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1.
Medicine (Baltimore) ; 100(36): e26855, 2021 Sep 10.
Article in English | MEDLINE | ID: covidwho-2191052

ABSTRACT

ABSTRACT: Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentation, diagnosis, and evaluation. Artificial intelligence can accurately segment infected parts in X-ray and CT images, assist doctors in improving diagnosis efficiency, and facilitate the subsequent assessment of the severity of the patient infection. The medical assistant platform based on machine learning can help radiologists make clinical decisions and helper in screening, diagnosis, and treatment. By providing scientific methods for image recognition, segmentation, and evaluation, we summarized the latest developments in the application of artificial intelligence in COVID-19 lung imaging, and provided guidance and inspiration to researchers and doctors who are fighting the COVID-19 virus.


Subject(s)
COVID-19/diagnostic imaging , Machine Learning , Pneumonia, Viral/diagnostic imaging , SARS-CoV-2 , Humans , Radiography , Tomography, X-Ray Computed
2.
Medicine (Baltimore) ; 100(21): e26143, 2021 May 28.
Article in English | MEDLINE | ID: covidwho-2191018

ABSTRACT

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is a rapidly emerging infectious respiratory disease caused by severe acute respiratory syndrome coronavirus 2. Currently, more than 100 million cases of COVID-19 have been confirmed worldwide, with over 2.4 million mortalities. The pandemic affects people of all ages but older individuals and those with severe chronic illnesses, including cancer patients, are at higher risk. PATIENT CONCERNS: The impact of cancer treatment on the progression of COVID-19 is unclear. Therefore, we assessed the effects of chemotherapy on COVID-19 outcomes for 2 cancer patients. On January 24, 2020, a level I response to a major public health emergency was initiated in Hubei Province, China, which includes Enshi Autonomous Prefecture that has a population of 4.026 million people. As of April 30, 2020, 252 confirmed cases of COVID-19 and 11 asymptomatic carriers were identified in Enshi. DIAGNOSIS: Among the confirmed cases and asymptomatic carriers, 2 patients were identified who were previously diagnosed with malignant tumors, including one with hepatocellular carcinoma and the other with cardia carcinoma. INTERVENTIONS: These 2 patients were receiving or just completed chemotherapy at the time of their COVID-19 diagnosis. OUTCOMES: Both patients were followed and presented favorable outcomes. The positive outcomes for these 2 patients could be partially explained by their recent chemotherapy that impacted their immune status. Also, their relatively younger ages and lack of comorbidities were likely factors in their successful recovery from COVID-19. CONCLUSIONS: Anticancer treatment might enhance a patient's ability to respond favorably to COVID-19 infection. However, anticancer treatment is likely to impact immune function differently in different individuals, which can influence disease outcomes.


Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , COVID-19/immunology , Liver Neoplasms/drug therapy , SARS-CoV-2/immunology , Stomach Neoplasms/drug therapy , Adult , COVID-19/complications , COVID-19/diagnosis , COVID-19/drug therapy , COVID-19 Nucleic Acid Testing , Cyclobutanes/therapeutic use , Docetaxel/therapeutic use , Drug Therapy, Combination/methods , Humans , Liver Neoplasms/complications , Liver Neoplasms/immunology , Lung/diagnostic imaging , Male , Middle Aged , Organoplatinum Compounds/therapeutic use , RNA, Viral/isolation & purification , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Sorafenib/therapeutic use , Stomach Neoplasms/complications , Stomach Neoplasms/immunology , Tomography, X-Ray Computed , Treatment Outcome
3.
Medicine (Baltimore) ; 100(21): e26034, 2021 May 28.
Article in English | MEDLINE | ID: covidwho-2191014

ABSTRACT

ABSTRACT: To determine the role of ultra-low dose chest computed tomography (uld CT) compared to chest radiographs in patients with laboratory-confirmed early stage SARS-CoV-2 pneumonia.Chest radiographs and uld CT of 12 consecutive suspected SARS-CoV-2 patients performed up to 48 hours from hospital admission were reviewed by 2 radiologists. Dosimetry and descriptive statistics of both modalities were analyzed.On uld CT, parenchymal abnormalities compatible with SARS-CoV-2 pneumonia were detected in 10/12 (83%) patients whereas on chest X-ray in, respectively, 8/12 (66%) and 5/12 (41%) patients for reader 1 and 2. The average increment of diagnostic performance of uld CT compared to chest X-ray was 29%. The average effective dose was, respectively, of 0.219 and 0.073 mSv.Uld CT detects substantially more lung injuries in symptomatic patients with suspected early stage SARS-CoV-2 pneumonia compared to chest radiographs, with a significantly better inter-reader agreement, at the cost of a slightly higher equivalent radiation dose.


Subject(s)
COVID-19/diagnosis , Lung/diagnostic imaging , Radiography, Thoracic/statistics & numerical data , SARS-CoV-2/isolation & purification , Tomography, X-Ray Computed/statistics & numerical data , Adult , Aged , Aged, 80 and over , COVID-19/virology , COVID-19 Nucleic Acid Testing , Female , Humans , Male , Middle Aged , Observer Variation , Predictive Value of Tests , RNA, Viral/isolation & purification , Radiation Dosage , Radiography, Thoracic/adverse effects , Radiography, Thoracic/methods , Radiometry/statistics & numerical data , Retrospective Studies , SARS-CoV-2/genetics , Tomography, X-Ray Computed/adverse effects , Tomography, X-Ray Computed/methods
4.
Medicine (Baltimore) ; 100(21): e25645, 2021 May 28.
Article in English | MEDLINE | ID: covidwho-2190994

ABSTRACT

ABSTRACT: Since December 2019, pneumonia caused by a novel coronavirus (SARS-CoV-2), namely 2019 novel coronavirus disease (COVID-19), has rapidly spread from Wuhan city to other cities across China. The present study was designed to describe the epidemiology, clinical characteristics, treatment, and prognosis of 74 hospitalized patients with COVID-19.Clinical data of 74 COVID-19 patients were collected to analyze the epidemiological, demographic, laboratory, radiological, and treatment data. Thirty-two patients were followed up and tested for the presence of the viral nucleic acid and by pulmonary computed tomography (CT) scan at 7 and 14 days after they were discharged.Among all COVID-19 patients, the median incubation period for patients and the median period from symptom onset to admission was all 6 days; the median length of hospitalization was 13 days. Fever symptoms were presented in 83.78% of the patients, and the second most common symptom was cough (74.32%), followed by fatigue and expectoration (27.03%). Inflammatory indicators, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) of the intensive care unit (ICU) patients were significantly higher than that of the non-ICU patients (P < .05). However, 50.00% of the ICU patients had their the ratio of T helper cells to cytotoxic T cells (CD4/CD8) ratio lower than 1.1, whose proportion is much higher than that in non-ICU patients (P < .01).Compared with patients in Wuhan, COVID-19 patients in Anhui Province seemed to have milder symptoms of infection, suggesting that there may be some regional differences in the transmission of SARS-CoV-2 between different cities.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/diagnosis , Cough/epidemiology , Fever/epidemiology , Hyperbaric Oxygenation/statistics & numerical data , Adolescent , Adult , Aged , Antibiotic Prophylaxis/statistics & numerical data , Blood Sedimentation , C-Reactive Protein/analysis , COVID-19/complications , COVID-19/epidemiology , COVID-19/therapy , COVID-19 Nucleic Acid Testing , Child , Child, Preschool , China/epidemiology , Cities/epidemiology , Cough/blood , Cough/therapy , Cough/virology , Female , Fever/blood , Fever/therapy , Fever/virology , Follow-Up Studies , Geography , Humans , Length of Stay/statistics & numerical data , Lung/diagnostic imaging , Male , Middle Aged , RNA, Viral/isolation & purification , Retrospective Studies , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Severity of Illness Index , Tomography, X-Ray Computed , Young Adult
5.
Technol Health Care ; 30(6): 1299-1314, 2022.
Article in English | MEDLINE | ID: covidwho-2154631

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a deadly viral infection spreading rapidly around the world since its outbreak in 2019. In the worst case a patient's organ may fail leading to death. Therefore, early diagnosis is crucial to provide patients with adequate and effective treatment. OBJECTIVE: This paper aims to build machine learning prediction models to automatically diagnose COVID-19 severity with clinical and computed tomography (CT) radiomics features. METHOD: P-V-Net was used to segment the lung parenchyma and then radiomics was used to extract CT radiomics features from the segmented lung parenchyma regions. Over-sampling, under-sampling, and a combination of over- and under-sampling methods were used to solve the data imbalance problem. RandomForest was used to screen out the optimal number of features. Eight different machine learning classification algorithms were used to analyze the data. RESULTS: The experimental results showed that the COVID-19 mild-severe prediction model trained with clinical and CT radiomics features had the best prediction results. The accuracy of the GBDT classifier was 0.931, the ROUAUC 0.942, and the AUCPRC 0.694, which indicated it was better than other classifiers. CONCLUSION: This study can help clinicians identify patients at risk of severe COVID-19 deterioration early on and provide some treatment for these patients as soon as possible. It can also assist physicians in prognostic efficacy assessment and decision making.


Subject(s)
COVID-19 , Humans , COVID-19/diagnostic imaging , Tomography, X-Ray Computed/methods , Machine Learning , Lung/diagnostic imaging , Algorithms , Retrospective Studies
6.
J Comput Assist Tomogr ; 46(4): 576-583, 2022.
Article in English | MEDLINE | ID: covidwho-2152278

ABSTRACT

METHODS: This study used the Personalized Rapid Estimation of Dose in CT (PREDICT) tool to estimate patient-specific organ doses from CT image data. The PREDICT is a research tool that combines a linear Boltzmann transport equation solver for radiation dose map generation with deep learning algorithms for organ contouring. Computed tomography images from 74 subjects in the Medical Imaging Data Resource Center-RSNA International COVID-19 Open Radiology Database data set (chest CT of adult patients positive for COVID-19), which included expert annotations including "infectious opacities," were analyzed. First, the full z-scan length of the CT image data set was evaluated. Next, the z-scan length was reduced from the left hemidiaphragm to the top of the aortic arch. Generic dose reduction based on dose length product (DLP) and patient-specific organ dose reductions were calculated. The percentage of infectious opacities excluded from the reduced z-scan length was used to quantify the effect on diagnostic utility. RESULTS: Generic dose reduction, based on DLP, was 69%. The organ dose reduction ranged from approximately equal to 18% (breasts) to approximately equal to 64% (bone surface and bone marrow). On average, 12.4% of the infectious opacities were not included in the reduced z-coverage, per patient, of which 5.1% were above the top of the arch and 7.5% below the left hemidiaphragm. CONCLUSIONS: Limiting z-scan length of chest CTs reduced radiation dose without significantly compromising diagnostic utility in COVID-19 patients. The PREDICT demonstrated that patient-specific organ dose reductions varied from generic dose reduction based on DLP.


Subject(s)
COVID-19 , Drug Tapering , Adult , Humans , Radiation Dosage , Thorax , Tomography, X-Ray Computed/methods
7.
N Z Med J ; 135(1557): 10-18, 2022 Jul 01.
Article in English | MEDLINE | ID: covidwho-2147084

ABSTRACT

AIM: The purpose of this study was to determine the utility of community-based imaging to reduce use of inpatient surgical resources and enforce social distancing at the outset of the COVID-19 pandemic. METHOD: A prospective evaluation of community-based CT for patients presenting to Christchurch general practitioners with acute abdominal pain from April to November 2020. Eligible patients were discussed with the on-call general surgical team, and then referred for CT abdomen rather than hospital assessment. The positivity rate of CT scans, the 30-day all-cause hospital admission rate, and the proportion of patients where community scanning altered management setting and the number of incidental findings, were all assessed. RESULTS: Of 131 included patients, 67 (51%) patients had a positive CT scan. Thirty-nine (30%) patients were admitted to hospital within 30 days, 34 (87%) of whom had a positive CT scan and were admitted under a surgical specialty. Ninety-two (70%) patients did not require hospital admission for their acute abdominal pain, thirty-three (35%) of whom had a positive CT scan. There were three deaths within 30 days of the community CT, and the setting of the community CT did not contribute to the death of any of the cases. Forty patients (30%) had incidental findings on CT, 10 (25%) of which were significant and were referred for further investigation. CONCLUSION: Community based abdominal CT scanning is a feasible option in the management of acute abdominal pain. While trialed in response to the initial nationwide COVID-19 lockdown in New Zealand, there may be utility for acute community-based CT scanning in regular practice.


Subject(s)
Abdomen, Acute , COVID-19 , Abdomen , Abdomen, Acute/diagnostic imaging , Abdominal Pain/etiology , Communicable Disease Control , Humans , New Zealand/epidemiology , Pandemics , Retrospective Studies , Tomography, X-Ray Computed/methods
8.
Crit Care ; 26(1): 154, 2022 05 27.
Article in English | MEDLINE | ID: covidwho-1866391

ABSTRACT

BACKGROUND: The physiological effects of prone ventilation in ARDS patients have been discussed for a long time but have not been fully elucidated. Electrical impedance tomography (EIT) has emerged as a tool for bedside monitoring of pulmonary ventilation and perfusion, allowing the opportunity to obtain data. This study aimed to investigate the effect of prone positioning (PP) on ventilation-perfusion matching by contrast-enhanced EIT in patients with ARDS. DESIGN: Monocenter prospective physiologic study. SETTING: University medical ICU. PATIENTS: Ten mechanically ventilated ARDS patients who underwent PP. INTERVENTIONS: We performed EIT evaluation at the initiation of PP, 3 h after PP initiation and the end of PP during the first PP session. MEASUREMENTS AND MAIN RESULTS: The regional distribution of ventilation and perfusion was analyzed based on EIT images and compared to the clinical variables regarding respiratory and hemodynamic status. Prolonged prone ventilation improved oxygenation in the ARDS patients. Based on EIT measurements, the distribution of ventilation was homogenized and dorsal lung ventilation was significantly improved by PP administration, while the effect of PP on lung perfusion was relatively mild, with increased dorsal lung perfusion observed. The ventilation-perfusion matched region was found to increase and correlate with the increased PaO2/FiO2 by PP, which was attributed mainly to reduced shunt in the lung. CONCLUSIONS: Prolonged prone ventilation increased dorsal ventilation and perfusion, which resulted in improved ventilation-perfusion matching and oxygenation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04725227. Registered on 25 January 2021.


Subject(s)
Lung , Respiratory Distress Syndrome , Electric Impedance , Humans , Perfusion , Prone Position , Prospective Studies , Respiratory Distress Syndrome/therapy , Tomography, X-Ray Computed
9.
S Afr Med J ; 112(11): 850-854, 2022 Nov 01.
Article in English | MEDLINE | ID: covidwho-2144965

ABSTRACT

BACKGROUND: Available clinical data have revealed that COVID-19 is associated with a risk of pulmonary microthrombosis and small airway disease, especially in patients with severe disease. These patients present with persistent pulmonary symptoms after recovery, with ventilation and perfusion abnormalities present on several imaging modalities. Few data are available on the occurrence of this complication in patients who earlier presented with a milder form of COVID-19, and their long-term follow-up. OBJECTIVE: To assess the incidence of persistent lung perfusion abnormalities as a result of suspected air trapping or microthrombosis in non-hospitalised patients diagnosed with COVID-19. The long-term follow-up of these patients will also be investigated. METHODS: This was a retrospective study conducted at the nuclear medicine department of Universitas Academic Hospital, Bloemfontein. We reviewed the studies of 78 non-hospitalised patients with SARS-CoV-2 infection referred to our department from July 2020 to June 2021 for a perfusion-only single-photon emission computed tomography/computed tomography (SPECT/CT) study or a ventilation perfusion (VQ) SPECT/CT study. All 78 patients were suspected of having pulmonary embolism, and had raised D-dimer levels, with persistent, worsening or new onset of cardiopulmonary symptoms after the diagnosis of COVID-19. RESULTS: Seventy-eight patients were studied. The median (interquartile range) age was 45 (41 - 58) years and the majority (88.5%) were females. Twenty-two (28.2%) of these patients had matching VQ defects with mosaic attenuation on CT. All 9 of the patients who had follow-up studies had abnormalities that persisted, even after 1 year. CONCLUSION: We confirm that persistent ventilation and perfusion abnormalities suspicious of small airway disease and pulmonary microthrombosis can occur in non-hospitalised patients diagnosed with a milder form of COVID-19. Our study also shows that these complications remain present even 1 year after the initial diagnosis of COVID-19.


Subject(s)
COVID-19 , Lung Diseases , Female , Humans , Middle Aged , Male , COVID-19/epidemiology , Pandemics , Incidence , Retrospective Studies , Follow-Up Studies , Tomography, Emission-Computed, Single-Photon/methods , Tomography, X-Ray Computed/methods , SARS-CoV-2 , South Africa , Lung/diagnostic imaging , Perfusion
11.
Semin Respir Crit Care Med ; 43(6): 899-923, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2133781

ABSTRACT

Radiology plays an important role in the management of the most seriously ill patients in the hospital. Over the years, continued advances in imaging technology have contributed to an improvement in patient care. However, even with such advances, the portable chest radiograph (CXR) remains one of the most commonly requested radiographic examinations. While they provide valuable information, CXRs remain relatively insensitive at revealing abnormalities and are often nonspecific. Chest computed tomography (CT) can display findings that are occult on CXR and is particularly useful at identifying and characterizing pleural effusions, detecting barotrauma including small pneumothoraces, distinguishing pneumonia from atelectasis, and revealing unsuspected or additional abnormalities which could result in increased morbidity and mortality if left untreated. CT pulmonary angiography is the modality of choice in the evaluation of pulmonary emboli which can complicate the hospital course of the ICU patient. This article will provide guidance for interpretation of CXR and thoracic CT images, discuss some of the invasive devices routinely used, and review the radiologic manifestations of common pathologic disease states encountered in ICU patients. In addition, imaging findings and complications of more specific clinical scenarios in which the incidence has increased in the ICU setting, such as patients who are immunocompromised, have interstitial lung disease, or COVID-19, will also be discussed. Communication between the radiologist and intensivist, particularly on complicated cases, is important to help increase diagnostic accuracy and leads to an improvement in the management of the most critically ill patients.


Subject(s)
COVID-19 , Pneumothorax , Humans , COVID-19/diagnostic imaging , Intensive Care Units , Tomography, X-Ray Computed , Communication
12.
Front Public Health ; 10: 931480, 2022.
Article in English | MEDLINE | ID: covidwho-2123468

ABSTRACT

Background: Omicron has become the dominant variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) globally. We aimed to compare the clinical and pulmonary computed tomography (CT) characteristics of the patients infected with SARS-CoV-2 Omicron with those of patients infected with the Alpha viral strain. Methods: Clinical profiles and pulmonary CT images of 420 patients diagnosed with coronavirus disease-2019 (COVID-19) at Ningbo First Hospital between January 2020 and April 2022 were collected. Demographic characteristics, symptoms, and imaging manifestations of patients infected with the SARS-CoV-2 Omicron variant were compared with those of patients infected with the Alpha strain. Results: A total of 38 patients were diagnosed to be infected with the Alpha strain of SARS-CoV-2, whereas 382 patients were thought to be infected with the Omicron variant. Compared with patients infected with the Alpha strain, those infected with the Omicron variant were younger, and a higher proportion of men were infected (P < 0.001). Notably, 93 (24.3%) of the patients infected with Omicron were asymptomatic, whereas only two (5.3%) of the patients infected with the Alpha strain were asymptomatic. Fever (65.8%), cough (63.2%), shortness of breath (21.1%), and diarrhea (21.1%) were more common in patients infected with the SARS-CoV-2 Alpha strain, while runny nose (24.1%), sore throat (31.9%), body aches (13.6%), and headache (12.3%) were more common in patients with the Omicron variant. Compared with 33 (86.84%) of 38 patients infected with the Alpha strain, who had viral pneumonia on pulmonary CT images, only 5 (1.3%) of 382 patients infected with the Omicron variant had mild foci. In addition, the distribution of opacities in the five patients was unilateral and centrilobular, whereas most patients infected with the Alpha strain had bilateral involvement and multiple lesions in the peripheral zones of the lung. Conclusion: The SARS-CoV-2 Alpha strain mainly affects the lungs, while Omicron is confined to the upper respiratory tract in patients with COVID-19.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnostic imaging , Humans , Lung/diagnostic imaging , Lung/pathology , Male , Tomography, X-Ray Computed
13.
Ann Intern Med ; 173(4): 268-277, 2020 08 18.
Article in English | MEDLINE | ID: covidwho-2110835

ABSTRACT

BACKGROUND: The new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 210 000 deaths worldwide. However, little is known about the causes of death and the virus's pathologic features. OBJECTIVE: To validate and compare clinical findings with data from medical autopsy, virtual autopsy, and virologic tests. DESIGN: Prospective cohort study. SETTING: Autopsies performed at a single academic medical center, as mandated by the German federal state of Hamburg for patients dying with a polymerase chain reaction-confirmed diagnosis of COVID-19. PATIENTS: The first 12 consecutive COVID-19-positive deaths. MEASUREMENTS: Complete autopsy, including postmortem computed tomography and histopathologic and virologic analysis, was performed. Clinical data and medical course were evaluated. RESULTS: Median patient age was 73 years (range, 52 to 87 years), 75% of patients were male, and death occurred in the hospital (n = 10) or outpatient sector (n = 2). Coronary heart disease and asthma or chronic obstructive pulmonary disease were the most common comorbid conditions (50% and 25%, respectively). Autopsy revealed deep venous thrombosis in 7 of 12 patients (58%) in whom venous thromboembolism was not suspected before death; pulmonary embolism was the direct cause of death in 4 patients. Postmortem computed tomography revealed reticular infiltration of the lungs with severe bilateral, dense consolidation, whereas histomorphologically diffuse alveolar damage was seen in 8 patients. In all patients, SARS-CoV-2 RNA was detected in the lung at high concentrations; viremia in 6 of 10 and 5 of 12 patients demonstrated high viral RNA titers in the liver, kidney, or heart. LIMITATION: Limited sample size. CONCLUSION: The high incidence of thromboembolic events suggests an important role of COVID-19-induced coagulopathy. Further studies are needed to investigate the molecular mechanism and overall clinical incidence of COVID-19-related death, as well as possible therapeutic interventions to reduce it. PRIMARY FUNDING SOURCE: University Medical Center Hamburg-Eppendorf.


Subject(s)
Autopsy/methods , Coronavirus Infections/mortality , Pneumonia, Viral/mortality , Pulmonary Embolism/mortality , Venous Thromboembolism/mortality , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Cause of Death , Female , Germany/epidemiology , Humans , Male , Middle Aged , Pandemics , Prospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed
14.
Medicine (Baltimore) ; 101(39): e30744, 2022 Sep 30.
Article in English | MEDLINE | ID: covidwho-2113766

ABSTRACT

OBJECTIVE: The aim of this study was to compare the radiographic features of patients with progressive and nonprogressive coronavirus disease 2019 (COVID-19) pneumonia. METHODS: PubMed, Embase, and Cochrane Library databases were searched from January 1, 2020, to February 28, 2022, by using the keywords: "COVID-19", "novel Coronavirus", "2019-novel coronavirus", "CT", "radiology" and "imaging". We summarized the computed tomography manifestations of progressive and nonprogressive COVID-19 pneumonia. The meta-analysis was performed using the Stata statistical software version 16.0. RESULTS: A total of 10 studies with 1092 patients were included in this analysis. The findings of this meta-analysis indicated that the dominating computed tomography characteristics of progressive patients were a crazy-paving pattern (odds ratio [OR] = 2.10) and patchy shadowing (OR = 1.64). The dominating lesions distribution of progressive patients were bilateral (OR = 11.62), central mixed subpleural (OR = 1.37), and central (OR = 1.36). The other dominating lesions of progressive patients were pleura thickening (OR = 2.13), lymphadenopathy (OR = 1.74), vascular enlargement (OR = 1.39), air bronchogram (OR = 1.29), and pleural effusion (OR = 1.29). Two patterns of lesions showed significant links with the progression of disease: nodule (P = .001) and crazy-paving pattern (P = .023). Four lesions distribution showed significant links with the progression of disease: bilateral (P = .004), right upper lobe (P = .003), right middle lobe (P = .001), and left upper lobe (P = .018). CONCLUSION: Nodules, crazy-paving pattern, and/or new lesions in bilateral, upper and middle lobe of right lung, and lower lobe of left lung may indicate disease deterioration. Clinicians should formulate or modify treatment strategies in time according to these specific conditions.


Subject(s)
COVID-19 , Pneumonia , COVID-19/diagnostic imaging , Humans , Lung/diagnostic imaging , Lung/pathology , Pneumonia/pathology , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed/methods
15.
Anal Chem ; 94(47): 16361-16368, 2022 Nov 29.
Article in English | MEDLINE | ID: covidwho-2119248

ABSTRACT

The unstoppable spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely threatened public health over the past 2 years. The current ubiquitously accepted method for its diagnosis provides sensitive detection of the virus; however, it is relatively time-consuming and costly, not to mention the need for highly skilled personnel. There is a clear need to develop novel computer-based diagnostic tools to provide rapid, cost-efficient, and time-saving detection in places where massive traditional testing is not practical. Here, we develop an electrochemiluminescence (ECL)-based detection system whose results are quantified as reverse transcriptase polymerase chain reaction (RT-PCR) cyclic threshold (CT) values. A concentration-dependent signal is generated upon the introduction of the virus to the electrode and is recorded with a smartphone camera. The ECL images are used to train machine learning algorithms, and a model using artificial neural networks (ANNs) for 45 samples was developed. The model demonstrated more than 90% accuracy in the diagnosis of 50 unknown real samples, detecting up to a CT value of 32 and a limit of detection (LOD) of 10-12 g mL-1 in the testing of artificial samples.


Subject(s)
COVID-19 , Humans , COVID-19/diagnosis , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2/genetics , Smartphone , Sensitivity and Specificity , Machine Learning , Immunoassay , Tomography, X-Ray Computed
16.
Technol Health Care ; 30(6): 1273-1286, 2022.
Article in English | MEDLINE | ID: covidwho-2119015

ABSTRACT

BACKGROUND: The infection caused by the SARS-CoV-2 (COVID-19) pandemic is a threat to human lives. An early and accurate diagnosis is necessary for treatment. OBJECTIVE: The study presents an efficient classification methodology for precise identification of infection caused by COVID-19 using CT and X-ray images. METHODS: The depthwise separable convolution-based model of MobileNet V2 was exploited for feature extraction. The features of infection were supplied to the SVM classifier for training which produced accurate classification results. RESULT: The accuracies for CT and X-ray images are 99.42% and 98.54% respectively. The MCC score was used to avoid any mislead caused by accuracy and F1 score as it is more mathematically balanced metric. The MCC scores obtained for CT and X-ray were 0.9852 and 0.9657, respectively. The Youden's index showed a significant improvement of more than 2% for both imaging techniques. CONCLUSION: The proposed transfer learning-based approach obtained the best results for all evaluation metrics and produced reliable results for the accurate identification of COVID-19 symptoms. This study can help in reducing the time in diagnosis of the infection.


Subject(s)
COVID-19 , Deep Learning , Humans , COVID-19/diagnostic imaging , SARS-CoV-2 , X-Rays , Tomography, X-Ray Computed/methods
17.
Radiology ; 305(3): 538-554, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2117945

ABSTRACT

This review focuses on three key noninvasive cardiac imaging modalities-cardiac CT angiography (CTA), MRI, and PET/CT-and summarizes key publications in 2021 relevant to radiologists in clinical practice. Although this review focuses primarily on articles published in Radiology, important studies from other major journals are included to highlight "must-know" articles in the field of cardiovascular imaging. Cardiac CTA has been established as the first-line test for patients with stable chest pain and no known coronary artery disease, and its value remains central to the assessment of surgical or transcatheter aortic valve replacement. Artificial intelligence continues to evolve in a number of applications in cardiovascular disease. In cardiac MRI studies, 2021 has seen an emphasis on nonischemic cardiomyopathies, valvular heart disease, and COVID-19 disease cardiac manifestations and the authors highlight the key articles on these topics. A section featuring the increasing role of cardiac PET/CT in the assessment of cardiac sarcoidosis and prosthetic valves is also provided.


Subject(s)
COVID-19 , Positron Emission Tomography Computed Tomography , Humans , Artificial Intelligence , Tomography, X-Ray Computed/methods , Magnetic Resonance Imaging
18.
Curr Med Imaging ; 18(14): 1536-1539, 2022.
Article in English | MEDLINE | ID: covidwho-2117596

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19, previously known as novel coronavirus [2019-nCoV]), first reported in China, has now been declared a global health emergency by World Health Organization. The clinical severity ranges from asymptomatic individuals to death. Here, we report clinical features and radiological changes of a cured family cluster infected with COVID-19. CASE PRESENTATION: In this report, we enrolled a family of 4 members who were admitted to our hospital in January 2020. We performed a detailed analysis of each patient's records. All patients underwent chest computed tomography (CT) examination with 120 kilovolts peak and 150 kilovolt-ampere. Realtime polymerase chain reaction (RT-PCR) examinations for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid were done using nasopharyngeal swabs. CONCLUSION: In the family members infected with COVID-19 who were accompanied by other diseases or had low immunity, the pneumonia was prone to be aggravated.


Subject(s)
COVID-19 , Humans , COVID-19/diagnostic imaging , SARS-CoV-2 , Tomography, X-Ray Computed , Radiography , China
19.
Ulus Travma Acil Cerrahi Derg ; 28(11): 1655-1658, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2111172

ABSTRACT

The pulmonary symptoms secondary to severe acute respiratory syndrome in coronavirus (COVID-19) infections are the most common presentation for the disease; however, it is now known that in a small portion of patients, severe hemorrhagic complications can also be seen. In this report, three cases of elderly women with known COVID-19 infection, developing spontaneous rectus sheath hematoma on anticoagulation therapy, are presented. Three cases presented above emphasize the need to perform a computed tomography examination after a sudden hemodynamic deterioration and a decrease in hemoglobin count in COVID-19 patients in intensive care units (ICUs). Since this clinical deterioration can be caused by spontaneous rectus sheath hematomas (RSH), it must be taken into consideration while examination. If these RSHs rupture into the abdominal cavity, the outcome may be fatal in few hours as represented in two of our cases. Major spontaneous hemorrhage in COVID-19 patients is quite uncommon; therefore, it may cause serious complications as it is rarely taken into consideration. Failure to acknowledge such a risk could significantly worsen the prognosis of the patients especially in ERs and ICUs.


Subject(s)
COVID-19 , Muscular Diseases , Humans , Female , Aged , Rectus Abdominis/diagnostic imaging , COVID-19/complications , Hematoma/etiology , Hematoma/complications , Muscular Diseases/complications , Muscular Diseases/therapy , Tomography, X-Ray Computed , Anticoagulants/adverse effects
20.
Medicine (Baltimore) ; 101(37): e30655, 2022 Sep 16.
Article in English | MEDLINE | ID: covidwho-2107668

ABSTRACT

The spread of abnormal opacity on chest computed tomography (CT) has been reported as a predictor of coronavirus disease 2019 (COVID-19) severity; however, the relationship between CT findings and prognosis in patients with severe COVID-19 remains unclear. The objective of this study was to evaluate the extent of abnormal opacity on chest CT and its association with prognosis in patients with COVID-19 in a critical care medical center, using a simple semi-quantitative method. This single-center case-control study included patients diagnosed with severe COVID-19 pneumonia who were admitted to a critical care center. The diagnosis of COVID-19 was based on positive results of a reverse transcription polymerase chain reaction test. All patients underwent non-contrast whole-body CT upon admission. Six representative axial chest CT images were selected for each patient to evaluate the extent of lung lesions. The percentage of the area involved in the representative CT images was visually assessed by 2 radiologists and scored on 4-point scale to obtain the bedside CT score, which was compared between patients who survived and those who died using the Mann-Whitney U test. A total of 63 patients were included in this study: 51 survived and 12 died after intensive treatment. The inter-rater reliability of bedside scores between the 2 radiologists was acceptable. The median bedside CT score of the survival group was 12.5 and that of the mortality group was 16.5; the difference between the 2 groups was statistically significant. The degree of opacity can be easily scored using representative CT images in patients with severe COVID-19 pneumonia, without sophisticated software. A greater extent of abnormal opacity is associated with poorer prognosis. Predicting the prognosis of patients with severe COVID-19 could facilitate prompt and appropriate treatment.


Subject(s)
COVID-19 , Pneumonia , COVID-19/diagnostic imaging , Case-Control Studies , Critical Care , Humans , Reproducibility of Results , Tomography, X-Ray Computed/methods
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