Study Population:
Our study utilized data from 266 COVID-19 patients with a past medical history of cancer who were registered in the Clinical COVID-19 Registry of Imam Khomeini Hospital between 2020 and 2022. COVID-19 infection was confirmed by clinical evaluation, considering both CT scan, and/ or RT-PCR test results. Cancer patients who had undergone chest CT scan examination in less than 5 days from the beginning of their symptoms were included. Demographic and clinical information related to COVID-19 and cancer disease including oxygen saturation, length of hospital stay, ICU hospitalization, intubation and mortality rates, type of cancer, stage of cancer, oncologic treatment, the interval between cancer diagnosis and the last time receiving anti-tumor treatment was collected in the COVID-19 registry. The type of cancer was categorized as hematological, lung, breast, GI, and other tumors gathered together due to the small sample size.
CT scan Protocol:
Non-enhanced chest CT scan images were obtained in the supine position, using CT scan systems (SOMATOM Emotion 16 scanner; Siemens). To minimize motion artifacts, CT scan images were acquired during a single inspiratory breath-hold. We used tube voltage = 80-110 kVp, effective current 60-80 mA, pitch = 1-1.5, matrix = 512 × 512, slice thickness = 5 mm (reconstructed slice thickness= 1.5 mm), and pulmonary U90S kernel to minimize patient radiation exposure. The reconstructed images were sent to the picture archiving and communication system (PACS). The low-dose CT scan protocol was recommended by the Iranian Society of Radiology COVID-19 Consultant Group (ISRCC) and did not make any problem with image interpretations (13).
Chest CT Image Interpretation:
All chest CT scans were reviewed by two radiologists concurrently with both lung (width, 1500 HU; level, −700 HU) and mediastinal (width, 350 HU; level, 40 HU) windows. After the final agreement, the prepared checklist was filled. During the review, both radiologists were blinded to the patient’s information and outcome. The CT scan evaluation was performed in four major fields: morphology, CT scan involvement score, associated pulmonary lesions, and mediastinal findings. Morphology features included pure ground-glass opacity (GGO), consolidation, predominant GGO, predominant consolidation, and other associated pulmonary abnormalities including crazy-paving pattern (a combination of GGO with superimposed interlobular and intralobular septal thickening), pleural effusion, pericardial effusion, lymphadenopathy, centrilobular nodules, architectural distortion, metastatic nodules, and mass.
All lung lobes were visually evaluated for CT scan involvement scores. Each lobe received 0 (non-involvement), 1 (less than 5% involvement), 2 (5-25% involvement), 3 (26-49% involvement), 4 (50-75% involvement), and 5 (>75% involvements) score. A total CT score was recorded from 0 to 25(14). Furthermore, according to The Radiological Society of North America (RSNA) chest CT classification system for the diagnosis of COVID-19 pneumonia, CT scan of patients was classified into ‘’Typical’’, ‘’Indeterminate’’, ‘’Atypical’’ and ‘’Negative’’ categories (8).
Statistical Analysis:
We used descriptive statistics to study the distribution of the patient’s characteristics. A univariate and multivariate logistic regression model was performed to calculate crude and adjusted odds ratio (OR) and 95% confidence interval (CI) and measure the association between prognostic CT scan factors and COVID-19 mortality. Analysis repeated for different categories of cancers and ORs were adjusted for age, gender, and comorbidities. We used Stata14 for statistical analysis (Stata Statistical Software: Release 14. College Station, TX: Stata Corp LLC).