Abstract
Purpose
To compare lung ultrasound (US) and computed tomography (CT) in the assessment of pregnant women with COVID‐19.
Methods
Prospective study comprising 39 pregnant inpatients with COVID‐19 who underwent pulmonary assessment with CT and US with a maximum span of 48 h between the exams. The thorax was divided into 12 regions and assessed in terms of the following: the presence of B‐lines (>2), coalescent B‐lines, consolidation on US; presence of interlobular thickening, ground glass, consolidation on CT. The two methods were scored by adding up the scores from each thoracic region.
Results
A significant correlation was found between the scores obtained by the two methods (rICC = 0.946; p < 0.001). They were moderately in agreement concerning the frequency of altered pulmonary regions (weighted kappa = 0.551). In US, a score over 15, coalescent B‐lines, and consolidation were predictors of the need for oxygen, whereas the predictors in CT were a lung score over 16 and consolidation. The two methods, US (p < 0.001; AUC = 0.915) and CT (p < 0.001; AUC = 0.938), were fairly accurate in predicting the need for oxygen.
Conclusion
In pregnant women, lung US and chest CT are of similar accuracy in assessing lungs affected by COVID‐19 and can predict the need for oxygen.
Keywords: chest computed tomography, COVID‐19, lung ultrasound, pregnancy, SARS‐CoV‐2
Lung ultrasound may be satisfactorily incorporated into the obstetricians' clinical practice to evaluate pregnant women with COVID‐19. It is an alternative method which is more accessible, less expensive, faster to learn, which can be used at the bedside and repeatedly without running the risk of exposing the fetus to radiation.
1. INTRODUCTION
The SARS‐CoV‐2 may cause infections ranging widely from asymptomatic infections all the way to severe acute respiratory syndrome. The anatomical and physiological changes in the respiratory system and the immunosuppressive state during pregnancy render pregnant women more susceptible to respiratory infections. 1 , 2 Pregnant women with COVID‐19 symptoms have an increased rate of admittance to an intensive care unit (ICU) when compared to the general population, and they have an increased mortality rate when compared to pregnant women without the infection. 3 , 4 , 5
In patients with COVID‐19, chest computed tomography (CT) is the most used method and the first choice when quantifying the degree of pulmonary impairment and when providing clinical follow‐up. 6 However, ultrasound (US) may also be utilized in evaluating pulmonary impairment by COVID‐19, for the infection caused by SARS‐CoV‐2 has a predominantly peripheral distribution and thus is easily captured on US. 7 Besides, US is a more accessible diagnostic method than CT, a team can easily train to use it, it can be used in emergency conditions in an ICU at the bedside of patients with hemodynamic instability, and chiefly, it does not expose the fetus to radiation.
Under exceptional conditions within the context of the pandemic, the obstetrician may use US to evaluate not only fetal well‐being but also the lung conditions of pregnant women with COVID‐19. 8 An obstetrician is a health professional who uses US in their routine with pregnant women and who is used to operating the machine and its images. An obstetrician's lung assessment may influence the clinical management of pregnant women with COVID‐19 and it may be used as a good screening method for severe cases. 9 Therefore, this study aimed at comparing lung ultrasound with chest computed tomography to detect pulmonary changes in pregnant inpatients infected with SARS‐CoV‐2.
2. MATERIALS AND METHODS
This is a prospective study conducted at the tertiary referral hospital from June to September 2020. Pregnant inpatients suspected of having COVID‐19 were invited to participate. They were excluded from the study if (1) they were a case of unconfirmed SARS‐CoV2 infection; (2) they had not undergone a chest CT scan, and (3) the time span between the chest CT scan and the lung US was more than 48 h. All pregnant women included in this study had the diagnosis of COVID‐19 confirmed via real‐time fluorescence reverse‐transcription polymerase chain reaction (rRT‐PCR).
The study was approved by the institutional board review (CAAE: 30270820.3.0000.0068). After accepting to participate in the study and signing a free and informed consent statement, the participants underwent lung US.
2.1. Lung ultrasound
Lung ultrasound was carried out with Mindray ultrasound (Z5 model), SonoSite (M‐Turbo model), and GE Healthcare (Voluson 730 model) equipped with 3.5–5 MHz convex transducers. The lung US examinations were performed by 3 examiners experienced in the ultrasonographic technique after undergoing specific training for lung assessment. The exams were conducted with the patients lying comfortably in the following positions: sitting, dorsal decubitus, and lateral decubitus. Six regions of each hemithorax (two anterior, two lateral, and two posterior) were examined (Figure 1) as previously established, 10 , 11 , 12 with the transducer placed lengthwise and parallel to the ribs.
FIGURE 1.
Division of the pregnant woman's hemothorax
Lung score evaluation was based on the presence of ultrasound artifacts termed A‐lines, B‐lines, and consolidation. 10 , 13 A‐lines (Image 1) are hyperechoic horizontal lines parallel to the pleural line, which repeat themselves anteroposteriorly as a result of a pleural acoustic reverberation phenomenon. B‐lines (Image 2) are hyperechoic artifacts perpendicular to the pleural line, which run along the anteroposterior field under assessment. They are said to be pathological when 3 or more occur per the intercostal space under examination, and they may correspond to the thickening of interlobular or subpleural intralobular septa on CT. The coalescent B‐lines (Image 3) are a grouping of B‐lines more than 3 mm thick corresponding to the ground glass identified on CT. Consolidations (Image 4) appear as subpleural hypoechoic regions which discontinue the pleural echo. Pleural effusion is easily detected on ultrasound, for it is a seemingly anechoic area. The ultrasound findings were scored as follows: A‐lines (0 point), B‐lines over 2 (1 point), coalescent B‐lines (2 points), and presence of subpleural consolidation (3 points). Each quadrant was analyzed and scored according to its worst finding. The US score was obtained by adding up the scores of the 12 quadrants of each patient. 14 , 15 , 16
IMAGE 1.
Normal lung ultrasound. Axial view of the chest showing the pleural line identified by asterisks and the A‐lines pointed at by arrows: horizontal and symmetrically spaced hyperechoic lines below the pleural line
IMAGE 2.
Lung ultrasound with B‐lines. Axial view of the chest showing the pleural line identified by asterisks and the B‐lines pointed at by arrows: vertical hyperechoic lines that erase the A‐line and reach the end of the ultrasound screen
IMAGE 3.
Lung ultrasound with coalescent B‐lines. Axial view of the chest showing the pleural line identified by asterisks and the coalescent B‐lines pointed at by an arrow: union of hyperechoic vertical lines that erase line‐A and reach the end of the ultrasound screen producing a white lung area
IMAGE 4.
Lung ultrasound with consolidation. Axial view of the chest showing the pleural line identified by asterisks and the consolidation image pointed at by an arrow: an hypoechoic area with a superficial limit at the same level as the pleural line and an irregular lower limit
2.2. Chest tomography
Chest CT scan was performed in a 64‐multislice detector CT scanner (Brilliance—Koninklijke Phillips, Netherlands) with volumetric acquisition at maximum inspiration without intravenous contrast media. Images were acquired with a tube voltage of 120 kVp and with tube current modulation, based on international recommendations. 17 To reduce radiation exposure, strict collimation from the lung apices to diaphragm was applied and patients wore an abdominal lead shield during examination. Total median dose length product (DLP) was 307 mGy.cm (±94 mGy.cm). CT images were reconstructed with 1 mm of thickness with lung and mediastinal filter and assessed by a thoracic radiologist with 8 years of experience, in a dedicated workstation. The presence or absence of the following abnormalities were recorded: septal thickening, ground glass opacities, consolidation and pleural effusion. Abnormalities were defined according to a glossary of thoracic terms. 18 Pulmonary impairment was visually categorized as it was on US: each lung was divided into six regions (Figure 1) and classified as normal (equivalent to A‐lines on US) (Image 5), as having septal thickening (equivalent to B‐lines on US) (Image 6), as having ground glass opacities (equivalent to coalescent B‐lines on US) (Image 7), or as having consolidations (equivalent to consolidations of US) (Image 8). The score of each region ranged from 0 to 3 in accordance with the tomographic finding: score of 0, normal tomographic pattern; score of 1, presence of interlobular thickening; score of 2, presence of ground glass opacity (white lung); score of 3, presence of pulmonary consolidation. If there were two or more abnormalities in the same region, the score was given according to the most severe finding. The lung score was obtained by adding up the scores of the 12 regions. Presence or absence of pleural effusion was also assessed.
IMAGE 5.
Normal chest computed tomography. Axial view, lung filter. Normal lung
IMAGE 6.
Chest computed tomography with thickening of interlobular septa. Axial view, lung filter. Area with thickening of the interlobular septa, on lung middle lobe (arrow)
IMAGE 7.
Chest computed tomography with ground glass. Axial view, lung filter. Ground glass opacities, on posterior aspect of the lungs (arrows)
IMAGE 8.
Chest computed tomography with consolidation. Axial view, lung filter. Areas of consolidation with air bronchogram (arrows)
Cases were classified according to the need for supplemental oxygen during hospitalization.
2.3. Statistical analysis
Quantitative variables were summarized as mean and standard deviation or as median and minimum and maximum values. Qualitative variables were expressed as absolute frequencies (n) and percentages (%). To compare the US and the CT scores, the Kolmogorov–Smirnov test was used to identify the distribution of variables and the Student t test was applied to the analysis of normally distributed variables. For the agreement analysis of the US and the CT methods, the Kappa coefficient was used and calculations were made to determine raw agreement, sensitivity, and specificity values, as well as positive and negative predictive values. Agreement by the Kappa coefficient was classified based on the scale proposed by Landis and Koch 19 : slight (0.00–0.20), fair (0.21–0.40), moderate (0.41–0.60), substantial (0.61–0.80), and almost perfect (0.81–1.00).
The ROC (Receiver Operating Characteristic) curve was utilized to discriminate the US from the CT score values according to severity of symptoms. The prediction of the need for oxygen was computed with the univariate binary logistic regression analysis, the generalized estimating equation, and the odds ratio (OR) with its respective 95% confidence interval (95% CI).
A significance level of 5% was adopted and thus p values lower than 0.05 were deemed significant. The data were tabulated on an Excel spreadsheet and analyzed with the IBM SPSS version 20 software.
3. RESULTS
During the study period 135 pregnant women were hospitalized under the suspicion of COVID‐19, and 96 of them underwent lung US (Figure 2). Fifty‐seven cases were excluded for not having undergone a chest CT scan (n = 33), for testing negative for SARS‐CoV‐2 (n = 23), and for having a time span longer than 48 h between the lung US and the chest CT scan (n = 1). Therefore, this study included data from 39 patients. Considering this 39‐patient sample, sample power analysis was performed based on the paired sign test. Test power was 80% (1 − β), effect size was 0.5, and a 5% alpha for a two‐tailed hypothesis was adopted (GPower version 3.1.).
FIGURE 2.
Flowchart of patient screening
Table 1 displays the epidemiological and clinical characteristics of the study population. Most patients were multiparous, over half were obese, and 50% needed supplemental oxygen. Approximately 80% of the patients underwent lung US and a chest CT scan with a maximum 24‐h interval between them. Most pregnant woman (43%) had between 6 and 10 days from symptoms onset they underwent both chest CT and LUS.
TABLE 1.
Epidemiological and clinical characteristics of the study population
| Maternal characteristics | N = 39 |
|---|---|
| Age, years | 31 ± 7.41 |
| White | 24 (61.53) |
| Nulliparous | 8 (20.51) |
| Smoking | 5 (12.82) |
| Gestational age, weeks | 31.56 (5.84–40.84) |
| Comorbidities | |
| CAH | 11 (28.20) |
| HDP | 1 (2.56) |
| Asthma | 6 (15.38) |
| Cardiopathy | 3 (7.69) |
| Obesity | 21 (53.84) |
| DM | 2 (5.12) |
| GDM | 5 (12.82) |
| Symptoms | |
| Fever, n (%) | 19 (48.71) |
| Cough, n (%) | 32 (82.05) |
| Myalgia, n (%) | 21 (53.84) |
| Diarrhea/vomiting, n (%) | 1 (2.56) |
| Anosmia, n (%) | 15 (38.46) |
| Rhinorrhea, n (%) | 13 (33.33) |
| Dyspnea, n (%) | 24 (61.53) |
| Dysgeusia, n (%) | 14 (35.89) |
| Abdominal pain, n (%) | 2 (5.12) |
| Headache, n (%) | 16 (41.02) |
| Days of symptoms a | |
| 1–5 | 10 (25.64) |
| 6–10 | 17 (43.58) |
| ≥11 | 12 (30.76) |
| O2 needs | |
| Nasal catheter O2 | 10 (25.64) |
| Noninvasive ventilation | 3 (7.6) |
| Orotracheal intubation | 6 (15.38) |
| Time Span between US and CT | |
| <24 h | 17 (43.58) |
| 24 h | 14 (35.89) |
| 48 h | 8 (20.5) |
Note: Data presented as mean ± SD, number (%), and median (interquartile range).
Abbreviations: CAH, chronic arterial hypertension; DM, diabetes mellitus; HDP, hypertensive disease of pregnancy; GDM, gestational diabetes mellitus.
Days of symptoms when patients submitted to US and CT.
Table 2 shows quadrant frequency with the lung abnormalities detected by each method and the results from comparing the methods. A moderate degree of agreement between the lung US and the chest CT scan was observed (weighted Kappa = 0.551). When comparing the data in terms of each lung abnormality, the Kappa coefficient varied from slight to moderate; the strongest agreement was that of the combination of abnormalities, that is, composite findings (agreement = 79.3%; Kappa = 0.583; p < 0.001). High specificity and high negative predictive value of US was found in terms of B‐lines over 2, coalescent B‐lines, and consolidation. Sensitivity and the positive predictive value of US were higher when associated with abnormal findings (composite findings), 90.6% and 74.6% respectively.
TABLE 2.
Comparison of the frequency of quadrants with lung abnormalities identified on lung ultrasound and on chest computed tomography in pregnant women with COVID‐19 (N = 468 quadrants)
| Lung abnormalities | CT US | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Yes | No | Concordance (%) | KAPPA | p | S (%) | E (%) | PPV (%) | NPV (%) | ||
| B‐line (>2)—n (%)/interlobular septal thickening | Yes | 2 (0.4) | 49 (10.5) | 87.2 | 0.019 | 0.598 | 15.4 | 89.2 | 3.9 | 97.4 |
| No | 11 (2.4) | 406 (86.8) | ||||||||
| Coalescent B‐line/ground glass—n (%) | Yes | 57 (12.2) | 60 (12.8) | 74.6 | 0.320 | <0.001 | 49.1 | 83 | 48.7 | 83.2 |
| No | 59 (12.6) | 292 (62.4) | ||||||||
| Consolidation—n (%) | Yes | 67 (14.3) | 56 (12) | 78.6 | 0.431 | <0.001 | 60.4 | 84.3 | 54.5 | 87.2 |
| No | 44 (9.4) | 301 (64.3) | ||||||||
| Composite findings a —n (%) | Yes | 217 (46.4) | 74 (15.8) | 79.3 | 0.583 | <0.001 | 90.4 | 67.5 | 74.6 | 87 |
| No | 23 (4.9) | 154 (32.9) | ||||||||
| Pleural effusion—n (%) | Yes | 4 (10.3) | 3 (7.7) | 84.6 | 0.478 | 0.003 | 57.1 | 90.6 | 57.1 | 90.6 |
| No | 3 (7.7) | 29 (74.4) | ||||||||
| Weighted Kappa | 59.82 | 0.551 | <0.001 | |||||||
Abbreviations: CT, computed tomography; E, specificity; NPV, negative predictive value; PPV, positive predictive value; S, sensitivity; US, ultrasound.
Includes the presence of any of the following abnormalities: B‐line >2, coalescent B‐line/ground glass, consolidation.
A positive and significant correlation was found between the lung US and the chest CT scan scores (Figure 3, rICC = 0.946; p < 0.001).
FIGURE 3.
Interclass correlation between the lung ultrasound (US) score and the chest computed tomography (CT) scan score of pregnant inpatients with COVID‐19
Table 3 shows the US and CT predictions of the need of pregnant women with COVID‐19 for supplemental oxygen use. In lung US the abnormalities predictive of oxygen use were the lung score, coalescent B‐lines, and subpleural consolidation. The predictors of oxygen use on the chest CT scan were the lung score and the presence of lung consolidation.
TABLE 3.
Prediction of the need of pregnant inpatients with COVID‐19 for oxygen use based on lung ultrasound and chest computed tomography according to lung score and lung abnormalities
| Lung abnormalities | Lung assessment method | O2 not needed (n = 21) | O2 needed (n = 18) | OR | CI (95%) | p |
|---|---|---|---|---|---|---|
| Lung score—mean ± SD a | US | 9.38 (7.9) | 25.38 (7.1) | 1.24 | 1.10–1.41 | 0.001 |
| CT | 7.85 (6.9) | 22.94 (6.9) | 1.32 | 1.11–1.56 | 0.001 | |
| B‐lines >2—n (%) b | US | 31 (12.3) | 20 (9.3) | 0.727 | 0.31–1.71 | 0.463 |
| CT | 3 (1.2) | 10 (4.6) | 4.02 | 0.76–21.3 | 0.101 | |
| Coalescent B‐lines/ground glass—n (%) b | US | 41 (16.3) | 76 (35.2) | 2.79 | 1,09–7.14 | 0.032 |
| CT | 51 (20.3) | 65 (30.1) | 1.69 | 0.73–3.95 | 0.220 | |
| Consolidation—n (%) b | US | 28 (11.1) | 95 (44) | 6.28 | 3.19–12.37 | <0.001 |
| CT | 20 (7.9) | 91 (42.1) | 8.44 | 4.31–16.54 | <0.001 |
Univariate binary logistic regression.
Generalized estimating equations.
The ROC curves (Figure 4) illustrate the performance assessment of the US and the CT lung scores according to the oxygen use needed by the pregnant women with COVID‐19. The two methods were significantly accurate in determining the need for O2 given an area under the curve of 0.915 and 0.938 respectively for US and CT. A lung score over 15 on US and over 16 on CT were predictors of the need for oxygen, and the sensitivities and specificities were 94.4%, 89.9%, 88.9%, and 90.5%, respectively.
FIGURE 4.
Lung score performance on lung ultrasound (>15) and on chest tomography (>16) in predicting the need of pregnant inpatients with COVID‐19 for supplemental oxygen use
4. DISCUSSION
4.1. Main findings
The findings of the present study show there is an optimal correlation between the US and the CT methods in the assessment of the pregnant women's lung abnormalities related to COVID‐19. The best correlation between the methods was evidenced by the lung score. Furthermore, the two methods were remarkably accurate in predicting the need for oxygen. Hence, lung ultrasound may be utilized in the assessment and follow‐up of pregnant women with COVID‐19.
4.2. Comparison with results of previous studies
A chest CT scan is not contraindicated in pregnancy and is regarded as the gold standard for evaluating viral pneumonia caused by SARS‐CoV‐2. Lung US, as it turned out, is also an accurate imaging method for detecting peripheral pulmonary and pleural abnormalities even during pregnancy. 7 , 20
Results similar to those obtained in the present study were reported by previous studies conducted with nonpregnant women. These studies also found an optimal correlation between the pulmonary findings using ultrasound and those using computed tomography. 21 , 22 , 23 Our results show significant agreement between the presence of coalescent B‐lines on US and ground glass on CT and the presence of consolidation in both methods (p < 0.001). The latter was also observed in the Lopes et al. study. 24
The ROC curve showed an excellent prediction of the lung score on US for determining the need for oxygen (AUC = 0.91). We did not find any studies that used the lung US score to predict the need for O2; however, Zieleskiewicz et al. observed the lung score performance (AUC = 0.92) to predict the severity of pneumonia as we did. 15 Therefore, such findings show that lung US may be employed to predict the worsening of pulmonary abnormalities in pregnant and nonpregnant populations.
Deng et al. analyzed the chest CT scan using the lung score, which is routinely done with US, similar we performed in our study. Both studies showed an excellent interclass correlation. Additionally, the scores produced by US and by CT performed in similar fashion in predicting the need for oxygen in our results, and the lung score >15 by US predicts the presence of severe pneumonia by chest CT in Chinese study. 25
4.3. Implications for clinical practice
Our findings demonstrate that lung ultrasound may be utilized in the follow‐up of pregnant women with COVID‐19 given its proven good level of performance. Currently, gynecologists and obstetricians are being highly encouraged to evaluate not only fetal well‐being but also pulmonary impairment due to COVID‐19 by means of ultrasound. In the last year, practical guides and educational articles have been published to teach the health professionals to perform a lung ultrasound assessment. 8 , 16 , 26
A few advantages of ultrasound over CT in lung assessment of pregnant women with COVID‐19 include the following: US may be performed concomitantly with fetal evaluation; US may be performed with the patient in her bed without having to move her, thus reducing exposure of the health professionals to a contagious disease, and in the severe cases, it may be performed in the ICU; the exam may be performed repeatedly in cases of maternal clinical aggravation, without exposing the fetus to radiation.
In agreement with other authors, 9 , 20 we believe that lung assessment of pregnant women with COVID‐19 by means of US may improve patient care by modifying disease management and treatment. For example, identification of subpleural consolidation on US is indicative of the need for introducing antibiotic therapy to treat bacterial coinfection; still, in cases of the mother's clinical aggravation with a worsening of the lung score on US, it may be possible to introduce corticosteroid therapy in order to reduce the pulmonary inflammatory response.
Another clinical implication of the findings of the present study is that the lung score—over 15 on lung US and over 16 on a chest CT scan—can be used to predict the need for oxygen during hospitalization, thus selecting the pregnant women in need of more careful monitoring.
4.4. Strengths and limitations
The strong points of this study include a prospective evaluation of pregnant women carried out in a single tertiary center for high‐risk pregnant women with COVID‐19. Also, the short time span between the imaging exams, 80% of which were conducted in 24‐h intervals between US and CT, allowed assessment with little or no interference from changes in lung images occasioned by the development of lung impairments.
The reproducibility of a lung assessment by US was not evaluated given that this imaging method is examiner dependent; nevertheless, it might still be considered a limitation of this study. However, a previous study involving obstetricians with different levels of experience with US, as well as radiologists, showed there was good interobserver correlation (Krippendorff's œ = 0.856 for images; œ = 0.785 for videoclips). 27 Moreover, a recent study demonstrated that the training of obstetricians for lung US assessment was highly effective. 8 Our study involved obstetricians with extensive experience in US who were given adequate training to assess COVID‐19 lung abnormalities, and a strong correlation was found between the findings on US and on CT. Consequently, and in accordance with the aforementioned studies, 8 , 27 we believe that the lack of assessment of the reproducibility of the US method had no impact on the analysis of our results.
5. CONCLUSIONS
This study has shown there is a significant correlation between lung US and a chest CT scan, primarily between the lung scores obtained by either method, in the case of pregnant women hospitalized with COVID‐19. The US accuracy in predicting the need for O2 was as satisfactory as the tomographic assessment; the over 15 score, the coalescent B‐lines, and the presence of subpleural consolidation were the ultrasound predictors.
FUNDING INFORMATION
This study was supported by CAPES (88881.504727/2020‐01) and the HCcomvida (02.25). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
CONFLICT OF INTEREST
The author declares that there is no conflict of interest.
ETHICS STATEMENT
The study was approved by the institutional board review (CAAE: 30270820.3.0000.0068).
ACKNOWLEDGMENTS
We acknowledge Mr. Alan Garcia da Silva and Mrs. Lucinda Cristina Pereira for their information technology and administrative support in the project development.
Biancolin SE, dos Santos Fernandes H, Sawamura MVY, et al. Lung ultrasound versus chest computed tomography for pregnant inpatients with COVID‐19. J Clin Ultrasound. 2022;1‐10. doi: 10.1002/jcu.23286
Funding information CAPES, Grant/Award Number: 88881.504727/2020‐01; HCcomvida, Grant/Award Number: 02.25
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.