Diagnostic accuracy of serial Chest X-ray as good as chest CT in COVID-19, finds study

Imaging-based diagnostic tools are attractive as a companion option for diagnosis of COVID-19, with some reports suggesting high sensitivity of COVID-19 detection by computed tomography (CT) studies.

However, questions have been raised about the reported high sensitivity of CT in those studies, which likely suffer from selection bias toward more severe cases. Some early reports have also described high specificity in the diagnosis of COVID-19 compared to other entities, but these too may be biased by the selection of more severe cases and, at least in one case, an artificial control group of other viral cases of pneumonia.

Head on studies evaluating the imaging characteristics, sensitivity, and specificity of both chest X-ray (CXR) and chest CT in detecting COVID-19 infection in patients with lab-confirmed SARS-CoV-2 viral infection over time is essential, but very few have been done.

A group of researchers under Stephanie Stephanie at al, from the Department of Internal Medicine, University of Maryland School of Medicine, sought to carry out a study to evaluate the sensitivity, specificity, and severity of chest x-rays (CXR) and chest CTs over time in confirmed COVID-19+ and COVID-19- patients and to evaluate determinants of false negatives.

The research team designed a retrospective multi-institutional study, with 254 RT-PCR verified COVID-19+ patients with at least one CXR or chest CT was compared with 254 age- and gender-matched COVID-19- controls. CXR severity, sensitivity, and specificity were determined concerning the time after the onset of symptoms; sensitivity, and specificity for chest CTs without time stratification.

The performance of serial CXRs against CTs was determined by comparing the area under the receiver operating characteristic curves (AUC). A multivariable logistic regression analysis was performed to assess factors related to false-negative CXR.

Reviewers evaluated for the predominant pattern in chest radiographs, selecting from interstitial opacities, interstitial and airspace opacities, atelectasis, diffuse airspace opacities, lobar consolidation, or peripheral opacities; if none of these patterns applied the reviewers would select 'normal'. Reviewers also assessed for a craniocaudal gradient and the presence of pleural effusions. Reviewers were asked to assign a severity score for the chest x-ray findings: normal, mild, moderate, or severe. Reviewers also assessed the likelihood of COVID-19 based on the radiograph findings, with a score between 1 and 5.

On data analysis, the following results emerged.

• COVID-19+ CXR severity and sensitivity increased with time (from sensitivity of 55% at ≤2 days to 79% at >11 days; p<0.001 for trends of both severity and sensitivity) whereas CXR specificity decreased over time (from 83% to 70%, p=0.02).
• Serial CXR demonstrated an increase in AUC (first CXR AUC=0.79, second CXR=0.87, p=0.02), and the second CXR approached the accuracy of CT (AUC=0.92, p=0.11).
• COVID-19 sensitivity of first CXR, second CXR, and CT was 73%, 83%, and 88%, whereas specificity was 80%, 73%, and 77%, respectively.
• Normal and mild severity CXR findings were the largest factor behind false-negative CXRs (40% normal and 87% combined normal/mild).
• Young age and African-American ethnicity increased false-negative rates.

The researchers further observed that several specific imaging findings in CXR and CT that were helpful in the diagnosis of COVID-19, including interstitial and airspace opacity pattern (OR 2.84) and peripheral airspace opacities (OR 7.94) on CXR, and reverse halo sign on chest-CT (OR 9.36).

"Our finding that serial CXR imaging approaches the accuracy of CT imaging in COVID-19 has potential value in enhancing bio-containment and workflow in hospitals. CXRs use less radiation and portable CXR machines can be brought to patient bedsides to perform CXRs and require far less time to decontaminate, making it an attractive option to employ." concluded the team.

For full article follow the link: https://doi.org/10.1148/ryct.2020200337

Primary source: Radiology: Cardiothoracic Imaging.