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1.
Diagnostics (Basel) ; 12(3)2022 Mar 18.
Article in English | MEDLINE | ID: covidwho-1760433

ABSTRACT

In this study, we first developed an artificial intelligence (AI)-based algorithm for classifying chest computed tomography (CT) images using the coronavirus disease 2019 Reporting and Data System (CO-RADS). Subsequently, we evaluated its accuracy by comparing the calculated scores with those assigned by radiologists with varying levels of experience. This study included patients with suspected SARS-CoV-2 infection who underwent chest CT imaging between February and October 2020 in Japan, a non-endemic area. For each chest CT, the CO-RADS scores, determined by consensus among three experienced chest radiologists, were used as the gold standard. Images from 412 patients were used to train the model, whereas images from 83 patients were tested to obtain AI-based CO-RADS scores for each image. Six independent raters (one medical student, two residents, and three board-certified radiologists) evaluated the test images. Intraclass correlation coefficients (ICC) and weighted kappa values were calculated to determine the inter-rater agreement with the gold standard. The mean ICC and weighted kappa were 0.754 and 0.752 for the medical student and residents (taken together), 0.851 and 0.850 for the diagnostic radiologists, and 0.913 and 0.912 for AI, respectively. The CO-RADS scores calculated using our AI-based algorithm were comparable to those assigned by radiologists, indicating the accuracy and high reproducibility of our model. Our study findings would enable accurate reading, particularly in areas where radiologists are unavailable, and contribute to improvements in patient management and workflow.

2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-317164

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) continues to spread worldwide. Because of the absence of reliable rapid diagnostic systems, patients with COVID-19 symptoms are suspected of disease. Computed tomography (CT) in patients with suspected COVID-19 may be reasonable for triaging, and CT-first triage strategies have been proposed. However, clinical evaluation of a CT-first triage protocol is lacking. The aim of this study is to investigate the real-world efficacy and limitations of a CT-first triage strategy in patients with suspected COVID-19. Methods: : This was a single-center cohort study evaluating outpatients with suspected COVID-19 who underwent a medical examination at Yokohama City University Hospital and who were prospectively registered between 9 February and 5 May 2020. We treated patients according to the CT-first triage protocol. CT findings were classified into five categories according to the COVID-19 Reporting and Data System (CO-RADS). With the CT-first triage protocol, patients with a suspicious clinical history, symptoms, or suspicious findings on chest CT were allocated to the COVID-19 suspected group. The primary outcome was efficacy of the CT-first triage protocol for outpatients with suspected COVID-19. We conducted additional analyses of the isolation time of outpatients with suspected COVID-19 and reached final diagnoses. Results: : In total, 108 outpatients with suspected COVID-19 were examined at our hospital. Forty-eight patients (44.9%) were categorized as CO-RADS 1, 26 patients (24.3%) as CO-RADS 2, 14 patients (13.1%) as CO-RADS 3, 6 patients (5.6%) as CO-RADS 4, and 13 patients (12.1%) as CO-RADS 5. One patient was excluded because of pregnancy. Using the CT-first triage protocol, 48 (44.9%) patients were suspected of having COVID-19. Nine patients (18.8%) in this group were positive for severe acute respiratory syndrome coronavirus 2 using polymerase chain reaction;no patients in the group not suspected of having COVID-19 were diagnosed with COVID-19 during follow up. The protocol significantly shortened the duration of isolation for the not-suspected versus the suspected group (70.5 vs. 1037.0 minutes, P < .001). Conclusions: : Our CT-first triage protocol was acceptable for triaging outpatients with suspected COVID-19. This protocol will be helpful for appropriate triage, especially in areas where polymerase chain reaction is limited.

4.
Medicine (Baltimore) ; 100(22): e26161, 2021 Jun 04.
Article in English | MEDLINE | ID: covidwho-1258818

ABSTRACT

ABSTRACT: The Coronavirus disease 2019 pandemic continues to spread worldwide. Because of the absence of reliable rapid diagnostic systems, patients with symptoms of Coronavirus disease 2019 are treated as suspected of the disease. Use of computed tomography findings in Coronavirus disease 2019 are expected to be a reasonable method for triaging patients, and computed tomography-first triage strategies have been proposed. However, clinical evaluation of a computed tomography-first triage protocol is lacking.The aim of this study is to investigate the real-world efficacy and limitations of a computed tomography-first triage strategy in patients with suspected Coronavirus disease 2019.This was a single-center cohort study evaluating outpatients with fever who received medical examination at Yokohama City University Hospital, prospectively registered between 9 February and 5 May 2020. We treated according to the computed tomography-first triage protocol. The primary outcome was efficacy of the computed tomography-first triage protocol for patients with fever in an outpatient clinic. Efficacy of the computed tomography-first triage protocol for outpatients with fever was evaluated using sensitivity, specificity, positive predictive value, and negative predictive value. We conducted additional analyses of the isolation time of feverish outpatients and final diagnoses.In total, 108 consecutive outpatients with fever were examined at our hospital. Using the computed tomography-first triage protocol, 48 (44.9%) patients were classified as suspected Coronavirus disease 2019. Nine patients (18.8%) in this group were positive for severe acute respiratory syndrome coronavirus 2 using polymerase chain reaction; no patients in the group considered less likely to have Coronavirus disease 2019 tested positive for the virus. The protocol significantly shortened the duration of isolation for the not-suspected versus the suspected group (70.5 vs 1037.0 minutes, P < .001).Our computed tomography-first triage protocol was acceptable for screening patients with suspected Coronavirus disease 2019. This protocol will be helpful for appropriate triage, especially in areas where polymerase chain reaction is inadequate.


Subject(s)
COVID-19/diagnostic imaging , Tomography, X-Ray Computed/methods , Triage/methods , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Clinical Protocols , Comorbidity , Female , Humans , Japan , Male , Middle Aged , SARS-CoV-2 , Sensitivity and Specificity , Severity of Illness Index , Sex Factors , Young Adult
7.
Jpn J Radiol ; 38(5): 391-393, 2020 May.
Article in English | MEDLINE | ID: covidwho-9202

ABSTRACT

A novel coronavirus (severe acute respiratory syndrome coronavirus 2) causes a cluster of pneumonia cases in Wuhan, China. It spread rapidly and globally. CT imaging is helpful for the evaluation of the novel coronavirus disease 2019 (COVID-19) pneumonia. Infection control inside the CT suites is also important to prevent hospital-related transmission of COVID-19. We present our experience with infection control protocol for COVID-19 inside the CT suites.


Subject(s)
Coronavirus Infections/prevention & control , Infection Control/methods , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Tomography, X-Ray Computed/methods , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/transmission , Humans , Infection Control/standards , Personal Protective Equipment , Pneumonia, Viral/transmission , Radiology Department, Hospital/standards , SARS-CoV-2 , Tomography, X-Ray Computed/instrumentation , Tomography, X-Ray Computed/standards
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