Skip to main content
NCBI home page
PLOS One logoLink to PLOS One
. 2021 Mar 23;16(3):e0248957. doi: 10.1371/journal.pone.0248957

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT

Jia-Ni Zou 1,#, Liu Sun 2,#, Bin-Ru Wang 3,#, You Zou 4,#, Shan Xu 4, Yong-Jun Ding 4, Li-Jun Shen 4, Wen-Cai Huang 1, Xiao-Jing Jiang 5, Shi-Ming Chen 4,6,*
Editor: Giordano Madeddu7
PMCID: PMC7987145  PMID: 33755708

Abstract

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (COVID-19) have not been adequately studied. AI-assisted chest high-resolution computed tomography (HRCT) was used to investigate the proportion of COVID-19 patients with pulmonary fibrosis, the relationship between the degree of fibrosis and the clinical classification of COVID-19, the characteristics of and risk factors for pulmonary fibrosis, and the evolution of pulmonary fibrosis after discharge. The incidence of pulmonary fibrosis in patients with severe or critical COVID-19 was significantly higher than that in patients with moderate COVID-19. There were significant differences in the degree of pulmonary inflammation and the extent of the affected area among patients with mild, moderate and severe pulmonary fibrosis. The IL-6 level in the acute stage and albumin level were independent risk factors for pulmonary fibrosis. Ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing, bronchiectasis and the extent of the affected area were significantly improved 30, 60 and 90 days after discharge compared with at discharge. The more severe the clinical classification of COVID-19, the more severe the residual pulmonary fibrosis was; however, in most patients, pulmonary fibrosis was improved or even resolved within 90 days after discharge.

Introduction

Pulmonary fibrosis can occur as a serious complication of viral pneumonia, which often leads to dyspnea and impaired lung function. It significantly affects quality of life and is associated with increased mortality in severe cases [1, 2]. Patients with confirmed severe acute respiratory syndrome coronavirus (SARS‐CoV) or Middle East respiratory syndrome coronavirus (MERS‐CoV) infections were found to have different degrees of pulmonary fibrosis after hospital discharge, and some still had residual pulmonary fibrosis and impaired lung function two years later. In addition, wheezing and dyspnea have also been reported in critically ill patients [3–5].

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel Betacoronavirus that is responsible for an outbreak of acute respiratory illness known as coronavirus disease 2019 (COVID-19). SARS-CoV-2 shares 85% of its genome with the bat coronavirus bat-SL-CoVZC45 [6]. However, there are still some considerable differences between SARS-CoV-2 and SARS‐CoV or MERS‐CoV. Whether COVID-19 can trigger irreversible pulmonary fibrosis deserves more investigation. George reported that COVID-19 was associated with extensive respiratory deterioration, especially acute respiratory distress syndrome (ARDS), which suggested that there could be substantial fibrotic consequences of infection with SARS-CoV-2 [7]. Moreover, it has also been shown that the pathological manifestations of COVID-19 strongly resemble those of SARS and MERS [8], with pulmonary carnification and pulmonary fibrosis in the late stages.

Chest X-rays and high-resolution computed tomography (HRCT) of the chest play important auxiliary roles in the diagnosis and management of patients with suspected cases of COVID-19 [9, 10]. The newly applied artificial intelligence (AI)-assisted pneumonia diagnosis system has been described as an objective tool that can be used to qualitatively and quantitatively assess the progression of pulmonary inflammation [11]. At present, although COVID-19 has been classified as a global epidemic for months, the risk factors for and severity and evolution of pulmonary fibrosis have not yet been reported. In this study, this new technology was applied to investigate the pulmonary imaging characteristics and related risk factors in COVID-19 patients at the time of hospital discharge, as well as the evolution of pulmonary fibrosis 30, 60 and 90 days after discharge, with the aim of providing an important basis for the clinical diagnosis, treatment and prognostic prediction of COVID-19-related pulmonary fibrosis.

Materials and methods

Study subjects

All 284 patients who had confirmed cases of COVID-19 and achieved a clinical cure from February 1 to March 31, 2020, at the Central Theater General Hospital of the Chinese People’s Liberation Army were recruited. Their clinical characteristics and chest HRCT data were collected; follow-up studies on the evolution of pulmonary fibrosis were conducted with patients who returned to the hospital for chest HRCT reexaminations 30 days, 60 days and 90 days after hospital discharge.

The clinical diagnosis, treatment, clinical classification and discharge criteria for all patients were based on the Diagnosis and Treatment of COVID-19 (trial version 7) published by the National Health Commission of China [12]. The inclusion criteria were as follows: primary infection with SARS-CoV-2 confirmed by a positive upper respiratory swab RT-PCR. The exclusion criteria were other viral respiratory infections, coexisting connective tissue disease, and a history of lung disease. The experimental procedures used in this study were approved by the ethics committee of Renmin Hospital of Wuhan University and Central Theater General Hospital of the Chinese People’s Liberation Army (WDRY2020-K110), [2020]030–1). The collection and use of relevant case data were performed with adequate protection of the patients’ privacy and met the ethics requirements. The need to obtain the informed consent of the patients was waived. All data were anonymized. The patients’ medical records were accessed from February 1 to June 8, 2020.

Chest HRCT examinations

In accordance with the COVID-19 Close Contacts Management Guidelines published by the National Health Commission of China [13], all patients underwent a chest HRCT examination in a designated room in which the environment and equipment were completely sterilized, and the scanning technicians were all wearing the appropriate level of personal protective equipment. The patients had to wear masks and were examined in the supine position after receiving instructions about breathing during the scan. A Sino-vision 64s CT spiral scanner (SINO VISION, Beijing) was used, and the scan covered the area from the apex of the lung to the costophrenic angle. The scanning parameters were as follows: tube voltage of 120 kV, adjusted tube current that ensured that the CTDIvol value was 7 mGy, scanning layer thickness and layer spacing of 0.5–2 mm, spiral pitch of 1.3, and pedal scan direction.

Chest HRCT image analysis

Image analysis was performed independently by 2 senior diagnostic radiologists in a double-blinded fashion. When their opinions differed, the chief diagnostic chest imaging physician was asked to lead a discussion, during which a final agreement was reached. The chest CT image analysis included the distribution of the lesions, the location of the lesions, the number of lobes affected, the characteristics of the lesions and external involvement. For each patient, the CT presentation was described according to the following parameters.

Lesion degree

The types of lesions were as follows: ground-glass opacity, linear opacity, interlobular septal thickening, reticulation, honeycombing or bronchiectasis. To describe the extent of the lesions, the lungs were divided into approximately 20 equal parts according to the distribution of lung segments (2 parts in the posterior apical segment of the left upper lobe, 2 parts in the anterior and basal segments of the lower lobe, and 1 part each for the upper and lower lingual segments of the left lung) [14].

Quantitative scoring of pulmonary fibrosis

The degree of pulmonary fibrosis was evaluated using the CT scoring method proposed by Camiciottoli [15]: chest HRCT images (ground-glass opacity, linear opacity, interlobular septal thickening, reticulation, honeycombing or bronchiectasis) were independently scored by two people; the intraclass correlation coefficient (ICC) was approximately 0.99, which indicated that this method was reliable. The mean was taken as the final score when the scores were inconsistent.

The scoring method had two parts, one for the lesion type and the other for the extend of the lesions. The maximum score was 30. The types of lesions were ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing and bronchiectasis, which were scored as 1, 2, 3, 4 and 5, respectively. The extent of each type of lesion was scored based on whether that lesion type was identified in 1 ~ 3, 4 ~ 9 or more than 9 pulmonary segments, which were scored as 1, 2 and 3, respectively. For example, if there were ground-glass opacities in 1 to 3 lung segments, the pulmonary fibrosis score was 1+1 = 2. The total quantitative pulmonary fibrosis score was equal to the score for all types of lesions + the extent score for each type of lesion; the total score ranged from 0 to 30. Pulmonary fibrosis was classified into three groups based on the total score as follows: mild (0–10), moderate (11–20), and severe (21–30).

AI inflammation score

The relative quantification was performed with the “Artificial Intelligence (AI)-assisted Pneumonia Diagnosis System” software developed by Hangzhou Etu Medical Technology Co. (https://www.yitutech.com). This system combines convolutional neural networks with the threshold method to dissect the left and right lungs and detect the areas of inflammation. It then calculates the pulmonary inflammatory volume (PIV), whole lung volume (WLV), percentage of diseased lung (PIV/WLV), and quantitative parameters such as the involved lung lobes and involved lung segments.

Risk factors for pulmonary fibrosis

Patient clinical data were collected from the electronic medical records system. The general clinical data included sex, age, and main clinical symptoms. The laboratory findings are listed in Table 4. All laboratory results were measured within 48 hours of admission.

Table 4. Analysis of risk factors in patients with pulmonary fibrosis.

Index HR 95%CI P
value
Age(years) 1.001 0.975–1.027 0.941
High fever (≥38.5°C) 0.502 0.174–1.450 0.203
Cough 0.708 0.309–1.621 0.708
Chest tightness 0.772 0.263–2.270 0.757
IL-6(acute stage)* 1.081 1.021–1.144 0.007
IL-6 (hospital discharge) 1.119 0.969–1.292 0.125
Lymphocyte ×10⁹ per L 0.921 0.711–1.194 0.536
Lymphocyte % 0.988 0.955–1.022 0.479
AST (U/L) 1.02 0.990–1.051 0.192
Albumin (g/L) * 0.821 0.734–0.918 0.001
PT (s) 0.93 0.822–1.052 0.250
Open in a new tab

Statistical analysis

Categorical variables are described by frequencies and percentages, and normally distributed data are presented as the means ± standard deviations (X±SD). Skewed data are presented as the medians and interquartile ranges. Comparisons between groups of measures that conformed to a normal distribution were performed using t tests, and comparisons between groups with skewed data distributions were performed with Wilcoxon’s test or the Mann-Whitney U test. Categorical data were analyzed using the χ2 test and Fisher’s exact test, and correlations were analyzed using Spearman’s rank correlation analyses. Statistical analyses were performed with SPSS (version 26.0) software. Statistical significance was defined by a two-sided P < 0.05.

Results

The proportion of COVID-19 patients with pulmonary fibrosis

A total of 284 COVID-19 patients who achieved a clinical cure were enrolled in this study, of whom 239 (84.15%) had pulmonary fibrosis and 45 (15.85%) did not have fibrosis. Pulmonary fibrosis occurred in 169 patients with moderate COVID-19 (78.9%) and in all patients with severe or critical COVID-19 (100%). The incidence of pulmonary fibrosis in patients with moderate COVID-19 was significantly lower than that in patients with severe or critical COVID-19 (Table 1, P<0.01).

Table 1. The proportion of COVID-19 patients with pulmonary fibrosis at discharge and its relationship to the clinical classification.

Pulmonary fibrosis Groups Total χ2 value P value
Moderate COVID-19 Severe COVID-19 Critical COVID-19
Yes Milda 101 10 3 114
Moderateb 68 25 3 96
Severec 0 22 7 29
Total 169 57 13 239 101.556 0.000
No Total 45 0 0 45
Open in a new tab

Fisher’s exact test: χ2 = 23.575, P = 0.000<0.01.

Kruskal-Wallis test: χ2 = 12.971, P = 0.002<0.01

a: the risk value is 28.27

b: the risk value is 39.38

c: the risk value is 48.50.

The relationship between the degree of pulmonary fibrosis and the clinical classification of COVID-19

Among the 239 COVID-19 patients with pulmonary fibrosis, 169 patients with moderate COVID-19 had mild pulmonary fibrosis (101 patients, 59.76%) or moderate pulmonary fibrosis (68 patients, 40.24%). Fifty-seven patients with severe COVID-19 had mild pulmonary fibrosis (10 patients, 17.54%), moderate pulmonary fibrosis (25 patients, 43.86%) or severe pulmonary fibrosis (22 patients, 38.60%). Thirteen patients with critical COVID-19 had mild pulmonary fibrosis (3 patients, 23.08%), moderate pulmonary fibrosis (3 patients, 23.08%) or severe pulmonary fibrosis (7 patients, 53.85%) (Table 1). These results indicated that patients with moderate COVID-19 mainly developed mild-to-moderate pulmonary fibrosis, while patients with critical COVID-19 generally developed severe pulmonary fibrosis (P<0.01).

Pulmonary fibrosis quantitative scores

Among the 239 COVID-19 patients with pulmonary fibrosis, those with mild cases mainly had ground-glass opacities and linear opacities; those with moderate cases mainly had ground-glass opacities, linear opacities and interlobular septal thickening; and those with severe cases mainly had ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing or bronchiectasis. There were significant differences in the lung segments affected by linear opacities or interlobular septal thickening among patients with mild, moderate, and severe cases (Table 2, P<0.01).

Table 2. The type of lesions and the affected lung segments in 239 COVID-19 patients with pulmonary fibrosis at discharge.

Affected lung segments Milda (n = 114) Moderateb (n-96) Severec (n = 29) Z value, P value
a vs. b a vs. c b vs. c
Ground-glass opacity [n (%)] 92(80.70%) 72(75.00%) 28(96.55%)
    Affected lung segments 4.80±2.80 6.29±3.64 9.50±3.97 -2.681, 0.007 -5.572, 0.000 -3.685, 0.000
Linear opacities [n (%)] 94(82.46%) 91(94.79%) 29(100.00%)
Affected lung segments 3.33±1.89 4.75±2.48 6.00±2.94 -4.072, 0.000 -4.804, 0.000 -2.206, 0.027
Interlobular septal thickening [n (%)] 10(8.77%) 72(75.00%) 29(100.00%)
    Affected lung segments 2.70±1.64 3.88±1.58 6.03±3.36 -2.571, 0.10 -3.399, 0.001 -2.968, 0.003
Reticulation [n (%)] 4(3.51%) 39(40.63%) 28(96.55%)
    Affected lung segments 1.25±0.50 3.64±2.28 5.39±2.42 -2.707, 0.007 -3.1296, 0.001 -3.190, 0.001
Honeycombing or bronchiectasis [n (%)] 2(1.75%) 55(57.29%) 29(100.00%)
    Affected lung segments 1.00 2.82±1.56 4.41±2.73 — -2.657, 0.008 —
Pulmonary fibrosis score 5.53±2.21 14.81±2.49 24.17±1.54 -12.513, 0.000 -8.362, 0.000 -8.176, 0.000
Open in a new tab

The AI inflammation score

The AI inflammation score was determined based on the quantitative evaluation of lung inflammation by AI-assisted chest HRCT and was further used to analyze its relationship with the degree of pulmonary fibrosis. The analysis revealed significant differences in the degree of pulmonary inflammation (PIV, PIV/WLV) and the extent of the affected area (the affected lung segments and lobes) among the three groups (P<0.05 or 0.01, Fig 1A). These results confirmed that there were significant differences in the extent and degree of lung inflammation among patients with mild, moderate and severe pulmonary fibrosis; that is, patients with severe pulmonary fibrosis had the most severe and extensive lung inflammation, followed by patients with moderate pulmonary fibrosis, while patients with mild pulmonary fibrosis had the least severe and extensive lung inflammation.

Fig 1.

Fig 1

Open in a new tab

A. The AI inflammation scores of 239 COVID-19 patients with pulmonary fibrosis at discharge. *, P<0.05; **, P<0.01; B. Comparison of the AI inflammation score or pulmonary fibrosis score between patients at discharge and 30 days (n = 34 patients), 60 days (n = 11 patients) and 90 days (n = 7 patients) after discharge. C. Comparison of chest HRCT results between patients at discharge and 30 days after hospital discharge. a, b and c represent three separate patients: a represents a patient with mild pulmonary fibrosis, b represents a patient with moderate pulmonary fibrosis, and c represents a patient with severe pulmonary fibrosis. ① represents the chest HRCT at discharge; ② represents the extent of lesions marked by AI at discharge (red); ③ represents the chest HRCT 30 days after hospital discharge; ④ represents the extent of lesions marked by AI 30 days after hospital discharge (red).

Risk factors for pulmonary fibrosis

After stratifying the 239 patients with pulmonary fibrosis during hospitalization according to their degree of pulmonary fibrosis at discharge, their clinical characteristics were analyzed. Patients with or without pulmonary fibrosis had statistically significant differences in age, IL-6 levels, lymphocyte %, aspartate transaminase (AST), albumin, CRP/albumin ratio, platelet/lymphocyte ratio and some other indexes (Table 3), suggesting that these abnormal clinical indicators may be related to the pulmonary fibrosis.

Table 3. The clinical characteristics of COVID-19 patients with pulmonary fibrosis at discharge.

Patients with pulmonary fibrosis Patients without pulmonary fibrosis χ2/T value P value
Number 239 45 — —
Age, years, mean (SD) 55.87±1.03 47.29±2.85 3.216 0.002※
Sex
Female 136 26 0.012 0.914
Male 103 19
Symptom
High fever (≥38.5°C) 99 7 10.83 0.001※
Cough 164 24 3.954 0.047#
Wheezing 69 8 2.358 0.125
Chest tightness 66 6 4.082 0.043#
IL-6
Acute stage 30.86±2.58 5.99±1.00 4.163 0.000※
Hospital discharge 5.89±0.53 2.59±0.53 3.577 0.000※
Laboratory findings
WBC, ×10⁹ per L 5.56±0.18 5.51±0.22 0.102 0.919
Lymphocyte ×10⁹ per L 1.24±0.07 1.70±0.11 2.583 0.010※
Lymphocyte % 24.58±0.81 31.43±1.76 3.381 0.001※
Platelet, ×10⁹ per L 200.10±4.90 212.80±9.60 1.054 0.293
HB (g/L) 127.10±1.16 132.20±2.65 1.767 0.078
CRP (mg/L) 28.00±2.52 7.38±1.36 3.534 0.001※
PCT (ng/mL) 0.31±0.14 0.04±0.00 0.808 0.420
ALT, U/L 33.42±2.63 25.58±4.28 1.236 0.217
AST, U/L 35.52±1.44 26.78±2.18 2.531 0.011※
Albumin (g/L) 38.34±0.31 42.28±0.51 5.270 0.000※
Creatinine (μmol/L) 67.33±1.22 67.82±2.23 0.166 0.868
Glucose (mmol/L) 6.74±0.17 6.13±0.34 1.421 0.156
Potassium (mmol/L) 3.86±0.03 3.91±0.07 0.620 0.536
CK (U/L) 68.11±10.91 54.09±9.05 0.547 0.585
Myoglobin (μg/L) 54.25±4.93 42.21±7.71 1.016 0.311
hs-cTnT, pg/mL 0.07±0.04 0.01±0.00 0.640 0.522
Prothrombin time, s 12.08±0.08 15.38±2.50 3.031 0.003※
APTT 32.42±0.25 33.56±0.53 1.822 0.070
D-dimer (mg/L) 387.80±69.36 164.70±40.40 1.386 0.167
AST/ALT 1.38±0.64 1.33±0.51 -0.067 0.946
CRP/albumin ratio 0.80±1.19 0.18±0.22 -4.946 0.000※
Platelet/lymphocyte ratio 209.98±148.92 146.72±70.49 -3.151 0.002#
Cellular immunity-related indexes
CD3 count (N = 174+37) 790.90±33.23 1262.00±89.02 5.687 0.000※
CD4 count (N = 174+37) 451.10±21.24 735.70±57.62 5.355 0.000※
CD8 count (N = 174+37) 282.00±15.01 418.40±36.19 3.728 0.000※
CD19 count (N = 174+37) 160.60±7.57 277.20±31.01 5.371 0.000※
CD16+56 (N = 174+37) 216.60±16.37 246.40±35.07 0.765 0.445
Humoral immunity-related indexes
IgG (g/L) (N = 112+17) 9.79±0.57 9.54±1.84 0.153 0.879
IgM (g/L) (N = 112+17) 4.81±0.59 6.14±1.67 0.815 0.417
IgA (g/L) (N = 112+17) 2.64±0.90 1.62±0.20 0.438 0.662
Open in a new tab

#, P<0.05

※, P<0.01

Analysis of risk factors in patients with pulmonary fibrosis

Multivariate binary logistic regression analysis was used to evaluate the relationship between the quantitative pulmonary fibrosis score and the related risk factors in 248 COVID-19 patients (Table 4). Our results showed that there were significant relationships between pulmonary fibrosis and the levels of albumin and IL-6, which suggests that IL-6 and albumin are independent risk factors affecting pulmonary fibrosis. The regression equation is logit(P) = β0+β1*X1+β2*X2 (where β0 = 9.964, β1 = 0.078, β2 = -0.197, X1 is the IL-6 level in the acute stage, and X2 is the albumin level).

Prognosis of patients with pulmonary fibrosis

Thirty-four of the 239 COVID-19 patients underwent chest HRCT 30 days after hospital discharge (23 moderate, 7 severe, 4 critical), 11 patients underwent chest HRCT 60 days after discharge (3 moderate, 6 severe, 2 critical), and 7 patients underwent chest HRCT 90 days after discharge (4 moderate, 1 severe, 2 critical). All of these patients showed significant improvements in ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing and bronchiectasis (Table 5, P<0.01). The linear opacities, interlobular septal thickening, reticulation, honeycombing and bronchiectasis were completely resolved 90 days after discharge.

Table 5. The prognosis of patients with pulmonary fibrosis.

The affected lung segment Follow-up after 30 days (n = 34) Follow-up after 60 days (n = 11) Follow-up after 90 days (n = 7)
At discharge After 30 days t/Z, P At discharge After 60 days t/Z, P At discharge After 90 days t/Z, P
Ground-glass opacity [n (%)] 29(85.29%) 18(52.94%) 10(90.91%) 4(36.36%) 5(71.43%) 1(14.29%)
    Affected lung segments 5.74±4.31 3.26±3.73 -2.427, 0.015 8.27±4.45 3.36±3.36 -2.494, 0.13 4.29±5.06 0.43±1.13 -1.986, 0.47
Linear opacities [n (%)] 27(79.41%) 20(58.82%) 11(100.00%) 8(72.73%) 7(100.00%) 2(28.57%)
    Affected lung segments 3.18±2.37 2.06±2.51 -2.175, 0.030 5.00±2.35 2.45±2.88 -2.124, 0.034 3.71±1.80 0.71±1.25 -2.688, 0.07
Interlobular septal thickening [n (%)] 10(29.41%) 4(11.76%) 4(36.36%) 2(18.18%) 3(42.86%) 0(0.00%)
    Affected lung segments 1.15±2.16 0.32±0.94 -1.8678,0.062 1.45±2.34 0.64±1.57 -0.963,0.336 1.29±1.89 0.00 —
Reticulation [n (%)] 8(23.53%) 1(2.94%) 4(36.36%) 1(9.09%) 5(71.43%) 0(0.00%)
    Affected lung segments 0.82±1.68 0.09±0.51 -2.499,0.012 1.18±2.32 0.27±0.90 -1.122,0.262 1.29±1.89 0.00 —
Honeycombing or bronchiectasis [n (%)] 8(23.53%) 2(5.88%) 4(36.36%) 1(9.09%) 2(28.57%) 0(0.00%)
    Affected lung segments 0.71±1.75 1.65±4.48 -4.253,0.000 1.55±1.44 0.09±0.30 -2.749, 0.006 1.71±3.40 0.00 —
Open in a new tab

AI inflammation score as an evaluation of the evolution of pulmonary fibrosis

The AI inflammation score and quantitative pulmonary fibrosis score in the patients included in this study were analyzed 30 days, 60 days and 90 days after hospital discharge. The results showed that the degree of pulmonary inflammation (PIV, PIV/WLV), the extent of the affected area (the affected lung segment and lobes), and the quantitative pulmonary fibrosis score were significantly improved 30, 60 and 90 days after discharge (Fig 1B and 1C, P<0.01).

Discussion

Quantitative CT scores have been used to assess the severity of pulmonary fibrosis in patients with idiopathic pulmonary fibrosis [16–19]. In this study, we found that approximately 80% of the 284 COVID-19 patients had pulmonary fibrosis at discharge. The incidence of pulmonary fibrosis in patients with moderate COVID-19 was relatively low (incidence rate 73.8%), but it occurred in all patients with severe or critical COVID-19. In particular, patients with moderate or severe COVID-19 usually developed mild-to-moderate pulmonary fibrosis, while patients with critical COVID-19 generally developed severe pulmonary fibrosis. These results confirmed that the degree of fibrosis was more severe in patients with critical COVID-19 than in patients with moderate or severe COVID-19, which may be related to the fact that acute-stage lung inflammation was more extensive and severe in patients with severe and critical cases of COVID-19.

AI-assisted chest HRCT technology was used to quantitatively evaluate the extent and degree of lung inflammation, and it provided a relatively accurate evaluation of the inflammatory status of the lungs. We observed that patients with severe pulmonary fibrosis had more extensive and severe lung inflammation than those with mild or moderate fibrosis. The AI inflammation score demonstrated good consistency with the quantitative pulmonary fibrosis score, which showed that AI-assisted chest HRCT technology could be used to not only quantify the degree of lung inflammation but also indirectly reflect the degree of pulmonary fibrosis, providing qualitative and quantitative data that could be used to analyze the long-term evolution of pulmonary fibrosis.

Previous studies reported that IL-6 could serve as an indicator of the progression of COVID-19 [20]. IL-6 levels can reflect the severity of the inflammatory response. Our results showed that IL-6 is an independent risk factor for pulmonary fibrosis. Its underlying mechanisms may be as follows: IL-6 activates neutrophils and promotes their accumulation at the site of injury, induces the release of protease and oxygen free radicals, and finally leads to pulmonary interstitial edema and a severe inflammatory response [21]. Moreover, we also identified albumin as an independent risk factor for pulmonary fibrosis, which emphasized the importance of correcting albumin abnormalities in patients with COVID-19.

It was reported that the AST/ALT ratio on admission was significantly associated with in-hospital mortality in COVID-19 patients [22]. In this work, we found that there were significant relationships between the levels of AST and pulmonary fibrosis. AST displays the highest activity in the liver and skeletal muscle but also occurs in several tissues, including lungs, heart muscle, kidneys, pancreas, brain, leucocyte and erythrocytes. AST is less specific for liver damage compared to ALT [22]. Therefore, COVID-19 patients with a significant increase in AST may also have large damage in other tissues, including the lungs, which may affect pulmonary fibrosis at discharge. Larger studies are required to confirm the capacity of this parameter to independently predict pulmonary damage and fibrosis in this group. We have revised it and added the article as a reference in the revised version.

In addition, we found that the degree of pulmonary inflammation (PIV, PIV/WLV), the extent of the affected area (the affected lung segments and lobes), and the pulmonary fibrosis scores of COVID-19 patients were significantly improved 30 days, 60 days and 90 days after discharge, which confirmed that pulmonary fibrosis was likely to resolve after discharge. Meanwhile, we also noted that the pulmonary fibrosis in some patients did not completely resolve within 90 days, and whether additional antifibrosis treatment could accelerate the process is worthy of further investigation. A proportion of SARS patients still had obvious additional improvements in interstitial injuries and lung functional recovery 2 years after hospital discharge [23]. Therefore, it is theoretically possible for patients with incompletely resolved pulmonary fibrosis within 90 days to continue to recover.

As it was retrospective, this study has some limitations. First, many of the patients were unwilling to undergo periodic HRCT reexaminations after discharge, and the relatively few patients with follow-up data limited our analysis and led to biased results. Second, pulmonary function data were unavailable in this study, and the extent to which pulmonary fibrosis influences pulmonary function remains unclear; however, our study explored the dynamic evolution of the structural abnormalities in the lungs using HRCT, and lung function should theoretically be restored if the lung structure returns to normal. Third, most of the patients admitted to our hospital were had moderate, severe or critical COVID-19, so it is still unknown whether pulmonary fibrosis occurs in patients with mild COVID-19 and, if so, what the clinical characteristics are; however, the study site was a designated hospital that treated a large number of COVID-19 patients in Wuhan, and our study included all patients who achieved a clinical cure in our hospital within 2 months. Therefore, this study is still representative of pulmonary fibrosis in COVID-19 patients.

In conclusion, AI-assisted chest HRCT technology was used in this study, and we found that the more severe the clinical classification of COVID-19 was, the more extensive and severe the lung inflammation and the more severe the residual pulmonary fibrosis. In most of these patients, pulmonary fibrosis improved or even resolved within 90 days after discharge. Furthermore, the levels of IL-6 and albumin are independent risk factors for pulmonary fibrosis and should be regarded as important therapeutic targets for the treatment of COVID-19 patients with pulmonary fibrosis.

Supporting information

S1 File

(XLSX)

Click here for additional data file. (70.8KB, xlsx)
S2 File

(XLSX)

Click here for additional data file. (103.1KB, xlsx)
S3 File

(XLSX)

Click here for additional data file. (95.4KB, xlsx)
S4 File

(XLSX)

Click here for additional data file. (2.3MB, xlsx)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This study was supported by grant 81770981 and 82002863 from the National Natural Science Foundation of China and grant [2018]116 from Wuhan Municipality Young and Middle-aged Medical Talent Cultivation Program.

References

  • 1.Spagnolo P, Maher TM, Richeldi L. Idiopathic pulmonary fibrosis: Recent advances on pharmacological therapy. Pharmacol Ther. 2015; 152: 18–27. 10.1016/j.pharmthera.2015.04.005 [DOI] [PubMed] [Google Scholar]
  • 2.Sheng G, Chen P, Wei Y, Yue H, Chu J, Zhao J, et al. Viral infection increases the risk of idiopathic pulmonary fibrosis: a meta-analysis. Chest. 2020; 157(5): 1175–1187. 10.1016/j.chest.2019.10.032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Hui DS, Wong KT, Ko FW, Tam LS, Chan DP, Woo J, et al. The 1-year impact of severe acute respiratory syndrome on pulmonary function, exercise capacity, and quality of life in a cohort of survivors. Chest. 2005; 128(4): 2247–2261. 10.1378/chest.128.4.2247 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Ngai JC, Ko FW, Ng SS, To KW, Tong M, Hui DS. The long-term impact of severe acute respiratory syndrome on pulmonary function, exercise capacity and health status. Respirology. 2010; 15(3): 543–550. 10.1111/j.1440-1843.2010.01720.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Das KM, Lee EY, Singh R, Enani MA, Al Dossari K, Van Gorkom K, et al. Follow-up chest radiographic findings in patients with MERS-CoV after recovery. Indian J Radiol Imaging. 2017; 27(3): 342–349. 10.4103/ijri.IJRI_469_16 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Xu J, Zhao S, Teng T, Abdalla AE, Zhu W, Xie L, et al. Systematic Comparison of Two Animal-to-Human Transmitted Human Coronaviruses: SARS-CoV-2 and SARS-CoV. Viruses. 2020; 12(2):244. 10.3390/v12020244 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.George PM, Wells AU, Jenkins RG. Pulmonary fibrosis and COVID-19: the potential role for antifibrotic therapy [published online ahead of print, 2020 May 15].Lancet Respir Med, 2020; S2213-2600(20)30225-3. 10.1016/S2213-2600(20)30225-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Ding Y, Wang H, Shen H, Li Z, Geng J, Han H, et al. The clinical pathology of severe acute respiratory syndrome (SARS): a report from China. J Pathol, 2003; 200(3): 282–289. 10.1002/path.1440 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Li M. Chest CT features and their role in COVID-19. Radiology of Infectious Diseases, 2020. 10.1016/j.jrid.2020.04.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Baratella E, Crivelli P, Marrocchio C, Bozzato AM, Vito A, Madeddu G, et al. Severity of lung involvement on chest X-rays in SARS-coronavirus-2 infected patients as a possible tool to predict clinical progression: an observational retrospective analysis of the relationship between radiological, clinical, and laboratory data. J Bras Pneumol. 2020; 46(5):e20200226. 10.36416/1806-3756/e20200226 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Qi X, Lei J, Yu Q, Xi Y, Wang Y, Ju S. CT imaging of coronavirus disease 2019 (COVID-19): from the qualitative to quantitative. Ann Transl Med, 2020; 8(5): 256. 10.21037/atm.2020.02.91 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Zou Y, Wang BR, Sun L, Xu S, Kong YG, Shen LJ, et al. The issue of recurrently positive patients who recovered from COVID-19 according to the current discharge criteria: investigation of patients from multiple medical institutions in Wuhan, China. J Infect Dis, 2020; 222(11):1784–1788. 10.1093/infdis/jiaa301 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.China National Health Commission. Diagnosis and treatment of 2019-nCoV pneumonia in China (7th ed.). In Chinese. Published March3, 2020. Accessed March 25,2020. http://www.nhc.gov.cn/yzygj/s7653p/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtm
  • 14.Yang R, Li X, Liu H, Zhen YL. Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiology Cardiothoracic Imaging, 2020; 2(2): e200047. 10.1148/ryct.2020200047 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Camiciottoli G, Orlandi I, Bartolucci M, Meoni E, Nacci F, Diciotti S, et al. Lung CT densitometry in systemic sclerosis: correlation with lung function, exercise testing, and quality of life. Chest. 2007;131(3):672–681. 10.1378/chest.06-1401 [DOI] [PubMed] [Google Scholar]
  • 16.Jacob J, Bartholmai BJ, Rajagopalan S, Kokosi M, Egashira R, Brun AL, et al. Serial automated quantitative CT analysis in idiopathic pulmonary fibrosis: functional correlations and comparison with changes in visual CT scores. Eur Radiol, 2018; 28(3): 1318–1327. 10.1007/s00330-017-5053-z [DOI] [PubMed] [Google Scholar]
  • 17.Choi KW, Chau TN, Tsang O, Tso E, Chiu MC, Tong WL, et al. Outcomes and prognostic factors in 267 patients with severe acute respiratory syndrome in Hong Kong. Ann Intern Med, 2003; 139(9): 715–723. 10.7326/0003-4819-139-9-200311040-00005 [DOI] [PubMed] [Google Scholar]
  • 18.Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet, 2020; 395(10229): 1054–1062. 10.1016/S0140-6736(20)30566-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Opal SM, Girard TD, Ely EW. The immunopathogenesis of sepsis in elderly patients. Clin Infect Dis, 2005; 41 Suppl 7:S504–S512. 10.1086/432007 [DOI] [PubMed] [Google Scholar]
  • 20.Wan SX, Yi QJ, Fan SB. Relationships among lymphocyte subsets, cytokines, and the pulmonary inflammation index in coronavirus (COVID-19) infected patients. British Journal of Haematology, 2020; 189: 428–437. 10.1111/bjh.16659 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Moitra S, Puri R, Paul D, Huang YC. Global perspectives of emerging occupational and environmental lung diseases. Curr Opin Pulm Med, 2015; 21(2): 114–120. 10.1097/MCP.0000000000000136 [DOI] [PubMed] [Google Scholar]
  • 22.Zinellu A, Arru F, De Vito A, Sassu A, Valdes G, Scano V, et al. The De Ritis ratio as prognostic biomarker of in-hospital mortality in COVID-19 patients. Eur J Clin Invest,2021;51(1):e13427. 10.1111/eci.13427 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Zhang P, Li J, Liu H, Han N, Ju J, Kou Y, et al. Long-term bone and lung consequences associated with hospital-acquired severe acute respiratory syndrome: a 15-year follow-up from a prospective cohort study. Bone Res, 2020; 8: 8. 10.1038/s41413-020-0084-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Giordano Madeddu

9 Dec 2020

PONE-D-20-31950

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT

PLOS ONE

Dear Dr. Chen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 23 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Giordano Madeddu

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In the ethics statement in the manuscript and in the online submission form, please provide additional information about the patient records/samples used in your retrospective study, including: a) whether all data were fully anonymized before you accessed them; b) the date range (month and year) during which patients' medical records/samples were accessed.

3. Thank you for stating the following in the Funding Section of your manuscript:

"This study was supported by grant 81770981 and 82002863 from the

National Natural Science Foundation of China and grant [2018]116 from Wuhan

Municipality Young and Middle-aged Medical Talent Cultivation Program."

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

"Unfunded studies"

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

4. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

5. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Authors,

First, I would like to thank you for the paper you submitted. After the great interest grown in the scientific community in the first months of the year toward the acute phase of COVID-19 and its possible treatments, now it is the time to ask us what will happen after the infection, and if these modifications will affect survivors for the rest of their lives. In the wake of the outcomes of SARS-CoV and MERS-CoV pneumonia, many papers investigating on the possible long-time effects of COVID-19 have been published in the past few months, but, by now, the follow-up timing is too short to establish a permanent effect. During 2020 numerous studies investigated toward the role of AI in the diagnosis of COVID-19 pneumonia, but this is possibly the first paper published on the use of AI in the evolution of pneumonia after the clinical healing and its role in predicting fibrosis, even if there are many limitations, that you correctly identified.

However, I have a few concerns I will enlist you as follow.

Minor concerns:

- In the abstract, you repeated the phrase “IL-6 and albumin are independent risk factors for pulmonary fibrosis” twice.

- Page 4, line 66: there is a typo, for it is written “SARA-CoA-2” instead of “SARS-CoV-2”.

- Page 5, line 88: milliampere-second is written in one word.

- Page 6, line 99: “anterior endobasal segment” is not a term commonly used in the anatomy of lung segments. Did you mean medial segment of the lower lobe? Please, correct.

- Page 8, line 149: you say that 248 patients were enrolled, clearly a refuse.

Major concerns:

- Page 3, line 33-34: there is an imprecision that I would suggest you to correct. In fact, you correctly reported that SARS-CoV-2 is similar for the 85% of genome to a bat coronavirus, but after that you included on parenthesis SARS-CoV: SARS-CoV-2, instead, share 85% of its genome with bat coronavirus bat-SL-CoVZC45 (Xu J, Zhao S, Teng T, Abdalla AE, Zhu W, Xie L, Wang Y, Guo X. Systematic Comparison of Two Animal-to-Human Transmitted Human Coronaviruses: SARS-CoV-2 and SARS-CoV. Viruses. 2020 Feb 22;12(2):244. doi: 10.3390/v12020244. PMID: 32098422; PMCID: PMC7077191).

- Page 6, line 95-96: you used the term “shadow” to describe many CT findings associated with COVID-19 pneumonia. This term it is not used by other radiologists in an international setting: I suggest you to change it with the common used “linear opacities” and honeycombing. I did not understand the term “mesh shadows”: could you explain it better?

- In page 6, line 104, you cited a score for lung fibrosis proposed by Camiciottoli, followed by an apex “1”. You didn’t cite the relative paper.

- In page 8, line 150 you say that patients with pulmonary fibrosis were 239, while in the rest of the text you say 237. I suggest you to correct the refuse.

- Page 9, paragraph “The relationship between the degree of pulmonary fibrosis and the clinical classification”: I suggest you to write again the initial part of the paragraph where you enlist the amount of patients with fibrosis for each group, because as it is written by now it is confusing and it is necessary to look at table 1 to understand what you meant.

- In the study, you found a statistical association with the elevation of AST and severity of fibrosis. A recently published study showed a peculiar association between AST/ALT ratio, known also as de Ritis ratio, and hospital mortality in COVID-19 patients, tied also to a larger pneumonia (Zinellu A, Arru F, De Vito A, Sassu A, Valdes G, Scano V, Zinellu E, Perra R, Madeddu G, Carru C, Pirina P, Mangoni AA, Babudieri S, Fois AG. The De Ritis ratio as prognostic biomarker of in-hospital mortality in COVID-19 patients. Eur J Clin Invest. 2020 Oct 11:e13427. doi: 10.1111/eci.13427. Epub ahead of print. PMID: 33043447; PMCID: PMC7646002). I suggest you to read this work and evaluate if de Ritis ratio was also associated with more severe pulmonary fibrosis. Moreover, another study found an association with others laboratory findings and combined indexes, and I suggest you to have a look for a comparison: Paliogiannis P, Zinellu A, Scano V, Mulas G, De Riu G, Pascale RM, Arru LB, Carru C, Pirina P, Mangoni AA, Fois AG. Laboratory test alterations in patients with COVID-19 and non COVID-19 interstitial pneumonia: a preliminary report. J Infect Dev Ctries. 2020 Jul 31;14(7):685-690. doi: 10.3855/jidc.12879. PMID: 32794454.

- It is a great pity that after all the good analysis you conducted you didn’t specify the category of patients who underwent CT at 30, 60 and 90 days from discharge: it would be very interesting to know if they were all severe cases or belonged to different groups. I suggest you to specify it. I would also like to know why only few patients had a new CT scan: were they symptomatic? Did symptoms mismatch CT findings? Why you suggest the use pf antibiotics in patients showing residual interstitial abnormalities after 90 days?

The abstract is concise and it is representative of the full article, and discussion and conclusion are coherent with the study and data shown.

The paper is generally well-written, but there are many phrase constructions atypical for English grammar which probably reflects a literal translation from your native language. I suggest an overall revision of the language, preferably from a mother tongue one.

Reviewer #2: General comments

The paper entitled “The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT” by Chen and Co-wokers is aimed at evaluating a possible role of artificial intelligence applied to chest CT in order to provide an important basis for the clinical diagnosis, treatment and prognosis of COVID-19 pulmonary fibrosis. The aim is clear and the topic is interesting and innovative. The paper is well written. Some shortcomings need to be addressed; in particular, the retrospective nature of this study and the relative high number of missed CT could affect the inference of the results.

Detailed comments

Introduction:

- “Pulmonary fibrosis is a serious complication of viral pneumonia, which often leads to dyspnea and impaired lung function”: I suggest “pulmonary fibrosis can occur as a serious …”

- Line 43: I suggest: “Chest x-rays and high-resolution-CT (citing Severity of lung involvement on chest X-rays in SARS-coronavirus-2 infected patients as a possible tool to predict clinical progression: an observational retrospective analysis of the relationship between radiological, clinical, and laboratory data. Baratella E, Crivelli P, Marrocchio C, Bozzato AM, Vito A, Madeddu G, Saderi L, Confalonieri M, Tenaglia L, Cova MA. J Bras Pneumol. 2020 Sep 21;46(5):e20200226. doi: 10.36416/1806-3756/e20200226. eCollection 2020).

- Methods:

- Chest CT protocol: Authors could better explain the mean radiation dose exposure during CT.

- Chest CT image analysis: Authors could better clarify the years of experience on chest CT images.

- “… striated shadow or mesh shadow…” Authors could explain the mean of these words.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Mar 23;16(3):e0248957. doi: 10.1371/journal.pone.0248957.r002

Author response to Decision Letter 0

11 Jan 2021

Dec 22, 2020

Dear Editors and Reviewers:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT”. (ID: PONE-D-20-31950).

These comments are very constructive and helpful for revising our paper. We have discussed the comments carefully and have made revisions which we hope will be met with approval. They are all marked in blue in the revised version. The main answers to the reviewer’s comments are as follow:

1.Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Answer: Thank you for this comment. We have revised the article format according to PLOS ONE's style requirements.

2.In the ethics statement in the manuscript and in the online submission form, please provide additional information about the patient records/samples used in your retrospective study, including: a) whether all data were fully anonymized before you accessed them; b) the date range (month and year) during which patients' medical records/samples were accessed.

Answer: Thank you for this comment. We make sure that all data were anonymous. The patients' medical records were accessed from February 1 to June 8, 2020. We have added these to the revised version and marked in blue in page 5, line 77-78.

3.Thank you for stating the following in the Funding Section of your manuscript:

"This study was supported by grant 81770981 and 82002863 from the

National Natural Science Foundation of China and grant [2018]116 from Wuhan

Municipality Young and Middle-aged Medical Talent Cultivation Program."

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

"Unfunded studies"

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

Answer: Thank you for this comment. We have removed the fund information in the manuscript and added it in the cover letter. However, we can not added it in the online submission form. We would be very grateful if you could change the online submission form on our behalf.

4.PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

Answer: Thank you for this comment. We have already applied ORCID iD (0000-0002-1216-004X).

5.Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

Answer: Thank you for this comment. We've removed ethics statement in any other section.

Reviewer 1:

Specific comments:

1. In the abstract, you repeated the phrase “IL-6 and albumin are independent risk factors for pulmonary fibrosis” twice.

Answer: Thank you for this comment. We have revised it and marked in blue in page 2, line 12.

2. there is a typo, for it is written “SARA-CoA-2” instead of “SARS-CoV-2”.

Answer: Thank you for this comment. We have revised it and marked in blue in page 5, line 69.

3. milliampere-second is written in one word.

Answer: Thank you for this comment. We have revised it and marked in blue in page 6, line 89-90.

4.“anterior endobasal segment” is not a term commonly used in the anatomy of lung segments. Did you mean medial segment of the lower lobe? Please, correct.

Answer: Thank you for this comment. “anterior endobasal segment” mean“anterior and basal segmental”. We have revised it and marked in blue in page 6, line 97-99.

5.you say that 248 patients were enrolled, clearly a refuse.

Answer: Thank you for this comment. We have revised it and marked in blue in page 9, line 157.

6. there is an imprecision that I would suggest you to correct. In fact, you correctly reported that SARS-CoV-2 is similar for the 85% of genome to a bat coronavirus, but after that you included on parenthesis SARS-CoV: SARS-CoV-2, instead, share 85% of its genome with bat coronavirus bat-SL-CoVZC45 (Xu J, Zhao S, Teng T, Abdalla AE, Zhu W, Xie L, Wang Y, Guo X. Systematic Comparison of Two Animal-to-Human Transmitted Human Coronaviruses: SARS-CoV-2 and SARS-CoV. Viruses. 2020 Feb 22;12(2):244. doi: 10.3390/v12020244. PMID: 32098422; PMCID: PMC7077191).

Answer: Thank you for this comment. We have revised SARS-CoV-2 share 85% of its genome with bat coronavirus bat-SL-CoVZC45 in the revised version and marked in blue in page 3, line 34-35.

7. you used the term “shadow” to describe many CT findings associated with COVID-19 pneumonia. This term it is not used by other radiologists in an international setting: I suggest you to change it with the common used “linear opacities” and honeycombing. I did not understand the term “mesh shadows”: could you explain it better?

Answer: Thank you for this comment. “shadow”should be “linear opacities”. “mesh shadows”should be “reticulation”. We have revised it and marked in blue in the Manuscript and Revised Manuscript with Track Changes.

8. you cited a score for lung fibrosis proposed by Camiciottoli, followed by an apex “1”. You didn’t cite the relative paper.

Answer: Thank you for this comment. We have added references in the Manuscript and Revised Manuscript with Track Changes. (Camiciottoli G, Orlandi I, Bartolucci M, Meoni E, Nacci F, Diciotti S, et al Lung CT densitometry in systemic sclerosis: correlation with lung function, exercise testing, and quality of life. Chest. 2007;131(3):672-681. doi.10.1378/chest.06-1401. )

9. you say that patients with pulmonary fibrosis were 239, while in the rest of the text you say 237. I suggest you to correct the refuse.

Answer: Thank you for this comment. The patients with pulmonary fibrosis were 239. We have corrected it in the rest of the text and marked in blue in page 9, line 173.

10. paragraph “The relationship between the degree of pulmonary fibrosis and the clinical classification”: I suggest you to write again the initial part of the paragraph where you enlist the amount of patients with fibrosis for each group, because as it is written by now it is confusing and it is necessary to look at table 1 to understand what you meant.

Answer: Thank you for this comment. We have write again the paragraph and marked in blue in page 9-10, line 173-182.

11.In the study, you found a statistical association with the elevation of AST and severity of fibrosis. A recently published study showed a peculiar association between AST/ALT ratio, known also as de Ritis ratio, and hospital mortality in COVID-19 patients, tied also to a larger pneumonia (Zinellu A, Arru F, De Vito A, Sassu A, Valdes G, Scano V, Zinellu E, Perra R, Madeddu G, Carru C, Pirina P, Mangoni AA, Babudieri S, Fois AG. The De Ritis ratio as prognostic biomarker of in-hospital mortality in COVID-19 patients. Eur J Clin Invest. 2020 Oct 11:e13427. doi: 10.1111/eci.13427. Epub ahead of print. PMID: 33043447; PMCID: PMC7646002). I suggest you to read this work and evaluate if de Ritis ratio was also associated with more severe pulmonary fibrosis. Moreover, another study found an association with others laboratory findings and combined indexes, and I suggest you to have a look for a comparison: Paliogiannis P, Zinellu A, Scano V, Mulas G, De Riu G, Pascale RM, Arru LB, Carru C, Pirina P, Mangoni AA, Fois AG. Laboratory test alterations in patients with COVID-19 and non COVID-19 interstitial pneumonia: a preliminary report. J Infect Dev Ctries. 2020 Jul 31;14(7):685-690. doi: 10.3855/jidc.12879. PMID: 32794454.

Answer: Thank you for this comment. It is a very good suggestion.We have found that CRP/albumin ratio, platelet/ lymphocyte ratio was associated with pulmonary fibrosis. We have included these results in the revised version and marked in blue in page 13.

12.It is a great pity that after all the good analysis you conducted you didn’t specify the category of patients who underwent CT at 30, 60 and 90 days from discharge: it would be very interesting to know if they were all severe cases or belonged to different groups. I suggest you to specify it. I would also like to know why only few patients had a new CT scan: were they symptomatic? Did symptoms mismatch CT findings? Why you suggest the use pf antibiotics in patients showing residual interstitial abnormalities after 90 days?

The abstract is concise and it is representative of the full article, and discussion and conclusion are coherent with the study and data shown. The paper is generally well-written, but there are many phrase constructions atypical for English grammar which probably reflects a literal translation from your native language. I suggest an overall revision of the language, preferably from a mother tongue one.

Answer: Thank you for these comment.

They belonged to different groups.We have revised it and marked in blue in page 14 line 238-240

All of the patients are required to undergo a chest CT scan after discharge in accordance with the guidelines, but many of them worry about radiation in chest CT. So only few patients had a new CT scan. And their symptoms were matched with CT findings.

As for the usage of antibiotics, we have made a mistake. It should be anti-fibrosis treatment. We have revised it and marked in blue in page 17, line 286.

As for the English grammar, we also know this is a very important issue. The revised manuscript has been proofread by an English-speaking professional with science background at Springer Nature Author Services. The certificate is uploaded as an attachment.

Reviewer 2:

1.“Pulmonary fibrosis is a serious complication of viral pneumonia, which often leads to dyspnea and impaired lung function”: I suggest “pulmonary fibrosis can occur as a serious …”

Answer: Thank you for this comment.We have revised it and marked in blue in page 3, line 24 .

2. I suggest: “Chest x-rays and high-resolution-CT (citing Severity of lung involvement on chest X-rays in SARS-coronavirus-2 infected patients as a possible tool to predict clinical progression: an observational retrospective analysis of the relationship between radiological, clinical, and laboratory data. Baratella E, Crivelli P, Marrocchio C, Bozzato AM, Vito A, Madeddu G, Saderi L, Confalonieri M, Tenaglia L, Cova MA. J Bras Pneumol. 2020 Sep 21;46(5):e20200226. doi: 10.36416/1806-3756/e20200226. eCollection 2020).

Answer: Thank you for this comment. We have revised it and marked in blue in page 3, line 44 .

3.Chest CT protocol: Authors could better explain the mean radiation dose exposure during CT.

Answer: Thank you for this comment. The mean radiation dose during CT is 7 mGy. We have revised it and marked in blue in page 6, line 89-90.

4.Chest CT image analysis: Authors could better clarify the years of experience on chest CT images.

Answer: Thank you for this comment. The years of experience on chest CT images analysis included the distribution of the lesion, the location of the lesion, the number of lobes involved, the characteristics of the lesion and external involvement. We have revised it and marked in blue in page 6, line 97-99 .

5. “… striated shadow or mesh shadow…” Authors could explain the mean of these words.

Answer: Thank you for this comment. “striated shadow” should be “linear opacities”.“mesh shadow” should be” reticulation”. We have revised it and marked in blue in the Manuscript and Revised Manuscript with Track Changes.

All of the revisions are shown here. We would like to express our great appreciation to you and reviewers for comments on our paper.

Looking forward to hearing from you.

Best regards,

Shi-Ming Chen

Attachment

Submitted filename: Response to Reviewers OF PONE-D-20-31950.docx

Click here for additional data file. (108.2KB, docx)

Decision Letter 1

Giordano Madeddu

11 Feb 2021

PONE-D-20-31950R1

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT

PLOS ONE

Dear Dr. Chen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Mar 28 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Giordano Madeddu

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The revised manuscript is well written, the topic is original and Clear. Authors responded correctly to the requested reviews

Reviewer #3: The paper was revised in the correct way, although no article is mentioned in support of important laboratory prognostic indices in particular on liver function (https://doi.org/10.1111/eci.13427).

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: Yes: Paola Crivelli

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Mar 23;16(3):e0248957. doi: 10.1371/journal.pone.0248957.r004

Author response to Decision Letter 1

16 Feb 2021

Feb 16, 2021

Dear Editors and Reviewers:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT”. (ID: PONE-D-20-31950).

These comments are very constructive and helpful for revising our paper. We have discussed the comments carefully and have made revisions which we hope will be met with approval. They are all marked in blue in the revised version. The main answers to the reviewer’s comments are as follow:

1.The paper was revised in the correct way, although no article is mentioned in support of important laboratory prognostic indices in particular on liver function (https://doi.org/10.1111/eci.13427)

Answer: Thank you for this comment. This is a good suggestion.

It was reported that the AST/ALT ratio on admission was significantly associated with in-hospital mortality in COVID-19 patients[https://doi.org/10.1111/eci.13427]. In this work, we found that there were significant relationships between the levels of AST and pulmonary fibrosis. AST displays the highest activity in the liver and skeletal muscle but also occurs in several tissues, including lungs, heart muscle, kidneys, pancreas, brain, leucocyte and erythrocytes. AST is less specific for liver damage compared to ALT[https://doi.org/10.1111/eci.13427]. Therefore, COVID-19 patients with a significant increase in AST may also have large damage in other tissues, including the lungs, which may affect pulmonary fibrosis at discharge. Larger studies are required to confirm the capacity of this parameter to independently predict pulmonary damage and fibrosis in this group. We have revised it and added the article as a reference in the revised version.

2.There are some spelling errors in page 2, line 11-13. It should be as follow: The IL-6 level in the acute stage and albumin level were independent risk factors for pulmonary fibrosis. We have revised it and marked in blue in the revised version.

3.There are some spelling errors in page 12, line 214-218. It should be as follow: Patients with or without pulmonary fibrosis had statistically significant differences in age, IL-6 levels, lymphocyte %, aspartate transaminase (AST), albumin, CRP/albumin ratio, platelet/lymphocyte ratio and some other indexes (Table 3), suggesting that these abnormal clinical indicators may be related to the pulmonary fibrosis. We have revised it and marked in blue in the revised version.

4.In addition, there are some errors in table 3 and table 4 because of the translation. We have revised it and marked in blue in the revised version.

All of the revisions are shown here. We would like to express our great appreciation to you and reviewers for comments on our paper.

Looking forward to hearing from you.

Best regards,

Shi-Ming Chen

Attachment

Submitted filename: Response to Reviewers OF PONE-D-20-31950 .docx

Click here for additional data file. (18.9KB, docx)

Decision Letter 2

Giordano Madeddu

9 Mar 2021

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT

PONE-D-20-31950R2

Dear Dr. Chen,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Giordano Madeddu

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: All comments bave been addressed. The paper is well written, the topic is original and the aim i clear. For the anice-mentionned reatina, The paper can ne published. I suggest pubblication of this paper.

Reviewer #3: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: Yes: Paola Crivelli

Reviewer #3: No

Acceptance letter

Giordano Madeddu

15 Mar 2021

PONE-D-20-31950R2

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT

Dear Dr. Chen:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Giordano Madeddu

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File

    (XLSX)

    Click here for additional data file. (70.8KB, xlsx)
    S2 File

    (XLSX)

    Click here for additional data file. (103.1KB, xlsx)
    S3 File

    (XLSX)

    Click here for additional data file. (95.4KB, xlsx)
    S4 File

    (XLSX)

    Click here for additional data file. (2.3MB, xlsx)
    Attachment

    Submitted filename: Response to Reviewers OF PONE-D-20-31950.docx

    Click here for additional data file. (108.2KB, docx)
    Attachment

    Submitted filename: Response to Reviewers OF PONE-D-20-31950 .docx

    Click here for additional data file. (18.9KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES