Comparisons of chest computed tomography patterns between survivors and non-survivors with Coronavirus Disease 2019 (COVID-19): a case-control study


 Objectives To compare the chest computed tomography (CT) findings between survivors and non-survivors with Coronavirus Disease 2019 (COVID-19).Materials and Methods Between 12 January 2020 to 20 February 2020, the records of 124 consecutive patients diagnosed with COVID-19 were retrospectively reviewed and divided into survivor (83/124) and non-survivor (41/124) groups. Chest CT findings were qualitatively compared on admission and serial chest CT scans were semi-quantitively evaluated between two groups using curve estimations.Results Elder age (median: 69 vs. 43y, p<0.001), higher male ratio (31/41 vs. 32/83, p<0.001), and more comorbidities were observed in non-survivor group. On admission, significantly more bilateral (97.6% vs. 73.5%, p=0.005) and diffuse lesions (39.0% vs. 8.4%, p<0.001) with higher total CT score (median: 10 vs. 4) were observed in non-survivor group compared with survivor group. Besides, crazy-paving pattern was more predominant in non- survivor group than survivor group (39.0% vs. 12.0%, p=0.004). From the prediction of curve estimation, in survivor group total CT score increased in the first 20 days reaching the peak of 6 points and then gradual decreased for more than other 40 days (R2=0.545, p<0.001). In non- survivor group, total CT score rapidly increased over 10 points in the first 10 days and gradually increased afterwards until ARDS occurred with following death events (R2=0.711, p<0.001).Conclusions Persistent progression with predominant crazy-paving pattern was the major manifestation of COVID-19 in non-survivors. Understanding this CT feature could help the clinical physician to predict the prognosis of the patients.


Introduction
Since December 2019, an outbreak of coronavirus disease 2019  has emerged in Wuhan, China [1,2]. Subsequently the disease has spread worldwide with a total infected population of more than 1.2 million reported on 7th April 2020 [3]. The pathogen was confirmed as a novel betacoronavirus, which has demonstrated rapid human-to-human transmission with a median incubation period of three days [4,5]. Recent data also suggest a higher transmission capability of this virus than the previously reported coronaviruses [3,6].
The clinical characteristics and laboratory findings of COVID-19 patients have been reported including non-specific fever and cough symptoms and lymphopenia [2,5,[7][8][9]. Real-time reverse transcriptionpolymerase chain reaction (RT-PCR) test has a relatively high false-negative rate (29%) for COVID-2019 diagnosis, so chest computed tomography (CT) is recommended as the major screen modality with a higher sensitivity of 97% and faster performance [10][11][12]. In Hubei province, the center of the outbreak in China, the clinical diagnostic criteria were only dependent on chest CT scan, instead of the RT-PCR test before 19 February 2020 [13]. However, the value of the consecutive CT scans for monitoring disease progression was still unclear.
A previous study suggested a typical time course of CT findings in mild COVID-19 in which initial progression was followed by recovery, the latter starting after about two weeks [14]. Case series have associated severe and critical COVID-19 with more diffuse lung involvement, development of acute respiratory distress syndrome (ARDS), and multi-organ failure [8,[15][16][17]. Using a case-control design, this study aims to identify the differentiating CT features and compare the temporal evolution of pulmonary involvement between recovered and died patients with COVID-19.

Patients and Groups
The consecutive records of hospitalized patients with RT-PCR confirmed COVID-19 were reviewed retrospectively for the period from 12 January 2020 to 20 February 2020 in this single-center (Union Hospital, Wuhan, China), including 21 patients who were preliminarily reported in the previous study [14]. Only patients with definite clinical outcomes (discharge or death events) were involved. For sufficient estimation of the radiological course, patients with less than three times of chest CT scans were excluded unless ARDS occurred resulting in impossibility to carry out the consecutive chest CT scans. Eventually, 124 patients were included and divided to two groups: survivor group (discharged patients, n=83) and non-survivor group (died patients, n=41). Clinical data (e.g. initial symptoms, past medical history, etc.) and serial chest-CT data in the follow-up (extended until 30 March 2020 in survivor group) were retrieved through the institutional electronic patient database.
Diagnostic, isolation, grades of the disease severities (moderate, severe, and critical), treatment and discharge criteria were based on the published standard protocols from the continuously-updated National Health Commission of the People's Republic of China [13].

Chest CT Scan Protocols
Chest CT scans were performed using two commercial multi-detector CT scanners (Philips Ingenuity Core128, Philips Medical Systems, Best, Netherlands; SOMATOM Definition AS, Siemens Healthineers, Erlangen, Germany) during a single breath-hold. The low-dose mode was set up with a tube voltage of 120kVp and automatic tube current modulation. From the raw data, CT images were reconstructed as 1.5 mm thick axial slices and increment of 1.5mm in transverse slice orientation with either hybrid iterative reconstruction (iDose level 5, Philips Healthcare, Best, Netherlands) or a pulmonary B70F kernel (Siemens Healthineers, Erlangen, Germany).
The distribution of abnormalities was also noted as being predominantly subpleural (involving mainly the subpleural one-third of the lung), random (without predilection for subpleural or central regions) or diffuse (continuous involvement without respect to lung segments) [21]. A conventional semiquantitative scoring system was used to evaluate the pulmonary involvement area of all these abnormalities [14,22]. There was a score of 0-5 for each lobe on the following: 0 -no involvement; 1, <5% involvement; 2, 6%-25% involvement; 3, 26%-49% involvement; 4, 50%-75% involvement; 5, >75% involvement. The total CT score was the sum of the score of each lobe and ranged from 0 (no involvement) to 25 (maximum involvement). The analysis was performed using the institutional digital database system (Vue PACS, version 11.3.5.8902, Carestream Health, Oakville, Canada) by two radiologists (CZ and LY, who had 26 and 22 years of experience in thoracic radiology, respectively) and the decisions were reached in consensus. All radiologists were blinded to the groups and clinical progress of the patients to avoid information bias.

Statistical Analysis
Statistical analysis was performed using IBM SPSS Statistics Software (version 24; IBM, New York, USA). Quantitative data were presented as median with inter-quartile range (IQR) and qualitative data were presented as the percentage of the total unless otherwise specified. The comparisons of the quantitative data were statistically evaluated using the Mann-Whitney U test, according to the nonnormal distribution assessed by the Shapiro-Wilk test. The comparisons of qualitative data were evaluated using the Chi-square test or Fisher's exact test. The dynamic total CT score with time from symptom onset was quantitatively assessed by using the SPSS curve estimation module [14]. A pvalue of <0.05 was defined as having statistical significance.

Basic characteristics:
The median age of the patients was 56 y (IQR: 38-68 y) with an approximately equal male to female ratio (63:61). The median age of patients was significantly higher in non-survivor compared to nonsurvivors (69 y vs. 43 y, p<0.001). The percentage of male was 38.6% and 75.6% in survivor and nonsurvivor groups, respectively (p<0.001) ( Table 1). Non-survivors were also more likely to have a history of hypertension, diabetes, and coronary heart disease than survivors (p<0.05) ( Table 1).
Fever and cough were the most common initial symptoms (85.5% and 65.3%, respectively). Chest distress was significantly more inclined to occur in non-survivors (p<0.001) ( Table 1). There was no significant difference in period of admission from symptom onset between survivor and non-survivor groups (8 days vs. 9 days, p=0.422) ( Table 1). The median survival period of non-survivor group after admission was 14 days (IQR: 8-22 days) from admission, while the median hospitalized period in survivor group was 18 days (IQR: 12-27 days) (p=0.068). The survivors underwent more times of chest CT scans than non-survivors (4 vs. 2, p<0.001) with a significantly longer duration (6 days vs. 5 days, p=0.001) ( Table 1). All non-survivors aggravated to ARDS after a median of 11 days (8-14 days) from symptom onset, while only one patient aggravated to ARDS in survivor group.
Multiple biochemical and hematological parameters differed significantly between the two groups such as lymphocyte count, neutrophil count, and C-reactive protein (CRP) (p<0.05) ( Table 2).

Dynamic estimation of pulmonary involvement between two groups
Based on analysis, the cubic model demonstrated the best fitting in both the survivor and nonsurvivor groups (R2=0.545 and 0.711, respectively; p<0.001, each) (Figure 1a and 1b; Electronic The optimal fitting equations were demonstrated in Figure 1c. From the optimal fitting, in survivor group the total CT score gradually increased in the first 20 days with a peak value of 6 and then gradually decreased afterwards lasting for more than another 40 days (Figure 1c). The typical CT manifestation was changed from subpleural GGO to enlarged consolidation with time which was gradually absorbed afterwards leaving residual GGO and parenchymal bands (Figure 2). But in non-survivor group, the total CT score rapidly increased in the first 10 days and eventually approached 15 until ARDS occurred (Figure 1c). From the dynamic CT images, the persistently progressive pulmonary lesions from GGO with crazy-paving pattern to bilaterally extensive consolidation could be observed (Figure 3).

Discussion
This study compared the temporal changes in CT manifestations between survivors and nonsurvivors with COVID-19. It demonstrated the pulmonary involvement of subpleural GGO and sequential consolidation gradually progressed reaching the peak after 20 days since symptom onset.
Afterwards, the lesions started to be absorbed lasting for more than 40 days. In contrast, nonsurvivors demonstrated more rapid and persistent progression with more extensive bilateral lesions until ARDS occurred. Crazy-paving pattern was more predominant in non-survivors on admission compared with survivors.
In accordance with the previous studies, old patients (69 y, IQR: 63-78 y) with more comorbidities such as hypertension, diabetes, and coronary heart disease were more inclined to develop fatal ARDS [7,23]. Initial symptoms were similar between survivor and non-survivor groups, whilst chest distress was more common in non-survivor group. Patients in non-survivor group underwent a progressive phase lasting for about 11 days which culminated in the development of ARDS. As a case-controlled study, the mortality rate of ARDS caused by COVID-19 could not be evaluated, but from a previous study, it was reported a mortality of 61.5% [24].
Initial laboratory investigations on admission showed multiple hematological and biochemical abnormalities which were significantly different between survivor and non-survivor groups. This can be attributed to the systematic inflammation reaction and pulmonary vascular endothelial damage caused by a severe viral infection, similar to the systemic response seen in other types of severe pneumonia [7,21,22,[24][25][26]. It has been postulated that COVID-19 could also damage T lymphocytes, thus, significant lymphopenia was probably a risk factor leading to the deterioration of patients' immune function and more rapid disease progression [7,8,24,27]. In addition, the increased levels of CRP, lactate dehydrogenase, and D-dimer could also be indicators for development of ARDS, as reported in other types of pneumonia [20,22,25,28].
In the early stage of COVID-19, subpleural GGO was the predominant finding [14,17]. But in this study, patients were hospitalized after a median period of 8 and 9 days after the onset of symptoms in survivor and non-survivor groups, respectively, at which time the predominant findings in both groups corresponded with the progressive stage [14]. Thus, GGO was not the predominant finding in both groups but the consolidation and crazy-paving pattern. Compared with the survivors, it demonstrated the predominant CT demonstration of crazy-paving pattern in non-survivor group on admission was a major difference except for more diffuse and bilateral distributions. Pathologically, GGO may be an indicator of alveolar edema and proteinaceous exudates [29]. As the disease progresses, increasing alveolar edema, exudates and lymphocyte infiltrates fill the interstitial space leading to the radiological demonstration of diffuse "crazy-paving pattern" [19,26,30,31].
Subsequent ARDS and potentially fatal respiratory failure developed as a result of diffuse alveolar edema with loss of alveolar epithelium [19,31]. Thus, it was speculated large area of crazy-paving pattern was probably a CT indicator of poor prognosis.
Considering the heterogeneities of the scan time among the patients, longitudinal comparisons were not appropriate. Thus, the curve estimation was used to statistically compare the temporal evolution of the disease between two groups. Being different from the static comparison of chest CT on admission using the logistic module, curve estimation could analyze the dynamic patterns of the pulmonary involvement with time [16,32]. Thus, it could provide a more composite comprehension of the time course in COVID-19 between survivors and non-survivors. As a result, it demonstrated a gradual resolution of abnormalities after a maximal total CT score of 6 at 20 days, longer than 10 days reported in the previous report [14]. It might be ascribed to a limited sample size in the previous study and more severe patients (15.7% of severe and critical patients) in survivor group. Thus, the previous study probably underestimated the recovery duration of COVID-19. Compared with survivor groups, the total CT score in non-survivor group demonstrated a more rapid increase in the first 10 days with a higher value of more than 10 points. Although the previous study showed the feasibility of making CT score as an indicator of prognosis, but it didn't demonstrate the dynamic changes of CT score in the whole course [16]. In this study, it revealed the total score persistently elevated to a higher level close to 15 points without any decrease in non-survivor group, until the ARDS occurred with the following death events. From one pathological study in severe acute respiratory syndrome (SARS), it found the long duration of illness was resulted from the severe fibrosis and organization [26]. Considering the partial homology of SARS and COVID-19, it might explain why the lesions were rarely absorbed in non-survivors with COVID-19. This is another major difference between the two groups in the course, associated with the refractory feature of the critical COVID-19 under the present treatment protocols [13].
This study has limitations. Firstly, as a retrospective study, chest CT was used by the physician based on the clinical necessity and the status of the patient, so the heterogeneities of scanning time made it impossible to perform a conventional longitudinal comparison between two groups. Second, CT was not clinically feasible for patients after developing ARDS so not enough CT information was provided in the course of ARDS. Consequently, the majority of CT scans were performed in mild disease (363/436, 83.3%). To avoid data heterogeneity, the comparison of chest CT between two groups was only performed on admission due to the similar period from symptom onset and the curve estimation was used to evaluate the comprehensive trend of pulmonary involvement between two groups. Third, the multi-variate regression involving the CT, clinical, and laboratory parameters was not performed owing to the limited sample size with relatively a large number of parameters with significant differences between the two groups.
In summary, from comparisons between survivors and non-survivors, this study indicated that the presence of crazy-paving pattern on chest CT with the high and rapidly increased CT scores may help to identify the patients at high risk of developing ARDS before clinical deterioration. A larger, prospective study is required to confirm these findings with the more accurate quantitative assessment modality of the CT images in COVID-19.

Acknowledgments
We express our sincere gratitude to the emergency services, nurses, doctors and a lot of medical supports from other provinces for their efforts to combat the COVID-19 outbreak in Wuhan. Besides, we are grateful to Dr. Jiazheng Wang and Dr. Dandan Zheng for many useful discussions through the formation and design of this work.

Fundings
No fund was supported to this study.

Conflict of Interest
All co-authors declared no confict of interest, financial or otherwise.

This retrospective study was approved by the Ethics of Committees of Union Hospital, Tongji Medical
College, Huazhong University of Science and Technology (No. 2020-0026), and followed the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Patient and other consents
Informed consent/deceased patient permission form for this retrospective study was waived by Ethics of Committees of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Only the anonymous data was collected and analyzed to facilitate better clinical decisions and treatment.