The standard diagnostic method for COVID-19 is real-time polymerase chain reaction (RT-PCR) to detect the SARS-CoV-2 nucleic acid in respiratory secretion specimens obtained by oropharyngeal or nasopharyngeal swab, bronchoalveolar lavage, or tracheal aspirate [2] [3] . However, recently, it has been revealed that RT-PCR results often lack high sensitivity and sufficient stability, which might be attributed to low virus titers within samples or technical issues, and require a relatively long processing time [4] [5] [6] [7] . By contrast, chest computed tomography (CT) has high sensitivity and can obtain results rapidly [4] [5] [6] [7] .
A recent study by Ai et al [6] reported that 59% patients with COVID-19 had positive RT-PCR results and 88% had positive chest CT scans; additionally, chest CT had 97% sensitivity in predicting COVID-19. Similarly, Long et al [7] found that the chest CT sensitivity for COVID-19 infection was 97.2% compared with the RT-PCR sensitivity of 71%. Therefore, some investigators think that CT can be used as an important complement to RT-PCR, particularly for patients with COVID-19 with false negative RT-PCR results [4] [5] [6] [7] [8] . According to recent reports, most patients with COVID-19 share typical CT appearances, including bilateral ground-glass opacities (GGOs), multifocal patchy consolidation, and interstitial thickening with a subpleural distribution [9] [10] [11] [12] . However, these imaging features were thought to be nonspecific because they were also frequently observed in patients with other types of pneumonia [12, 13] .
In clinical practice, we have found that vascular enlargement (VE) pattern presents in most of our patients with COVID-19, which is characterized by dilatation of pulmonary vessels around and within the lesions on CT images. This particular CT feature is different from the previous imaging descriptions for pneumonia, which led us to wonder if the CT J o u r n a l P r e -p r o o f characteristics are specific to COVID-19. However, the related radiologic characteristics and diagnostic value of the VE pattern in COVID- 19 have not yet been investigated in detail.
Herein, we aimed to investigate the incidence, CT characteristics, and diagnostic value of the VE pattern in COVID-19.
This study was approved by the ethics committee of our institution, and informed consent was waived. From January 19 to February 29, 2020, 125 patients with a diagnosis of COVID-19 confirmed by nucleic acid testing in three institutions in China, who did not have severe cardiopulmonary diseases (e.g. pulmonary hypertension, heart failure) which might contribute to VE, underwent serial chest CT examinations. Among these patients, 19
with negative chest CT were excluded. In total, 106 patients were included. We also retrospectively collected the initial CT data of 52 patients with laboratory-confirmed influenza virus pneumonia (IVP) who had been admitted in our hospital between January 2018 and February 2020, including 47 patients with influenza A virus pneumonia and five patients with influenza B virus pneumonia.
All chest CT examinations were performed using the following three scanners: Discovery The imaging parameters were as follows: tube voltage, 100-130 kV; tube current, 100-400 mA; and scanning slice thickness, 5 mm. All images were reconstructed using 1-mm or 1.25-mm thin slices and stored on an ADW 4.6 workstation (GE Healthcare). Generally, follow-up CT scans were performed every 5-7 days for assessing disease progression after a short-term regular treatment. When the patient's symptoms worsened or the treatment protocols changed, the follow-up interval was shortened according to the patient's condition. Finally, the follow-up interval for our patients was 3-7 days. Among them, 61 patients had undergone four follow-up CT scans, 18 patients had undergone five follow-up CT scans, and 27 patients had undergone six follow-up CT scans.
Two experienced radiologists with >10 years of experience in chest imaging who were blinded to the related clinical data interpreted the axial images with 5-mm slice thickness on the workstations, assisted by thin-slice images and 10-mm maximum-intensity projection images. Any disagreement was resolved by discussion to reach a consensus. For each patient with COVID-19, the following data were carefully observed and recorded: (1) for patients with IVP, presence of the VE pattern and common CT features on initial CT were analyzed. The criteria for assessing the presence of the VE pattern was as follows: 1) increased vascular diameter by comparing with that of other vessels of the same grade in the identical or other lung lobes; 2) increased vascular diameter relative to that of the same vessel on previous or later CT images. Lesions meeting any one of the abovementioned criteria were considered to have the VE pattern. Furthermore, the VE pattern was only evaluated within areas of GGO or mixed GGO (hereinafter referred to as GGOs), and consolidated lesions were excluded from analysis because vessels within the lesions were obscured.
Disease severity was classified into four categories according to the Guidelines for the Diagnosis and Treatment of COVID-19 issued by the National Health Commission (fifth edition; China) [14] : 1) mild type: mild clinical symptoms without pneumonia on CT imaging; 2) common type: fever and other symptoms of respiratory infection with pneumonia on CT imaging; 3) severe type: had a. respiratory distress with respiratory rate ≥ 30/min, b. oxygen saturation ≤ 93% in the resting condition, and/or c. arterial partial pressure of oxygen/oxygen concentration ≤ 300 mmHg (1 mmHg = 0.133 kPa); 4) critical J o u r n a l P r e -p r o o f 8 type: had a. respiratory failure requiring mechanical ventilation, b. shock, and/or c. required intensive care unit monitoring and treatment because of other organ failure.
Statistical analyses were performed using IBM SPSS Statistics for Windows (version 19,0; IBM Corp., Armonk, NY). Single-sample Kolmogorov-Smirnov analysis was used to test the variance in homogeneity of the measurements. Normally distributed quantitative data were expressed as means ± standard deviations, whereas nonnormally distributed data were presented as medians ± interquartile ranges. The two independent-samples Student's t-test was performed to assess parameters consistent with normal distribution; otherwise, the Mann-Whitney U test was performed. The frequencies of the VE pattern between COVID-19 and IVP, between different-sized lesions in COVID-19, and between patients with COVID-19 under different clinical classifications were compared using the chisquared test. A two-tailed P < 0.05 indicated statistical significance.
Clinical characteristics including sex, age, comorbidities, days from illness onset to initial CT, and outcome of the 106 patients with COVID-19 and the 52 patients with IVP are summarized in Table 1 .
J o u r n a l P r e -p r o o f Among the 106 patients with COVID-19, 82 (77.36%) showed multilobar involvement, seven (6.60%) showed single-lobar involvement with ≥2 lesions, and 17(16.04%) showed single-lobar involvement with only one lesion. In total, 552 lesions were detected on initial CT. General CT findings of lesions including distribution, location, density, and lesion size and shape are shown in Table 2 . Peripheral GGOs, mainly in the lower or upper lobes and less frequently within the right middle lobe, with various sizes and morphologies were the typical features of COVID-19 on initial CT.
Out of 106 patients with COVID-19, 88 (83.02%) had the VE pattern on initial CT. Out of 52 patients with IVP, 10 (19.23%) had the VE pattern. The chi-squared test showed that there was a significant difference between the VE pattern frequencies with COVID-19 and with IVP, indicating that the VE pattern was more common in patients with COVID-19 (P < 0.001). Among the 52 patients with IVP, 42 (80.77%) showed multilobar involvement and 10 (19.23%) showed single-lobar involvement. GGOs (94.23%, 49/52) and consolidation (53.85%, 28/52) with a predominant peribronchovascular and subpleural distribution were the most frequent CT signs, followed by the interstitial thickening (38.46%, 20/52).
A total of 530 lesions presented as GGOs on initial CT. Among them, 370 (69.81%) lesions had the VE pattern. Three special CT signs related to the VE pattern based on the lesions' J o u r n a l P r e -p r o o f morphology were observed: 1) central vascular sign: characterized by ≥1 dilated vessels extending into or passing through the center of a round-like lesion, similar to a target, string bead, or hanging fruit according to the positional relationship between the lesions and vessels on axial CT images (96/370, 25.95%) (Fig. 1) ; 2) ginkgo leaf sign: characterized by ≥1 trunks of dilated vessels extending into a fan-shaped lesion from its tip facing the hilar, resembling a ginkgo leaf (41/370, 11.08%) (Fig. 2) ; 3) comb sign: characterized by multiple nearly parallel and dilated vessels vertically entering into a subpleural arch-shaped lesion, similar to a comb (51/370, 13.78%) (Fig. 3) .
As shown in Table 3 25.28%): the VE pattern was present on initial CT, and follow-up CT showed further enlargement of vessels with lesion progression, and then, the vessels gradually became thin or remained unchanged with lesion resolution in different degrees (Fig. 1) .
Additionally, the dynamic changes of the VE pattern and the evolution of lesions on serial CT were found to be associated with the time interval from the onset of symptoms to the initial CT scan. Regarding types I and III, the lesions with progression tended to have a significantly shorter time interval than those with absorption (all P < 0.05). Type II and IV tended to have a short time interval.
For the 106 patients with COVID-19, Table 4 summarizes the relationships between frequencies of the VE pattern versus lesion sizes and clinical classification associated with disease severity. Significant differences in the frequencies of the VE pattern were observed between <3-cm lesions and 3-5-cm lesions, 3-5-cm lesions and >5-cm lesions, <3-cm lesions and >5-cm lesions, respectively (all P < 0.001), indicating that the larger the lesion, the higher the occurrence of the VE pattern. Compared with those with the common type, patients with the severe-critical type had a significantly higher incidence of the VE pattern (P < 0.001).
Recently, some investigators have shown that angiotensin-converting enzyme-2 (ACE-2) may be a functional receptor for SARS-CoV-2 infections and plays a key role in the development and progression of COVID-19 [15] [16] . ACE-2 is abundantly present in lung alveolar epithelial cells and vascular endothelial cells and weakly expressed in epithelial cells of bronchial mucosa [17] . Therefore, the lung is the main target. The present study first analyzed general features of COVID-19 based on the initial CT images. The lesions were predominantly peripheral and multilobar. This distribution of COVID-19 may be attributed to the small size of SARS-CoV-2 [18] . After entering the respiratory tract, the virus can directly invade the terminal bronchioles and adjacent acini, resulting in a subpleural distribution. Meanwhile, it can easily disperse in the lung through the alveolar pore and cause multiple lesions. GGO was the most commonly encountered lesion density type. The lower lobe was preferentially affected, followed by the upper lobe; the right middle lobe was the least commonly involved. The lesions exhibited many morphologies and sizes.
These findings were consistent with some earlier reports [9] [10] [11] [12] [13] . However, several studies have found that aforementioned CT appearances of COVID-19 overlap with those of respiratory tract infections caused by other viruses [12, 13] , similar to our results.
In this study, we found that COVID-19 had a significantly higher frequency (83.02%, 88/106) of the VE pattern than IVP (19.23%, 10/52), suggesting that the VE pattern is a valuable CT feature for discriminating these two diseases. Zhou et al [10] analyzed the CT features of 62 patients with COVID-19 pneumonia and found that 45.2% (28/62) patients showed vascular dilation, which is somewhat lower than that indicated in our study. The reason for this may lie in the differences in the evaluation criteria of the VE pattern and the study sample size. A study by Bai et al [12] indicated that COVID-19 was more likely to have vascular thickening, which was then thought to be one of the most distinguishing J o u r n a l P r e -p r o o f 13 features for COVID-19, than non-COVID-19 pneumonia; this finding is consistent with our results. The VE pattern may be attributed to vascular dilation and damage characterized by endothelial injury and enhanced permeability resulting from a combination of coronavirusinduced direct cytopathic effects and virus-triggered host immune reactions accompanied by massive accumulation of pro-inflammatory factors in the lung [19] [20] [21] . For the higher occurrence of the VE pattern in COVID-19, we speculated that pulmonary vessels might be more vulnerable in COVID-19 than in IVP and that the expression pattern of ACE-2 in the lung might explain this [17] .
This study identified four types of dynamic changes in the VE pattern on serial CT that were closely associated with the evolution of lesions and time interval from the onset of symptoms to initial CT scan. The results of the present work showed no matter which the VE pattern was present on initial CT, if the vessels further dilated on follow-up CT, the lesions always progressed, which was usually observed soon after illness onset. Most lesions showed resolution in the absence of the VE pattern on all CT scans and were often detected long after the onset of symptoms. These results indicated that disease progression always accompanied aggravation of vascular injury. More serious vascular inflammatory responses showed more obvious increases in vascular diameter and permeability, and more exudation in the alveolar spaces. We found that some lesions with the VE pattern on initial CT but without further vascular dilation on follow-up CT were associated with different outcomes, which were further proved to be related to the time from the onset of symptoms to the initial CT. The improved lesions tended to have a longer interval and vice versa. This can be supported by the results of a previous study which found that 83% of patients with COVID-J o u r n a l P r e -p r o o f scan long after the onset of symptoms, these CT progression-related changes may be missed, and we can only observe these CT performances related to absorption. Hence, the dynamic changes in the VE pattern on follow-up CT combined with the time interval after the onset of symptoms may help predict the evolution of lesions in the short run. Additionally, the VE pattern was found to be more commonly seen in larger lesions and in patients with severecritical type COVID-19, indicating that vascular changes in COVID-19 were closely related to lesion size and pneumonia severity.
This study has several limitations. First, given the large number of small vessels within or around the lesions we studied, it was difficult to determine whether the VE pattern was present by measuring the diameter of each vessel and calculating the average value. Therefore, we lack an objective quantitative index to confirm the presence of the VE pattern.
Second, our study sample size was small. Third, considering that no patients underwent contrast-enhanced scanning in this study, we did not address the origin of enlarged vessels.
Future studies with larger sample sizes are needed for a more comprehensive analysis and to substantiate our findings.
In conclusion, the VE pattern is a useful CT sign for differentiating COVID-19 from IVP, which correlates with more extensive or serious disease. A good understanding of the CT characteristics of the VE pattern may contribute to the early and accurate diagnosis of COVID-19 and prediction of the evolution of lesions. 