Lung Ultrasound and Sonographic Subpleural Consolidation in COVID-19 Pneumonia Correlate with Disease Severity. Crit Care Res Pract. 2021;2021:6695033. [PMID: 33425386 PMCID: PMC7780695 DOI: 10.1155/2021/6695033]

Sensitivity of Lung Point-of-Care Ultrasound (POCUS) to Predict Oxygen Requirements in Emerging Viral Infections

OBJECTIVES

The prognostic characteristics of lung point-of-care ultrasound (L-POCUS) to predict respiratory decompensation in patients with emerging infections remains unstudied. Our objective was to examine whether scored lung ultrasounds predict hypoxia among a nonhypoxic, ambulatory population of patients with COVID-19.

METHODS

This was a diagnostic case-control study. Three academic emergency departments across the United States collected a convenience sample of nonhypoxic subjects with COVID-19, scored subjects' hemithorax at 7 locations using lung ultrasound, and followed outcomes for 40 days. We defined cases as hypoxia (≤91% by pulse oxygenation) from 2 hours after index presentation to day 40. Follow-up was by telephone plus home pulse oximeter and by chart review. We conducted a logistic regression to test the association between L-POCUS scores and hypoxia. To evaluate lung ultrasound score prediction of a hypoxic event, we calculated sensitivity and specificity at optimal cut off scores and report receiver operating characteristic curve and area under the curve.

RESULTS

We enrolled 163 subjects but excluded 15 (3 duplicate entries; 12 lost to follow up). Median age was 41 years (interquartile range [IQR] 31-56); 83 (56%) were female, and median body mass index was 29 (IQR 25-35). We classified 47 of 148 as hypoxic cases (32%, 95% confidence interval [CI]: 25-40), leaving 101 controls. L-POCUS scores associated with hypoxia by logistic regression (odds ratio = 1.05, 95% CI: 1.02-1.08), with a 5% increase in odds of hypoxia for each 1-unit increase in L-POCUS score. The optimal cut-off score was 15 (sensitivity, 0.60; specificity, 0.73) and the area under the curve was 0·66 (95% CI 0·58-0·75). The correctly classified proportion was 69% (95% CI: 61-76).

CONCLUSIONS

Among nonhypoxic COVID-19 patients, higher L-POCUS rubric scores were associated with hypoxia but no scoring threshold strongly predicts hypoxia at 40 days.

Deep-learning generated B-line score mirrors clinical progression of disease for patients with heart failure

BACKGROUND

Ultrasound can detect fluid in the alveolar and interstitial spaces of the lung using the presence of artifacts known as B-lines. The aim of this study was to determine whether a deep learning algorithm generated B-line severity score correlated with pulmonary congestion and disease severity based on clinical assessment (as identified by composite congestion score and Rothman index) and to evaluate changes in the score with treatment. Patients suspected of congestive heart failure underwent daily ultrasonography. Eight lung zones (right and left anterior/lateral and superior/inferior) were scanned using a tablet ultrasound system with a phased-array probe. Mixed effects modeling explored the association between average B-line score and the composite congestion score, and average B-line score and Rothman index, respectively. Covariates tested included patient and exam level data (sex, age, presence of selected comorbidities, baseline sodium and hemoglobin, creatinine, vital signs, oxygen delivery amount and delivery method, diuretic dose).

RESULTS

Analysis included 110 unique subjects (3379 clips). B-line severity score was significantly associated with the composite congestion score, with a coefficient of 0.7 (95% CI 0.1-1.2 p = 0.02), but was not significantly associated with the Rothman index.

CONCLUSIONS

Use of this technology may allow clinicians with limited ultrasound experience to determine an objective measure of B-line burden.

The Comparison of Ultrasound and Tomographic Images of Lung Involvement in Critically Ill Patients With COVID-19 Pneumonia: A Prospective Observational Study

Introduction Computed tomography (CT) has a high sensitivity for diagnosing COVID-19 pneumonia in critically ill patients, but it has significant limitations. Lung ultrasonography (LUS) is an imaging method increasingly used in intensive care units. Our primary aim is to evaluate the relationship between LUS and CT images by scoring a critically ill patient who was previously diagnosed with COVID-19 pneumonia and underwent CT, as well as to determine their relationship with the patient's oxygenation. Methods This was a single-center, prospective observational study. The study included COVID-19 patients (positive reverse transcription polymerase chain reaction, RT-PCR) who were admitted to the intensive care unit between June 2020 and December 2020, whose oxygen saturation (SpO2) was below 92%, and who underwent a chest tomography scan within the last 12 hours. CT findings were scored by the radiologist using the COVID-19 Reporting and Data System (CO-RADS). The intensivist evaluated 12 regions to determine the LUS score. The ratio of the partial pressure of oxygen in the arterial blood to the inspiratory oxygen concentration (PaO2/FiO2) was used to assess the patient's oxygenation. Results The study included 30 patients and found a weak correlation (ICC = 0.45, 95% CI = 0.25-0.65, p < 0.05) between total scores obtained from LUS and CT scans. The correlation between the total LUS score and oxygenation (r = -0.514, p = 0.004) was stronger than that between the CT score and oxygenation (r = -0.400, p = 0.028). The most common sonographic findings were abnormalities in the pleural line, white lung, and subpleural consolidation. On the other hand, the CT images revealed dense ground-glass opacities and consolidation patterns classified as CO-RADS 5. Conclusion A weak correlation was found between LUS and CT scores in critically ill COVID-19 pneumonia patients. Also, as both scores increased, oxygenation was detected to be impaired, and such a correlation is more evident with the LUS score.

Detection of COVID-19 features in lung ultrasound images using deep neural networks

BACKGROUND

Deep neural networks (DNNs) to detect COVID-19 features in lung ultrasound B-mode images have primarily relied on either in vivo or simulated images as training data. However, in vivo images suffer from limited access to required manual labeling of thousands of training image examples, and simulated images can suffer from poor generalizability to in vivo images due to domain differences. We address these limitations and identify the best training strategy.

METHODS

We investigated in vivo COVID-19 feature detection with DNNs trained on our carefully simulated datasets (40,000 images), publicly available in vivo datasets (174 images), in vivo datasets curated by our team (958 images), and a combination of simulated and internal or external in vivo datasets. Seven DNN training strategies were tested on in vivo B-mode images from COVID-19 patients.

RESULTS

Here, we show that Dice similarity coefficients (DSCs) between ground truth and DNN predictions are maximized when simulated data are mixed with external in vivo data and tested on internal in vivo data (i.e., 0.482 ± 0.211), compared with using only simulated B-mode image training data (i.e., 0.464 ± 0.230) or only external in vivo B-mode training data (i.e., 0.407 ± 0.177). Additional maximization is achieved when a separate subset of the internal in vivo B-mode images are included in the training dataset, with the greatest maximization of DSC (and minimization of required training time, or epochs) obtained after mixing simulated data with internal and external in vivo data during training, then testing on the held-out subset of the internal in vivo dataset (i.e., 0.735 ± 0.187).

CONCLUSIONS

DNNs trained with simulated and in vivo data are promising alternatives to training with only real or only simulated data when segmenting in vivo COVID-19 lung ultrasound features.

Lung Ultrasound Improves Outcome Prediction over Clinical Judgment in COVID-19 Patients Evaluated in the Emergency Department

In the Emergency Department (ED), the decision to hospitalize or discharge COVID-19 patients is challenging. We assessed the utility of lung ultrasound (LUS), alone or in association with a clinical rule/score. This was a multicenter observational prospective study involving six EDs (NCT046291831). From October 2020 to January 2021, COVID-19 outpatients discharged from the ED based on clinical judgment were subjected to LUS and followed-up at 30 days. The primary clinical outcome was a composite of hospitalization or death. Within 393 COVID-19 patients, 35 (8.9%) reached the primary outcome. For outcome prognostication, LUS had a C-index of 0.76 (95%CI 0.68−0.84) and showed good performance and calibration. LUS-based classification provided significant differences in Kaplan−Meier curves, with a positive LUS leading to a hazard ratio of 4.33 (95%CI 1.95−9.61) for the primary outcome. The sensitivity and specificity of LUS for primary outcome occurrence were 74.3% (95%CI 59.8−88.8) and 74% (95%CI 69.5−78.6), respectively. The integration of LUS with a clinical score further increased sensitivity. In patients with a negative LUS, the primary outcome occurred in nine (3.3%) patients (p < 0.001 vs. unselected). The efficiency for rule-out was 69.7%. In unvaccinated ED patients with COVID-19, LUS improves prognostic stratification over clinical judgment alone and may support standardized disposition decisions.

Ultrasound findings of lung ultrasonography in COVID-19: A systematic review

PURPOSE

To identify the defining lung ultrasound (LUS) findings of COVID-19, and establish its association to the initial severity of the disease and prognostic outcomes.

METHOD

Systematic review was conducted according to the PRISMA guidelines. We queried PubMed, Embase, Web of Science, Cochrane Database and Scopus using the terms ((coronavirus) OR (covid-19) OR (sars AND cov AND 2) OR (2019-nCoV)) AND (("lung ultrasound") OR (LUS)), from 31st of December 2019 to 31st of January 2021. PCR-confirmed cases of SARS-CoV-2 infection, obtained from original studies with at least 10 participants 18 years old or older, were included. Risk of bias and applicability was evaluated with QUADAS-2.

RESULTS

We found 1333 articles, from which 66 articles were included, with a pooled population of 4687 patients. The most examined findings were at least 3 B-lines, confluent B-lines, subpleural consolidation, pleural effusion and bilateral or unilateral distribution. B-lines, its confluent presentation and pleural abnormalities are the most frequent findings. LUS score was higher in intensive care unit (ICU) patients and emergency department (ED), and it was associated with a higher risk of developing unfavorable outcomes (death, ICU admission or need for mechanical ventilation). LUS findings and/or the LUS score had a good negative predictive value in the diagnosis of COVID-19 compared to RT-PCR.

CONCLUSIONS

The most frequent ultrasound findings of COVID-19 are B-lines and pleural abnormalities. High LUS score is associated with developing unfavorable outcomes. The inclusion of pleural effusion in the LUS score and the standardisation of the imaging protocol in COVID-19 LUS remains to be defined.

Right ventricle early inflow-outflow index may inform about the severity of pneumonia in patients with COVID-19

BACKGROUND

Echocardiography is generally used in our daily practice to detect cardiovascular complications in COVID-19 patients and for etiological research in the case of worsened clinical status. Many echocardiographic parameters have been the subject of investigation in previous studies on COVID-19. Recently, the right ventricle early inflow-outflow (RVEIO) index has been identified as a possible and indirect marker of the severity of tricuspid regurgitation and right ventricular dysfunction in pulmonary embolism. In this study, we aimed to investigate the relationship between the severity of pneumonia in COVID-19 patients and the RVEIO index.

METHODS

A total of 54 patients diagnosed with COVID-19 pneumonia were enrolled in this study. Our study population was separated into two groups as severe pneumonia and nonsevere pneumonia based on computed tomography imaging.

RESULTS

Saturation O₂ , C-reactive protein, D-dimer, deceleration time, tricuspid annular plane systolic excursion, tricuspid lateral annular systolic velocity, and RVEIO index values were found to be significantly different between severe and nonsevere pneumonia groups. The result of the multivariate logistic regression test revealed that saturation O2, D-dimer, Sm, and RVEIO index were the independent predictive parameters for severe pneumonia. Receiver operating characteristic curve analysis demonstrated that RVEIO index >4.2 predicted severe pneumonia with 77% sensitivity and 79% specificity.

CONCLUSION

The RVEIO index can be used as a bedside, noninvasive, easily accessible, and useful marker to identify the COVID-19 patient group with widespread pneumonia and, therefore high risk of complications, morbidity, and mortality.

One-day seminar for residents for implementing abdominal pocket-sized ultrasound

Despite its proven high utility, integration of pocked-sized portable ultrasound (US) into internal medicine residency training remains inconsistent. For 10 years, we have held a 1-d seminar biannually, consisting of lecture (half-day) and hands-on training (half-day) on pocket-sized US of the abdomen and lungs. The lecture consists of training on US physics and clinical applications of pocket-sized US, followed by a lecture covering the basic anatomy of the abdomen and lungs and introducing the systemic scanning method. Given the simple structure of pocket-sized US devices, understanding the basic physics is sufficient yet necessary to operate the pocket-sized US device. It is important to understand the selection of probes, adjustment of B mode gain, adjustment of color gain, and acoustic impedance. Basic comprehension may have a significant positive impact on the overall utilization of pocket-sized US devices. The easiest and most reliable way to observe the whole abdomen and lungs is a combination of transverse, sagittal, and oblique scanning, pursuing the main vascular system from the center to the periphery of the organ in the abdomen and systemic scanning of the pleura. There is usually a marked change in knowledge and attitudes among the program participants, although skill gaps remain among them. We discuss the limitations and problems to this education system as well.

M-BLUE protocol for coronavirus disease-19 (COVID-19) patients: interobserver variability and correlation with disease severity

AIM

To retrospectively evaluate the interobserver variability of intensive care unit (ICU) practitioners and radiologists who used the M-BLUE (modified bedside lung ultrasound in emergency) protocol to assess coronavirus disease-19 (COVID-19) patients, and to determine the correlation between total M-BLUE protocol score and three different scoring systems reflecting disease severity.

MATERIALS AND METHODS

Institutional review board approval was obtained and informed consent was not required. Ninety-six lung ultrasonography (LUS) examinations were performed using the M-BLUE protocol in 79 consecutive COVID-19 patients. Two ICU practitioners and three radiologists reviewed video clips of the LUS of eight different regions in each lung retrospectively. Each observer, who was blind to the patient information, described each clip with M-BLUE terminology and assigned a corresponding score. Interobserver variability was assessed using intraclass correlation coefficient. Spearman's correlation coefficient analysis (R-value) was used to assess the correlation between the total score of the eight video clips and disease severity.

RESULTS

For different LUS signs, fair to good agreement was obtained (ICC = 0.601, 0.339, 0.334, and 0.557 for 0-3 points respectively). The overall interobserver variability was good for both the five different readers and consensus opinions (ICC = 0.618 and 0.607, respectively). There were good correlations between total LUS score and scores from three systems reflecting disease severity (R=0.394-0.660, p<0.01).

CONCLUSION

In conclusion, interobserver agreement for different signs and total scores in LUS is good and justifies its use in patients with COVID-19. The total scores of LUS are useful to indicate disease severity.