Abnormal pulmonary vessel and perfusion patterns often appear on CT pulmonary angiography (CTA) in patients with COVID-19 pneumonia, suggesting the important role pulmonary vascular pathology and hypoxemia play in the disease, according to a study published June 18 in Radiology: Cardiothoracic Imaging.
And adding dual-energy CT to CTA can help identify even more abnormal characteristics in the lungs of patients with COVID-19, wrote a group of researchers from Massachusetts General Hospital in Boston.
"Dual-energy CT pulmonary angiography provides insight on the vascular manifestations of COVID-19 pneumonia," a team led by Dr. Min Lang wrote.
Lang's group conducted a retrospective study that included 48 patients with reverse transcription polymerase chain reaction (RT-PCR)-confirmed COVID-19 pneumonia who had CTA between March 22 and April 5. Of these 48 patients, 25 also had dual-energy CT as part of the CTA protocol. Two chest radiologists read all the studies; any interpretation disagreements were resolved via consult with a third reader.
Of 48 patients, 45 were admitted to the hospital, 18 were admitted to the intensive care unit, and 13 required intubation. The group noted the following CTA findings:
- 15% of patients had pulmonary emboli.
- 85% had dilated vessels; of these, 78% showed vessel enlargement inside lung opacities and 55% showed vessel enlargement outside of lung opacities.
- 82% of patients had dilated distal vessels extending to the pleura and 61% had dilated distal vessels extending to the fissures.
Adding dual-energy CT to CTA helped identify further abnormalities caused by COVID-19, according to the group: 96% of patients who had dual-energy CT exams showed a mosaic perfusion pattern; 52% showed regional hyperemia corresponding with areas of pulmonary opacities, 96% showed opacities associated with oligemia, and 36% of cases showed hyperemic halo.
The takeaway? COVID-19's effects are not confined to the lungs -- they also include a "diffuse vascular process," according to the authors.
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
