Lung Ultrasound in the Diagnosis of COVID-19 Pneumonia: Not Always and Not Only What Is COVID-19 "Glitters"

COVID-19 Lung Ultrasound Scores and Lessons from the Pandemic: A Narrative Review

The WHO recently declared that COVID-19 no longer constitutes a public health emergency of international concern; however, lessons learned through the pandemic should not be left behind. Lung ultrasound was largely utilized as a diagnostic tool thanks to its feasibility, easy application, and the possibility to reduce the source of infection for health personnel. Lung ultrasound scores consist of grading systems used to guide diagnosis and medical decisions, owning a good prognostic value. In the emergency context of the pandemic, several lung ultrasound scores emerged either as new scores or as modifications of pre-existing ones. Our aim is to clarify the key aspects of lung ultrasound and lung ultrasound scores to standardize their clinical use in a non-pandemic context. The authors searched on PubMed for articles related to "COVID-19", "ultrasound", and "Score" until 5 May 2023; other keywords were "thoracic", "lung", "echography", and "diaphragm". A narrative summary of the results was made. Lung ultrasound scores are demonstrated to be an important tool for triage, prediction of severity, and aid in medical decisions. Ultimately, the existence of numerous scores leads to a lack of clarity, confusion, and an absence of standardization.

Thoracic ultrasound combined with low-dose computed tomography may represent useful screening strategy in highly exposed population in the industrial city of Taranto (Italy)

Objectives

We validated a screening protocol in which thoracic ultrasound (TUS) acts as a first-line complementary imaging technique in selecting patients which may deserve a second-line low-dose high resolution computed tomography (HRCT) scan among a population of asymptomatic high-risk subjects for interstitial lung abnormalities (ILA) and lung cancer. Due to heavy environmental pollution burden, the district Tamburi of Taranto has been chosen as "case study" for this purpose.

Methods

From July 2018 to October 2020, 677 patients aged between 45 and 65 year and who had been living in the Tamburi district of Taranto for at least 10 years were included in the study. After demographic, clinical and risk factor exposition data were collected, each participant underwent a complete TUS examination. These subjects were then asked to know if they agreed to perform a second-level examination by low-dose HRCT scan.

Results

On a total of 167 subjects (24.7%) who agreed to undergo a second-level HRCT, 85 patients (50.9%) actually showed pleuro-pulmonary abnormalities. Interstitial abnormalities were detected in a total of 36 patients on HRCT scan. In particular, 34 participants presented subpleural ILAs, that were classified in the fibrotic subtype in 7 cases. The remaining 2 patients showed non-subpleural interstitial abnormalities. Subpleural nodules were observed in 46 patients. TUS showed an overall diagnostic accuracy of 88.6% in detecting pleuro-pulmonary abnormalities in comparison with HRCT scan, with a sensitivity of 95.3%, a specificity of 81.7%, a positive predictive value of 84.4% and a negative predictive value of 94.4%. The matched evaluation of specific pulmonary abnormalities on HRTC scan (i.e., interstitial abnormalities or pulmonary nodules) with determinate sonographic findings revealed a reduction in both TUS sensibility and specificity. Focusing TUS evaluation on the assessment of interstitial abnormalities, a thickened pleural line showed a sensitivity of 63.9% and a specificity of 69.5%, hypoechoic striae showed a sensitivity of 38.9% and a specificity of 90.1% and subpleural nodules showed a sensitivity of 58.3% and a specificity of 77.1%. Regarding to the assessment of subpleural nodules, TUS showed a sensitivity of 60.9% and a specificity of 81.0%. However, the combined employment of TUS examination and HRCT scans allowed to identify 34 patients with early subpleural ILA and to detect three suspicious pulmonary nodules (of which two were intraparenchymal and one was a large subpleural mass), which revealed to be lung cancers on further investigations.

Conclusion

A first-line TUS examination might aid the identification of subjects highly exposed to environmental pollution, who could benefit of a second-line low-dose HRCT scan to find early interstitial lung diseases as well as lung cancer.

Protocol registration code

PLEURO-SCREENING-V1.0_15 Feb, 17.

Reliability and clinical correlations of semi-quantitative lung ultrasound on BLUE points in COVID-19 mechanically ventilated patients: The 'BLUE-LUSS'-A feasibility clinical study

INTRODUCTION

Bedside lung ultrasound has gained a key role in each segment of the treatment chain during the COVID-19 pandemic. During the diagnostic assessment of the critically ill patients in ICUs, it is highly important to maximize the amount and quality of gathered information while minimizing unnecessary interventions (e.g. moving/rotating the patient). Another major factor is to reduce the risk of infection and the workload of the staff.

OBJECTIVES

To serve these significant issues we constructed a feasibility study, in which we used a single-operator technique without moving the patient, only assessing the easily achievable lung regions at conventional BLUE points. We hypothesized that calculating this 'BLUE lung ultrasound score' (BLUE-LUSS) is a reasonable clinical tool. Furthermore, we used both longitudinal and transverse scans to measure their reliability and assessed the interobserver variability as well.

METHODS

University Intensive Care Unit based, single-center, prospective, observational study was performed on 24 consecutive SARS-CoV2 RT-PCR positive, mechanically ventilated critically ill patients. Altogether 400 loops were recorded, rated and assessed off-line by 4 independent intensive care specialists (each 7+ years of LUS experience).

RESULTS

Intraclass correlation values indicated good reliability for transversal and longitudinal qLUSS scores, while we detected excellent interrater agreement of both cLUSS calculation methods. All of our LUS scores correlated inversely and significantly to the P/F values. Best correlation was achieved in the case of longitudinal qLUSS (r = -0.55, p = 0.0119).

CONCLUSION

Summarized score of BLUE-LUSS can be an important, easy-to-perform adjunct tool for assessing and quantifying lung pathology in critically ill ventilated patients at bedside, especially for the P/F ratio. The best agreement for the P/F ratio can be achieved with the longitudinal scans. Regarding these findings, assessing BLUE-points can be extended with the BLUE-LUSS for daily routine using both transverse and longitudinal views.

Lung Ultrasound Findings in Healthy Children and in Those Who Had Recent, Not Severe COVID-19 Infection

Background: Lung ultrasound (LUS) is gaining consensus as a non-invasive diagnostic imaging method for the evaluation of pulmonary disease in children. Aim: To clarify what type of artifacts (e.g., B-lines, pleural irregularity) can be defined normal LUS findings in children and to evaluate the differences in children who did not experience COVID-19 and in those with recent, not severe, previous COVID-19. Methods: LUS was performed according to standardized protocols. Different patterns of normality were defined: pattern 1: no plural irregularity and no B-lines; pattern 2: only mild basal posterior plural irregularity and no B-lines; pattern 3: mild posterior basal/para-spine/apical pleural irregularity and no B-lines; pattern 4: like pattern 3 plus rare B-lines; pattern 5: mild, diffuse short subpleural vertical artifacts and rare B-lines; pattern 6: mild, diffuse short subpleural vertical artifacts and limited B-lines; pattern 7: like pattern 6 plus minimal subpleural atelectasis. Coalescent B-lines, consolidations, or effusion were considered pathological. Results: Overall, 459 healthy children were prospectively recruited (mean age 10.564 ± 3.839 years). Children were divided into two groups: group 1 (n = 336), those who had not had COVID-19 infection, and group 2 (n = 123), those who experienced COVID-19 infection. Children with previous COVID-19 had higher values of LUS score than those who had not (p = 0.0002). Children with asymptomatic COVID-19 had similar LUS score as those who did not have infections (p > 0.05), while those who had symptoms showed higher LUS score than those who had not shown symptoms (p = 0.0228). Conclusions: We report the pattern of normality for LUS examination in children. We also showed that otherwise healthy children who recovered from COVID-19 and even those who were mildly symptomatic had more “physiological” artifacts at LUS examinations.

WEENet: An Intelligent System for Diagnosing COVID-19 and Lung Cancer in IoMT Environments

The coronavirus disease 2019 (COVID-19) pandemic has caused a major outbreak around the world with severe impact on health, human lives, and economy globally. One of the crucial steps in fighting COVID-19 is the ability to detect infected patients at early stages and put them under special care. Detecting COVID-19 from radiography images using computational medical imaging method is one of the fastest ways to diagnose the patients. However, early detection with significant results is a major challenge, given the limited available medical imaging data and conflicting performance metrics. Therefore, this work aims to develop a novel deep learning-based computationally efficient medical imaging framework for effective modeling and early diagnosis of COVID-19 from chest x-ray and computed tomography images. The proposed work presents "WEENet" by exploiting efficient convolutional neural network to extract high-level features, followed by classification mechanisms for COVID-19 diagnosis in medical image data. The performance of our method is evaluated on three benchmark medical chest x-ray and computed tomography image datasets using eight evaluation metrics including a novel strategy of cross-corpse evaluation as well as robustness evaluation, and the results are surpassing state-of-the-art methods. The outcome of this work can assist the epidemiologists and healthcare authorities in analyzing the infected medical chest x-ray and computed tomography images, management of the COVID-19 pandemic, bridging the early diagnosis, and treatment gap for Internet of Medical Things environments.

Inter-Observer Agreement between Low-Dose and Standard-Dose CT with Soft and Sharp Convolution Kernels in COVID-19 Pneumonia

Computed tomography (CT) has been an essential diagnostic tool during the COVID-19 pandemic. The study aimed to develop an optimal CT protocol in terms of safety and reliability. For this, we assessed the inter-observer agreement between CT and low-dose CT (LDCT) with soft and sharp kernels using a semi-quantitative severity scale in a prospective study (Moscow, Russia). Two consecutive scans with CT and LDCT were performed in a single visit. Reading was performed by ten radiologists with 3–25 years’ experience. The study included 230 patients, and statistical analysis showed LDCT with a sharp kernel as the most reliable protocol (percentage agreement 74.35 ± 43.77%), but its advantage was marginal. There was no significant correlation between radiologists’ experience and average percentage agreement for all four evaluated protocols. Regarding the radiation exposure, CTDI_vol was 3.6 ± 0.64 times lower for LDCT. In conclusion, CT and LDCT with soft and sharp reconstructions are equally reliable for COVID-19 reporting using the “CT 0-4” scale. The LDCT protocol allows for a significant decrease in radiation exposure but may be restricted by body mass index.