Chest CT in patients with a moderate or high pretest probability of COVID-19 and negative swab

Abstract

Objectives: We aimed to assess the diagnostic performance of CT in patients with a negative first RT-PCR testing and to identify typical features of COVID-19 pneumonia that can guide diagnosis in this case.

Methods: Patients suspected of COVID-19 with a negative first RT-PCR testing were retrospectively revalued after undergoing CT. CT was reviewed by two radiologists and classified as suspected COVID-19 pneumonia, non-COVID-19 pneumonia or negative. The performance of both first RT-PCR result and CT was evaluated by using sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC) and by using the second RT-PCR test as the reference standard. CT findings for confirmed COVID-19 positive or negative were compared by using the Pearson chi-squared test (P values < 0.05) RESULTS: Totally, 337 patients suspected of COVID-19 underwent CT and nasopharyngeal swabs in March 2020. Eighty-seven out of 337 patients had a negative first RT-PCR result; of these, 68 repeated RT-PCR testing and were included in the study. The first RT-PCR test showed SE 0, SP = 100%, PPV = NaN, NPV = 70%, AUC = 50%, and CT showed SE = 70% SP = 79%, PPV = 86%, NPV = 76%, AUC = 75%. The most relevant CT variables were ground glass opacity more than 50% and peripheral and/or perihilar distribution.

Discussion: Negative RT-PCR test but positive CT features should be highly suggestive of COVID-19 in a cluster or community transmission scenarios, and the second RT-PCR test should be promptly requested to confirm the final diagnosis.

Keywords: COVID-19; Computed tomography; Nasopharyngeal swab; RT-PCR.

Fig.1

For each timing, the box plots show the median value (circle with a spot in the middle), the range from the 25% and the 75% quartiles (height of the box), the limits of the spread and the outliers

Fig. 2

P values of examined features. Grey bars show not statistically significant features (p value >  = 0.05), violet bars highlight statistically significant features (p value < 0.05)

Fig. 3

A 67-year-old man with a negative first RT-PCR result: ground glass opacities more than 50% of the lung pattern with peripheral and bilateral distribution in axial and coronal CT planes (A, B). Images were analyzed with the COPD advanced visualization application in ISP (Philips Medical Systems, Best, The Netherlands). The extent of the aerated lung was in all batches quantified by the percent of lung voxels with attenuation <  − 660 Hounsfield units (C)

Fig. 4

Sensitivity, specificity, diagnostic accuracy, positive predictive value (PPV), negative predictive value (NPV) and area under the ROC curve (AUC) for statistically significant features. Colored bars allow a visual comparison of the achieved performance (red for performance measures mainly focusing on positive patients, blue for performance measures mainly focusing on negative patients, yellow for performance measures balancing the performance on positive and negative patients)