Korean journal of radiology : official journal of the Korean Radiological Society
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To describe the experience of implementing a deep learning-based computer-aided detection (CAD) system for the interpretation of chest X-ray radiographs (CXR) of suspected coronavirus disease (COVID-19) patients and investigate the diagnostic performance of CXR interpretation with CAD assistance. ⋯ Radiologists with CAD assistance could identify patients with rRT-PCR-positive COVID-19 or pneumonia on CXR with a reasonably acceptable performance. In patients suspected with COVID-19, CXR had much faster TATs than rRT-PCRs.
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The epidemic of 2019 novel coronavirus, later named as coronavirus disease (COVID-19), began in Wuhan, China in December 2019 and has spread rapidly worldwide. Early diagnosis is crucial for the management of the patients with COVID-19, but the gold standard diagnostic test for this infection, the reverse transcriptase polymerase chain reaction, has a low sensitivity and an increased turnaround time. In this scenario, chest computed tomography (CT) could play a key role for an early diagnosis of COVID-19 pneumonia. Here, we have reported a confirmed case of COVID-19 with an atypical CT presentation showing a "double halo sign," which we believe represents the pathological spectrum of this viral pneumonia.
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This study aimed to evaluate the diagnostic value of combining the quantitative parameters of shear wave elastography (SWE) and superb microvascular imaging (SMI) to breast ultrasound (US) to differentiate between benign and malignant breast masses. ⋯ Combining all quantitative values of SWE and SMI with B-mode US improved the diagnostic performance in differentiating between benign and malignant breast lesions.
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To assess the incremental prognostic value of coronary computed tomography angiography (CCTA) in comparison to a clinical risk model (Framingham risk score, FRS) and coronary artery calcium score (CACS) for future cardiac events in ischemic stroke patients without chest pain. ⋯ Assessment of stenosis degree and plaque type using CCTA provided additional prognostic value over CACS and FRS to risk stratify stroke patients without prior history of CAD better.
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The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19). ⋯ Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.