How did radiologists' diagnostic performance has changed in COVID-19 pneumonia: A single-centre retrospective study

Changes in Radiologists' Gaze Patterns Against Lung X-rays with Different Abnormalities: a Randomized Experiment

The workload of some radiologists increased dramatically in the last several, which resulted in a potentially reduced quality of diagnosis. It was demonstrated that diagnostic accuracy of radiologists significantly reduces at the end of work shifts. The study aims to investigate how radiologists cover chest X-rays with their gaze in the presence of different chest abnormalities and high workload. We designed a randomized experiment to quantitatively assess how radiologists' image reading patterns change with the radiological workload. Four radiologists read chest X-rays on a radiological workstation equipped with an eye-tracker. The lung fields on the X-rays were automatically segmented with U-Net neural network allowing to measure the lung coverage with radiologists' gaze. The images were randomly split so that each image was shown at a different time to a different radiologist. Regression models were fit to the gaze data to calculate the treads in lung coverage for individual radiologists and chest abnormalities. For the study, a database of 400 chest X-rays with reference diagnoses was assembled. The average lung coverage with gaze ranged from 55 to 65% per radiologist. For every 100 X-rays read, the lung coverage reduced from 1.3 to 7.6% for the different radiologists. The coverage reduction trends were consistent for all abnormalities ranging from 3.4% per 100 X-rays for cardiomegaly to 4.1% per 100 X-rays for atelectasis. The more image radiologists read, the smaller part of the lung fields they cover with the gaze. This pattern is very stable for all abnormality types and is not affected by the exact order the abnormalities are viewed by radiologists. The proposed randomized experiment captured and quantified consistent changes in X-ray reading for different lung abnormalities that occur due to high workload.

How did radiologists' diagnostic performance has changed in COVID-19 pneumonia: A single-centre retrospective study

AIMS

Delay and false positivity in PCR test results have necessitated accurate chest CT reporting for the management of patients with COVID-19-suspected symptoms. Pandemic related workload and level of experience on covid-dedicated chest CT scans might have affected the diagnostic performance of on-call radiologists. The aim of this study was to reveal the interpretation errors (IEs) in chest CT reports of COVID-19-suspected patients admitted to the Emergency Room (ER).

METHODS

Chest CT scans between March and June 2020 were re-evaluated and compared with the former reports and PCR test results. CT scan results were classified into four groups. Parenchymal involvement ratios, radiology departments' workload, COVID-19-related educational activities have been examined.

RESULTS

Out of 5721 Chest CT scans, 783 CTs belonging to 664 patients (340 female, 324 male) were included in this study. PCR test was positive in 398; negative in 385 cases. PCR positivity was found to be highest in "normal" and "typical for covid" groups whereas lowest in "atypical for covid" and "not covid" groups. 5%-25% parenchymal involvement ratio was found in 84.2% of the cases. Regarding the number of chest CT scans performed, radiologists' workload has found to be increased six-folds. With the re-evaluation, a total of 145 IEs (18.5%) have been found. IEs were mostly precipitated in the first two months (88.3%) and mostly in the "not covid" class (60%) regardless of PCR positivity. COVID-19 and radiology entitled educational activities along with the ER admission rates within the first two months of the pandemic have seemed to be related to the decline of IEs within time.

CONCLUSION

COVID-19 pandemic made a great impact on radiology departments with an inevitable burden of daily chest CT reporting. This workload and concomitant factors have effects on diagnostic challenges in COVID-19 pneumonia.