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Updated: Nov 22, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Spectrum of lung perfusion changes on dual-energy CT in COVID-19: incremental benefit to conventional CT
Srujana Ganti1, Shawn Shi Xian Kok2, Syed Aftab2
1Department of Radiology, Sengkang General Hospital, 110, Sengkang East Way, Singapore, 544886, Republic of Singapore. ganti.srujana@singhealth.com.sg.
Abstract:
The purpose of this case report is to demonstrate lung perfusion changes on dual-energy CT (DECT) in patients with Coronavirus disease 2019 (COVID-19). Since the first case of COVID-19 was reported in Wuhan, Hubei province in China, the spectrum of lung parenchymal findings has been well described but the underlying pathophysiology is less well understood. DECT imaging contributes to the growing evidence that vascular dysregulation has an important role in the underlying pathophysiology of the disease. Three patients with reverse transcriptase polymerase chain reaction (RT-PCR)-confirmed COVID-19 underwent DECT scans. One patient had a DECT for persistent spikes in temperature while the other two patients underwent dual-energy CT pulmonary angiograms (CTPA) for worsening shortness of breath, elevated D dimers and suspected pulmonary embolism. The perfusion abnormalities include focal areas of both hyperperfusion, hypoperfusion, and areas of hypoperfusion surrounded by hyperemia. In addition, dilatation of segmental and subsegmental pulmonary arteries was seen in relation to the lung parenchymal change. DECT has proven useful in supporting the hypothesis that vascular dysregulation plays a significant role in the pulmonary pathophysiology of COVID-19. Early identification and a high index of suspicion is required in the emergency department setting to identify and isolate cases even prior to the results of RT-PCR test being available. Vascular changes on DECT may be an additional radiological feature in detecting the presence of and predicting the severity of disease in the emergency department or acute care setting.
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