Patients and clinical follow-up
Thirty-one adults (>18 years) diagnosed with COVID–19 and hospitalized between March 15, 2020 and April 30, 2020 in Hacettepe University Adult Hospital, Ankara, Turkey (a 1000-bed tertiary care facility), who underwent DECT angiography because of suspected pulmonary thromboembolism (PE) were analyzed. COVID–19 was diagnosed using reverse-transcription polymerase chain reaction (RT-PCR) on nasopharyngeal smears. According to national guidelines, all RT-PCR confirmed COVID–19 patients were considered for hospital admission. Electronic records of the Hacettepe University Hospital and follow-up charts of the patients were reviewed by the authors (ISI, GTD, ACI) and saved in an electronic database. Gender, age, comorbidities, fever, SaPO2, daily follow-up records, medications to treat comorbidities and COVID–19 and results of blood biochemistry, complete blood count, coagulation tests, C-reactive protein (CRP), procalcitonin, urinalysis were also recorded in an electronic case record form. Confirmed patients that were evaluated as needing treatment as per the national guidelines were admitted to isolation wards. A suspected PE was based on clinical findings and/or elevated D-dimer serum levels (>1000 ng/mL). Patients were informed about the radiological procedure and provided informed consent. Pregnant women and those declining consent were excluded. Clinical disease severity for COVID–19 was defined as proposed by Feng et al . In brief, patients are categorized into four types. Type one had mild symptoms and no abnormal radiological findings. Type two had moderate symptoms and evidence of pneumonia on chest CT. Type three patients had either a high respiratory rate (≥30/min) or SaO2 (≤93%) or low oxygen partial pressure/inspired oxygen fraction (≤300 mmHg) in arterial blood. Type four patients needed mechanical ventilation or had shock or organ dysfunction needing intensive care unit (ICU) admission.
CT acquisition protocol and DECT Post-processing and Image Reconstruction
The DECT angiography images were obtained by third-generation dual-source CT (Somatom Force, Siemens Healthineers, Erlangen). Patients received intravenously 50–60mL iohexol (Omnipaque 350; GE Healthcare, Princeton, NJ), at a rate of 4.0 mL/sec via antecubital intravenous catheter, followed by a 40-ml saline chaser bolus. A region of interest (ROI) was placed over the pulmonary artery and acquisition was started when the ROI reaches 100 HU with a delay of 5 s. Craniocaudal acquisition was set with the following parameters: 80/140Sn kVp, modulated mA (CareDose 4D, Siemens Healthineers, Erlangen, Germany) with reference 80 mAs, rotation time 0.25 s, with a pitch of 0.7 and a collimation of (64 x 0.6 mm x 2).
Perfused Blood Volume (PBV) images and iodine maps were generated using DECT post-processing softwares (“Lung PBV” and “Virtual unenhanced” in syngo Dual Energy; Siemens Healthineers) on a dedicated workstation.
The DECT scanner generates three different series of images: 80-kV images, 140-kV images, and weighted-average images (similar to 120-kVp scan of the abdomen). Images were loaded to a dedicated DE post-processing workstation (Syngo Via VB10; Siemens Medical Solutions). By using Lung PBV application, iodine uptake distribution can be mapped to visualize perfusion. This calculation is based on a so-called three-material decomposition: Assuming that every voxel in the lung is composed of air, soft tissue, and iodine, the algorithm generates a map that encodes the iodine distribution in each individual CT voxel. To generate lung perfusion maps, we put an ROI on the pulmonary artery. We used scale factor of 0.15 to normalize the perfusion of the lung parenchyma. Lung volume and subvolume, mean contrast (iodine) enhancement in HU and relative enhancement in percentage can be measured automatically. In addition to lung PBV images, virtual noncontrast (VNC) image and iodine maps were obtained by using “virtual unenhanced” software. Iodine map can be superimposed on weighted-average or VNC images for visualization of iodine uptake distribution and anatomic information at the same time.
Morphologic images, lung perfusion maps and iodine maps were analyzed by three experienced readers (with 14, 24 and 32 years of CT experience). Image quality on the perfusion map was recorded as either excellent (no artifacts), good (minor artifacts), moderate (still able to assess iodine distribution), or poor (impossible to assess iodine distribution). The pulmonary DECT angiography image quality was excellent in 2 cases, good in 21 cases and moderate in 8 patients. The perfusion map images were then reviewed for the presence of any deficit. Perfusion map deficits were characterized as either overlapping with GGO or consolidation, not overlapping with GGO or consolidation, or band-like deficits consistent with artifact, often due to cardiac motion or beam hardening from contrast material within the superior vena cava or innominate vein. The lesions on CT images that are over 1 cm were also evaluated and recorded as GGO or consolidation and iodine uptake of these lesions was measured with three elliptic round of interest (ROI) on iodine map images and mean value was calculated.
Lung CT images were classified according to the extent of GGOs and the presence of consolidation and crazy-paving pattern in the lobes. The scores were defined as follows: 0 (none), one (affecting less than 5% of the lobe), two (affecting 5–25% of the lobe), three (affecting 26–49% of the lobe), four (affecting 50–75% of the lobe) and five (affecting more than 75% of the lobe) . If the crazy-paving pattern or consolidation appeared in one lobe, the CT score was increased by one for each of them. Therefore, a maximum CT score of seven was possible for each lobe. The total CT score was calculated by summing the five lobe scores (range from 0 to 35). Perfusion images were graded according to the extent of perfusion deficits (PDs). The grades were defined as follows: 0 (no PD), one (affecting only one area), two (affecting 1–3 PD areas), three (multiple bilateral PDs >4–10 areas), and four (bilateral PDs disseminated in all segments covering >50% of the total lung perfusion areas).
In 5 patients, pulmonary CTA examination did not include more than 75% of the longitudinal diameter of the kidneys and excluded from the kidney analyses. The kidneys were analyzed on VNC, iodine map and mixed DECT images. An ROI was placed over the abdominal aorta to normalize contrast enhancement before the analysis. Visual analysis of these images were performed by three radiologists in consensus. Homogeneous pattern on iodine map is defined as smooth appearance without low iodine uptake areas; heterogeneous pattern is defined as mottled appearance with alternating low and high iodine uptake. Density measurements were made on cortex of the kidney on iodine map and VNC images. A freehand ROI was placed on the cortex of the kidney and density measurements were recorded. Also, mottled areas were also evaluated by a using a circular region-of-interest of approximately 5 mm2.
Hacettepe University Ethics Board for Non-Interventional Studies reviewed and approved the study protocol (Decision no: 17.04.2020 - GO 20/388).
Categorical data are presented as numbers (percentages), and continuous variables are expressed as means ± standard deviations unless otherwise stated. Categorical data were compared using the Pearson Chi-square test/Fisher’s exact test, and continuous variables were compared using the Student’s t-test or Mann-Whitney U-test according to the distribution of data. The degree of association between continuous and/or ordinal variables was calculated using Pearson’s correlation coefficient or Spearman’s rho analysis according to the distribution of data. A one-way analysis of variance (ANOVA) or Kruskal–Wallis analysis was performed for comparing continuous variables in different PD grades. A two-tailed p-value of <0.05 was considered statistically significant. A receiver operating characteristic (ROC) curve analysis was performed to define the value of laboratory parameters in predicting PD.