic to minimize the spread of infection.
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Boettcher AN, Hammoud DA, Weinberg JB, Agarwal P, Mendiratta-Lala M, Luker GD. Cancer Imaging and Patient Care during the COVID-19 Pandemic. Radiol Imaging Cancer 2020; 2:e200058. [PMID: 33778750 PMCID: PMC7706101 DOI: 10.1148/rycan.2020200058] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Patients with cancer have been negatively impacted during the coronavirus disease 2019 (COVID-19) pandemic, as many of these individuals may be immunosuppressed and of older age. Additionally, cancer follow-up or imaging appointments have been delayed in many clinics around the world. Postponement of routine screening exams will result in delays in new cancer diagnoses. Clinics are continuing to monitor and adapt their appointment schedules based on local outbreaks of COVID-19. Studies on COVID-19 in patients with cancer are limited, but consistently indicate that this population is at risk for more severe COVID-19 illness. Data from recent studies also suggest that pediatric patients with cancer have a lower risk of severe COVID-19 illness compared to adults. Certain features of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection detected by lung, brain, and gastrointestinal imaging may confound radiologists' interpretation of cancer diagnosis, staging, and treatment response. Lastly, as clinics begin to re-open for routine appointments, protocols have been put in place to reduce SARS-CoV-2 exposure to patients during their visits. This review details different perspectives on the impact of the COVID-19 pandemic on patients with cancer and on cancer imaging. Keywords: Abdomen/GI, Cardiac, Infection, Nervous-Peripheral.
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Affiliation(s)
- Adeline N. Boettcher
- From the Scientific Editor, RSNA (A.N.B.); Center for Infectious Disease Imaging, NIH Clinical Center, Bethesda, Maryland (D.A.H.); Departments of Pediatrics and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (J.B.W.); Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan (P.A.); Department of Radiology, Division of Abdominal imaging, University of Michigan, Ann Arbor, Michigan (M.M.); Department of Radiology, Biomedical Engineering, and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (G.D.L)
| | - Dima A. Hammoud
- From the Scientific Editor, RSNA (A.N.B.); Center for Infectious Disease Imaging, NIH Clinical Center, Bethesda, Maryland (D.A.H.); Departments of Pediatrics and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (J.B.W.); Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan (P.A.); Department of Radiology, Division of Abdominal imaging, University of Michigan, Ann Arbor, Michigan (M.M.); Department of Radiology, Biomedical Engineering, and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (G.D.L)
| | - Jason B. Weinberg
- From the Scientific Editor, RSNA (A.N.B.); Center for Infectious Disease Imaging, NIH Clinical Center, Bethesda, Maryland (D.A.H.); Departments of Pediatrics and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (J.B.W.); Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan (P.A.); Department of Radiology, Division of Abdominal imaging, University of Michigan, Ann Arbor, Michigan (M.M.); Department of Radiology, Biomedical Engineering, and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (G.D.L)
| | - Prachi Agarwal
- From the Scientific Editor, RSNA (A.N.B.); Center for Infectious Disease Imaging, NIH Clinical Center, Bethesda, Maryland (D.A.H.); Departments of Pediatrics and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (J.B.W.); Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan (P.A.); Department of Radiology, Division of Abdominal imaging, University of Michigan, Ann Arbor, Michigan (M.M.); Department of Radiology, Biomedical Engineering, and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (G.D.L)
| | - Mishal Mendiratta-Lala
- From the Scientific Editor, RSNA (A.N.B.); Center for Infectious Disease Imaging, NIH Clinical Center, Bethesda, Maryland (D.A.H.); Departments of Pediatrics and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (J.B.W.); Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan (P.A.); Department of Radiology, Division of Abdominal imaging, University of Michigan, Ann Arbor, Michigan (M.M.); Department of Radiology, Biomedical Engineering, and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (G.D.L)
| | - Gary D. Luker
- From the Scientific Editor, RSNA (A.N.B.); Center for Infectious Disease Imaging, NIH Clinical Center, Bethesda, Maryland (D.A.H.); Departments of Pediatrics and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (J.B.W.); Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan (P.A.); Department of Radiology, Division of Abdominal imaging, University of Michigan, Ann Arbor, Michigan (M.M.); Department of Radiology, Biomedical Engineering, and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan (G.D.L)
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Oniani D, Jiang G, Liu H, Shen F. Constructing co-occurrence network embeddings to assist association extraction for COVID-19 and other coronavirus infectious diseases. J Am Med Inform Assoc 2020; 27:1259-1267. [PMID: 32458963 PMCID: PMC7314034 DOI: 10.1093/jamia/ocaa117] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 05/19/2020] [Accepted: 05/22/2020] [Indexed: 02/07/2023] Open
Abstract
Objective As coronavirus disease 2019 (COVID-19) started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for having a knowledge repository for the disease became crucial. To address this issue, a new COVID-19 machine-readable dataset known as the COVID-19 Open Research Dataset (CORD-19) has been released. Based on this, our objective was to build a computable co-occurrence network embeddings to assist association detection among COVID-19–related biomedical entities. Materials and Methods Leveraging a Linked Data version of CORD-19 (ie, CORD-19-on-FHIR), we first utilized SPARQL to extract co-occurrences among chemicals, diseases, genes, and mutations and build a co-occurrence network. We then trained the representation of the derived co-occurrence network using node2vec with 4 edge embeddings operations (L1, L2, Average, and Hadamard). Six algorithms (decision tree, logistic regression, support vector machine, random forest, naïve Bayes, and multilayer perceptron) were applied to evaluate performance on link prediction. An unsupervised learning strategy was also developed incorporating the t-SNE (t-distributed stochastic neighbor embedding) and DBSCAN (density-based spatial clustering of applications with noise) algorithms for case studies. Results The random forest classifier showed the best performance on link prediction across different network embeddings. For edge embeddings generated using the Average operation, random forest achieved the optimal average precision of 0.97 along with a F1 score of 0.90. For unsupervised learning, 63 clusters were formed with silhouette score of 0.128. Significant associations were detected for 5 coronavirus infectious diseases in their corresponding subgroups. Conclusions In this study, we constructed COVID-19–centered co-occurrence network embeddings. Results indicated that the generated embeddings were able to extract significant associations for COVID-19 and coronavirus infectious diseases.
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Affiliation(s)
- David Oniani
- Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
| | - Guoqian Jiang
- Division of Digital Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Hongfang Liu
- Division of Digital Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Feichen Shen
- Division of Digital Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
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