Abstract
BackgroundCorona Virus Disease 2019 (COVID-19) is currently a worldwide pandemic and has a huge impact on public health and socio-economic development. The purpose of this study is to explore the diagnostic value of the quantitative computed tomography (CT) method by using different threshold segmentation techniques to distinguish between patients with or without COVID-19 pneumonia.MethodsA total of 47 patients with suspected COVID-19 were retrospectively analyzed, including nine patients with positive real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR) test (confirmed case group) and 38 patients with negative RT-PCR test (excluded case group). An improved 3D convolutional neural network (VB-Net) was used to automatically extract lung lesions. Eight different threshold segmentation methods were used to define the ground glass opacity (GGO) and consolidation. The receiver operating characteristic (ROC) curves were used to compare the performance of various parameters with different thresholds for diagnosing COVID-19 pneumonia.ResultsThe volume of GGO (VOGGO) and GGO percentage in the whole lung (GGOPITWL) were the most effective values for diagnosing COVID-19 at a threshold of − 300 HU, with areas under the curve (AUCs) of 0.769 and 0.769, sensitivity of 66.67 and 66.67%, specificity of 94.74 and 86.84%. Compared with VOGGO or GGOPITWL at a threshold of − 300 Hounsfield units (HU), the consolidation percentage in the whole lung (CPITWL) with thresholds at − 400 HU, − 350 HU, and − 250 HU were statistically different. There were statistical differences in the infection volume and percentage of the whole lung, right lung, and lobes between the two groups. VOGGO, GGOPITWL, and volume of consolidation (VOC) were also statistically different at the threshold of − 300 HU.ConclusionsQuantitative CT provides an image quantification method for the auxiliary diagnosis of COVID-19 and is expected to assist in confirming patients with COVID-19 pneumonia in suspected cases.
Highlights
Corona Virus Disease 2019 (COVID-19) is currently a worldwide pandemic and has a huge impact on public health and socio-economic development
Some radiology professional organizations and societies, including the Society of Thoracic Radiology (STR), the American College of Radiology (ACR), and the Radiological Society of North America (RSNA), have recommended against performing routine computed tomography (CT) for screening and preliminary diagnosis of COVID-19 [6], they play an important role in evaluating severe cases and monitoring disease progression [7,8,9]
Cases were in the non-COVID-19 group with a median age of (IQR 21.5) years, a female proportion of 50% and a median time of three (IQR 4.5) days from initial symptom onset to first CT scan
Summary
Corona Virus Disease 2019 (COVID-19) is currently a worldwide pandemic and has a huge impact on public health and socio-economic development. Corona Virus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus (SARSCoV-2) [1]. It is currently a worldwide pandemic and has a huge impact on public health and socio-economic development. A lung computed tomography (CT), on the other hand, is easy to perform and has a high sensitivity when diagnosing patients suspected of having COVID-19 [4], especially patients with COVID-19 who initially result negative to RT-PCR [5]. Ground glass opacity (GGO) and consolidation are the most common CT signs of COVID-19 pneumonia [10,11,12]
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