Differentiating pneumonia with and without COVID-19 using chest CT images: from qualitative to quantitative

Abstract

Background: Pneumonia caused by COVID-19 shares overlapping imaging manifestations with other types of pneumonia. How to objectively and quantitatively differentiate pneumonia patients with and without COVID-19 virus remains clinical challenge.

Objective: To formulate standardized scoring criteria and an objective quantization standard to guide decision making in detection and diagnosis of COVID-19 virus induced pneumonia in clinical practice.

Methods: A retrospective dataset includes computed tomography (CT) images acquired from 43 pneumonia patients with COVID-19 virus detected by reverse transcription-polymerase chain reaction (RT-PCR) tests and 49 pneumonia patients without COVID-19 virus. All patients were treated during the same time period in two hospitals. Key indicators of differential diagnosis were identified in relevant literature and the scores were quantified namely, patients with more than 8 points were identified as high risk, those with 6-8 points as moderate risk, and those with fewer than 6 points as low risk for COVID-19 virus. In the study, 3 radiologists determined the scores for all patients. Diagnostic sensitivity and specificity were subsequently calculated.

Results: A total of 61 patients were determined as high risk, among which 42 were COVID-19 positive by RT-PCR tests. Next, 9 were identified as moderate risk, one of whom was COVID-19 positive. Last, 22 were classified into the low-risk group, all of them are COVID-19 negative. Based on these results, the sensitivity of detection COVID-19 positive cases between the high-risk group and the non-high-risk group was 0.98 with 95% confidence interval [0.88, 1.00], and the specificity was 0.61 [0.46, 0.75]. The detection sensitivity between the moderate-/high-risk group and the low-risk group was 1.00 [0.92, 1.00], and the specificity was 0.45 [0.31, 0.60].

Conclusion: The proposed quantitative scoring criteria showed high sensitivity and moderate specificity in detecting COVID-19 using CT images, which indicates that these criteria may be beneficial for screening in real-world practice and helpful for long-term disease control.

Keywords: COVID-19; Coronavirus; Pneumonia; X-ray computed tomography.

Fig. 1

The patient showed scattered distribution, small patchy ground glass opacities, bronchiectasis and vessel dilations. The patient was scored 8 points and had confirmed COVID-19 based on positive PCR results. PCR – polymerase chain reaction.

Fig. 2

The patient showed subpleural distribution, multiple large patchy ground glass opacities, lesions with the long axis parallel to the pleura, fine-mesh changes, bronchiectasis with rigid course and vessel dilations, and was scored 12 points. The patient was diagnosed with COVID-19, which was confirmed by positive PCR results. PCR – polymerase chain reaction.

Fig. 3

The patient showed subpleural distribution, large patchy ground glass opacities, lesions with the long axis parallel to the pleura, fine-mesh changes, bronchiectasis with rigid course and thickening of passing-through vessels. The patient was scored 12 points, but with negative PCR results. PCR – polymerase chain reaction.

Fig. 4

The patient showed scattered distribution, small patchy ground glass opacities, consolidation shadows, miliary shadows, fine-mesh changes, bronchiectasis with rigid course and lymphadenopathy. The patient was scored 5 points, with negative PCR results. PCR – polymerase chain reaction.

Fig. 5

The patient showed scattered distribution, patchy ground glass opacities, cord shadows, consolidation shadows, lesions that were parallel to the long axis, and bronchiectasis with rigid course. They were scored 7 points, with negative PCR results. PCR – polymerase chain reaction.

Fig. 6

Receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated. The corresponding AUC values for two radiologists (A and B) are 0.96 [95% confidence interval (CI): 0.92, 0.99] and 0.94 [95% CI: 0.90, 0.98], respectively.