New International Guidelines and Consensus on the Use of Lung Ultrasound

The prognostic role of lung ultrasound in hospitalised patients with COVID-19. Correlation with chest CT findings and clinical markers of severity

BACKGROUND

The use of lung ultrasound (LUS) has recently become vital in the diagnosis and prognosis of various respiratory diseases. Its role in COVID-19 requires further investigation.

RESEARCH DESIGN AND METHODS

Twenty-five consecutive, non-ICU hospitalized COVID-19 patients were included. LUS was performed on admission and sequentially every 3 days at 8 points in the chest. Based on the LUS findings a score was designed. Logarithmic regression models and ROC curve analysis were applied.

RESULTS

A statistically significant positive correlation was found between LUS score at admission and the severity of SARS-COV-2 infection. Higher LUS score was significantly associated with lower PaO2/FiO2 ratio, use of HFNC, longer hospitalization and greater extent of chest CT infiltrates. A significant association between LUS score and risk of death or intubation or HFNC was found. For one point of increase in the score, risk of death or intubation or HFNC increased 1.93-fold (95% CI 1.02 to 3.65). The predictive role of the score was very satisfactory (area under the ROC curve = 0.87).

CONCLUSIONS

Lung ultrasound findings were significantly positively associated with clinical and radiological markers of severity of SARS-CoV-2 pneumonia. It therefore constitutes a promising and reliable technique for assessing pneumonia, comparable to chest CT.

Lung Ultrasound in Critical Care: A Narrative Review

Lung ultrasound (LUS) has become a crucial part of the investigative tools available in the management of critically ill patients, both within the intensive care unit setting and in prehospital medicine. The increase in its application, in part driven by the COVID-19 pandemic, along with the easy access and use of mobile and handheld devices, allows for immediate access to information, reducing the need for other radiological investigations. LUS allows for the rapid and accurate diagnosis and grading of respiratory pathology, optimisation of ventilation, assessment of weaning, and monitoring of the efficacy of surfactant therapies. This, however, must occur within the framework of accreditation to ensure patient safety and prevent misinterpretation and misdiagnosis. This narrative review aims to outline the current uses of LUS within the context of published protocols, associated pathologies, LUS scoring systems, and their applications, whilst exploring more novel uses.

Lung ultrasound in children with cystic fibrosis - A new promising approach

BACKGROUND

Lung ultrasound is becoming increasingly important in the diagnosis of acute and chronic lung disease, especially in children and adolescents. In children with cystic fibrosis (CF), conventional radiography or computed tomography (CT) has been the main modality used to evaluate acute pneumonia or the progression of chronic lung disease. This Study aimed to evaluate Lung-Ultrasound as a diagnostic tool for children and adolescents with CF.

METHODS

We examined 30 CF patients with lung ultrasound before and after spirometry and compared them with lung ultrasounds of 15 lung-healthy children. We used a comprehensive and complete examination procedure with 12 probe positions to determine the best examination procedure in retrospect. In addition, an acceptance survey was conducted among the children and adolescents after the examination.

RESULTS

There was a significant difference in pleural irregularities, B-lines, consolidations and the adapted Peixoto et al. score between CF patients and healthy children before spirometry. We found excellent discrimination between patients and lung-healthy subjects using the Peixoto-score (AUC 0.968), pleural irregularities (AUC 0.890). CF patients had more B-lines, more consolidations, and a higher Peixoto score (mean difference 7.7 points). There was no significant difference in lung ultrasound results in children with CF before and after spirometry. Shortening our extended examination procedure would minimally compromise diagnostic accuracy. The lung ultrasound examination was well accepted by the children.

CONCLUSION

We could demonstrate that lung ultrasound is a sensitive and reliable method for assessing pulmonary changes in cystic fibrosis.

WFUMB Commentary Paper on Artificial intelligence in Medical Ultrasound Imaging

Artificial intelligence (AI) is defined as the theory and development of computer systems able to perform tasks normally associated with human intelligence. At present, AI has been widely used in a variety of ultrasound tasks, including in point-of-care ultrasound, echocardiography, and various diseases of different organs. However, the characteristics of ultrasound, compared to other imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), poses significant additional challenges to AI. Application of AI can not only reduce variability during ultrasound image acquisition, but can standardize these interpretations and identify patterns that escape the human eye and brain. These advances have enabled greater innovations in ultrasound AI applications that can be applied to a variety of clinical settings and disease states. Therefore, The World Federation of Ultrasound in Medicine and Biology (WFUMB) is addressing the topic with a brief and practical overview of current and potential future AI applications in medical ultrasound, as well as discuss some current limitations and future challenges to AI implementation.

Artificial Intelligence-Guided Lung Ultrasound by Nonexperts

Importance

Lung ultrasound (LUS) aids in the diagnosis of patients with dyspnea, including those with cardiogenic pulmonary edema, but requires technical proficiency for image acquisition. Previous research has demonstrated the effectiveness of artificial intelligence (AI) in guiding novice users to acquire high-quality cardiac ultrasound images, suggesting its potential for broader use in LUS.

Objective

To evaluate the ability of AI to guide acquisition of diagnostic-quality LUS images by trained health care professionals (THCPs).

Design, Setting, and Participants

In this multicenter diagnostic validation study conducted between July 2023 and December 2023, participants aged 21 years or older with shortness of breath recruited from 4 clinical sites underwent 2 ultrasound examinations: 1 examination by a THCP operator using Lung Guidance AI and the other by a trained LUS expert without AI. The THCPs (including medical assistants, respiratory therapists, and nurses) underwent standardized AI training for LUS acquisition before participation.

Interventions

Lung Guidance AI software uses deep learning algorithms guiding LUS image acquisition and B-line annotation. Using an 8-zone LUS protocol, the AI software automatically captures images of diagnostic quality.

Main Outcomes and Measures

The primary end point was the proportion of THCP-acquired examinations of diagnostic quality according to a panel of 5 masked expert LUS readers, who provided remote review and ground truth validation.

Results

The intention-to-treat analysis included 176 participants (81 female participants [46.0%]; mean [SD] age, 63 [14] years; mean [SD] body mass index, 31 [8]). Overall, 98.3% (95% CI, 95.1%-99.4%) of THCP-acquired studies were of diagnostic quality, with no statistically significant difference in quality compared to LUS expert-acquired studies (difference, 1.7%; 95% CI, -1.6% to 5.0%).

Conclusions and Relevance

In this multicenter validation study, THCPs with AI assistance achieved LUS images meeting diagnostic standards compared with LUS experts without AI. This technology could extend access to LUS to underserved areas lacking expert personnel.

Trial Registration

ClinicalTrials.gov Identifier: NCT05992324.

Lung Ultrasound Findings in Children With Asthma Exacerbations

OBJECTIVE

We sought to assess whether the presence and extent of lung ultrasound (LUS) findings were associated with asthma exacerbation severity in children.

METHODS

We enrolled a convenience sample of patients aged 5-18 years presenting with acute asthma exacerbation to a tertiary care pediatric emergency department. Severity of an asthma exacerbation (mild, moderate, severe) was assessed within 1 hour of the LUS using the Hospital Asthma Severity Score, a validated asthma assessment tool. LUS was performed by trained pediatric emergency providers. The presence of LUS findings (B-lines, consolidations, pleural effusion, and pleural line abnormalities) was assessed using a standardized criterion based on consensus guidelines.

RESULTS

A total of 111 patients with a median age of 8 years (interquartile range 6-12) were enrolled. LUS was positive in 57% of patients. Pleural line abnormalities were observed in 34%, B-lines in 29%, consolidations <1 cm in 24%, and consolidations ≥1 cm in 7%. Patients with moderate and severe asthma exacerbations were more likely to have any B-lines (31% and 43%, respectively) than patients with mild exacerbations (12%; P = .021); however, the presence of ≥3 B-lines or confluent B-lines did not differ across severity groups. The presence of other findings did not differ based on asthma severity.

CONCLUSIONS

LUS findings are observed in a substantial portion of children presenting with asthma exacerbations. B-lines were the only LUS finding significantly associated with asthma severity, while lung consolidations <1 cm and >1 cm were not correlated with severity. These findings provide valuable information for the diagnostic use of LUS in pediatric patients with asthma exacerbation.

Lung ultrasound in pneumonia: a guide for effective implementation

In patients with pneumonia, lung ultrasound is a useful diagnostic and monitoring tool and has been proven to be superior to physical examination and chest X-ray in terms of feasibility and diagnostic accuracy. Guidelines do not address lung ultrasound as part of the diagnostic workup or as monitoring tool which is surprising. This article provides a succinct overview on the currently available evidence on efficacy and utility of lung ultrasound in patients with a clinical suspicion of pneumonia. Various clinical settings are considered, in addition to limitations, pitfalls and advanced techniques. The aim of this paper is to equip the clinician with the necessary knowledge to maximize lung ultrasound in pneumonia as effective diagnostic and monitoring tool.

Comprehensive management of pneumonia in older patients

Pneumonia is a leading cause of death and functional decline in the older population. Diagnosis of pneumonia conventionally includes the presence of respiratory signs and symptoms, systemic signs of infection and a radiographic demonstration of lung involvement. Pneumonia diagnosis in the very old patient is compromised by atypical and unspecific presentation, resulting in a high proportion of false positive diagnosis. Chest radiograph is frequently of low quality and inconclusive in older patients. Computed tomography scan and chest ultrasound may provide valuable diagnostic confirmation in uncertain cases. Bacterial pneumonia has been mainly studied, but viruses, among which influenza, SARS-CoV-2, and respiratory syncytial virus, are increasingly recognized as major players. The decision to treat pneumonia is usually based on a triple assessment of diagnostic probability, disease severity and the general assessment of the patient (frailty, comorbidities, place of living, and goals of care). Antimicrobial treatment is probabilistic, targeting common pathogens. The optimal antibiotic treatment depends on epidemiological data, setting of acquisition, comorbidities, risk factors for methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, or aspiration pneumonia, and severity. Recent controlled trials have demonstrated the non-inferiority of short regimen in non-severe community acquired pneumonia, even in older individuals and a five-day antibiotic treatment is recommended in case of clinical improvement. Pneumonia management in older patients requires a comprehensive approach, including control of comorbidities (particularly cardiovascular), nutritional support, rehabilitation, and prevention of aspiration. Finally, pneumonia may be a pre-terminal event in many patients, requiring advanced-care planning and prompt instauration of palliative management.

Guidelines for the use of lung ultrasound to optimise the management of neonatal respiratory distress: international expert consensus

BACKGROUND

Respiratory distress is the main reason for the admission of infants to the neonatal intensive care unit (NICU). Rapid identification of the causes of respiratory distress and selection of appropriate and effective treatment strategies are important to optimise favourable short- and long-term patient outcomes. Lung ultrasound (LUS) technology has become increasingly important in this field. According to the scientific literature, LUS has high sensitivity (92-99%) and specificity (95-97%) in diagnosing neonatal respiratory distress syndrome. This diagnostic power helps guide timely interventions, such as surfactant therapy and mechanical ventilation.

METHODS

Our objective was to outline consensus guidelines among an international panel of experts on the use of LUS to support the decision-making process in managing respiratory distress in the NICU. We used a three-round Delphi process. In each Delphi round, 28 panellists rated their level of agreement with each statement using a four-point Likert scale.

RESULTS

In round 1, the panellists reviewed 30 initially proposed statements. In rounds 2 and 3, the statements were redeveloped based on the reviewers' comments, leading to the final approval of 18 statements. Among the 18 consensus statements, grade A was assigned a value of 10, grade B was assigned a value of 7, and grade C was assigned a value of 1.

CONCLUSIONS

A panel of experts agreed on 18 statements regarding managing infants with respiratory distress. Using LUS may help design future interventional studies and improve the benchmarking of respiratory care outcomes.

The diagnostic performance of automatic B-lines detection for evaluating pulmonary edema in the emergency department among novice point-of-care ultrasound practitioners

Purpose

B-lines in lung ultrasound have been a critical clue for detecting pulmonary edema. However, distinguishing B-lines from other artifacts is a challenge, especially for novice point of care ultrasound (POCUS) practitioners. This study aimed to determine the efficacy of automatic detection of B-lines using artificial intelligence (Auto B-lines) for detecting pulmonary edema.

Methods

A retrospective study was conducted on dyspnea patients treated at the emergency department between January 2023 and June 2024. Ultrasound documentation and electronic emergency department medical records were evaluated for sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of auto B-lines in detection of pulmonary edema.

Results

Sixty-six patients with a final diagnosis of pulmonary edema were enrolled, with 54.68% having positive B-lines in lung ultrasound. Auto B-lines had 95.6% sensitivity (95% confidence interval [CI]: 0.92–0.98) and 77.2% specificity (95% CI: 0.74–0.80). Physicians demonstrated 82.7% sensitivity (95% CI: 0.79–0.97) and 63.09% sensitivity (95% CI: 0.58–0.69).

Conclusion

The auto B-lines were highly sensitive in diagnosing pulmonary edema in novice POCUS practitioners. The clinical integration of physicians and artificial intelligence enhances diagnostic capabilities.

Retrospective Evaluation of Subpleural Consolidations Using Lung Ultrasound in 634 Dogs and 347 Cats

BACKGROUND

Human literature describes vascular patterns in various types of lung consolidations; however, these changes have not been analyzed in dogs and cats. This retrospective analysis of medical records aimed to describe vascular patterns observed in the airless subpleural lung tissue of dogs and cats and to compare these patterns to various lung consolidations and clinical diagnoses according to parenchymal and vascular criteria described in human literature.

ANIMALS

This study included 347 cats and 634 dogs.

METHODS

This was a retrospective study encompassing medical records obtained between 2018 and 2023. Lung ultrasound was performed in dogs and cats and cases with different sonographically identified airless subpleural lung tissue were selected. Airless subpleural lung tissue was categorized into five types of consolidations: shred, nodule, wedge sign, mass, and tissue sign. Further classification was based on the parenchymal criteria, the presence or absence of bronchograms and the vascular patterns identified within these regions. Bronchograms were classified as air bronchograms (dynamic and/or static), fluid bronchograms, mixed fluid and air bronchograms, and/or absence of bronchograms. Vascular patterns were classified as tree-like, residual, chaotic, "vascular sign", and whether they were continuous with and extended from the chest wall or not.

CONCLUSIONS AND CLINICAL IMPORTANCE

It is possible to identify and characterize airless subpleural lung tissue in cats and dogs based on the parenchymal and vascular characteristics.

Standard to Handheld: A New Wave in Thoracic Ultrasound and Patient Care-A Direct Comparison of Portable Handheld Against Standard in Thoracic Ultrasound

Background and Objective: Ultrasound has become more popular and useful over the last few years in improving healthcare. While handheld devices offer portability and convenience, their diagnostic accuracy and clinical utility require further scrutiny. This study attempted to evaluate the non-inferiority of handheld portable ultrasound devices compared to standard ultrasound devices for common lung pathologies. Materials and Methods: Videos of various common lung pathologies from 20 patients were recorded by a single operator using both portable handheld and standard ultrasound devices in a single setting. These videos were then assessed via online questionnaires by clinicians of various levels of experience from respiratory and non-respiratory departments. A Likert scale was used, ranging from strongly disagree to strongly agree (ranging from 1 to 5) in terms of overall image quality, clear anatomical visualization, similar clinical interpretations/decisions, and the perception of non-inferiority. Median values with interquartile ranges were reported; a rating of 3 or above was defined as indicating non-inferiority. Results: Thirty participants completed the questionnaires, of which the majority were at trainee level (n = 20, 73%) and from a respiratory department (n = 20, 67%). The participants had mixed levels of experience in terms of the years and frequency of use of the ultrasound. Overall median ratings were 4.0 for overall image quality, clear anatomical visualization, and similar clinical interpretations/decisions, with slight variations in interquartile ranges. No significant differences were observed between subgroups. The portable ultrasound device was rated similarly for the overall perception of non-inferiority, but clinicians from respiratory departments and clinicians with less experience showed statistically significant variability in their assessments. Conclusions: The portable handheld device demonstrated potential as a reliable alternative to standard models in standard clinical settings without compromising clinical decision. Further evaluation is needed that includes a direct comparison of various types of handheld ultrasound devices, across different operators' levels of experience, to further solidify their suitability in patient care.

Inter-rater agreement and characterization of pleural line and subpleural fields in canine lung ultrasound: a comparative pilot study between high-frequency linear and curvilinear transducers using B- and M-mode ultrasonographic profiles

BACKGROUND

Lung ultrasound (LUS) is increasingly utilized in veterinary medicine to assess pulmonary conditions. However, the characterization of pleural line and subpleural fields using different ultrasound transducers, specifically high-frequency linear ultrasound transducers (HFLUT) and curvilinear transducers (CUT), remains underexplored in canine patients. This study aimed to evaluate inter-rater agreement in the characterization of pleural line and subpleural fields using B- and M-mode ultrasonography in dogs with and without respiratory distress.

RESULTS

Eighty-eight ultrasound clips from nine dogs were analyzed. HFLUT demonstrated strong inter-rater agreement in B-mode (κ = 0.89) and near-perfect agreement in M-mode (κ = 1.00) for pleural line homogeneity. In contrast, CUT showed minimal agreement in both B-mode (κ = 0.34) and M-mode (κ = 0.37). Homogeneous pleural lines were predominantly observed in control dogs or those with cardiogenic pulmonary edema (CPE), while non-homogeneous pleural lines were more common in dogs with non-cardiogenic alveolar-interstitial syndrome (NCAIS). Vertical subpleural fields identified in M-mode were associated with both CPE and NCAIS, whereas horizontal fields were more often observed in control dogs.

CONCLUSIONS

HFLUT offers superior inter-rater reliability for characterizing pleural and subpleural features in canine LUS compared to CUT, particularly in M-mode. These findings suggest HFLUT may enhance diagnostic accuracy for pulmonary conditions in dogs. Further studies are needed to explore the diagnostic potential of LUS in differentiating vertical artifact (e.g., B-lines) etiologies in veterinary patients.

Effects of ultrasound-guided recruitment manoeuvres on postoperative pulmonary complications in laparoscopic bariatric surgery patients: study protocol for a randomised clinical trial

BACKGROUND

Lung ultrasound-guided alveolar recruitment manoeuvres (RMs) may reduce the lung ultrasound score. However, whether the use of this strategy can reduce the incidence of postoperative pulmonary complications (PPCs) in the adult obese population has not yet been tested.

METHODS/DESIGN

This is a single-centre, two-arm, prospective, randomised controlled trial. A total number of 476 obese patients scheduled for bariatric surgeries will be enrolled. They will be randomly assigned to receive either lung ultrasound-guided RMs (intervention group) or conventional RMs (control group) intraoperatively. The occurrence of PPCs will be recorded as the primary outcome.

DISCUSSION

To the best of our knowledge, this is the first trial to test the effect of lung ultrasound-guided RMs on PPCs. The results of this trial will support the anaesthesiologists in choosing a potentially more efficient method to perform RMs for bariatric surgery patients.

TRIAL REGISTRATION

www.chictr.org.cn ChiCTR2400080203. Registered on 23 January 2024.

Early prediction of long COVID-19 syndrome persistence at 12 months after hospitalisation: a prospective observational study from Ukraine

OBJECTIVE

To identify the early predictors of a self-reported persistence of long COVID syndrome (LCS) at 12 months after hospitalisation and to propose the prognostic model of its development.

DESIGN

A combined cross-sectional and prospective observational study.

SETTING

A tertiary care hospital.

PARTICIPANTS

221 patients hospitalised for COVID-19 who have undergone comprehensive clinical, sonographic and survey-based evaluation predischarge and at 1 month with subsequent 12-month follow-up. The final cohort included 166 patients who had completed the final visit at 12 months.

MAIN OUTCOME MEASURE

A self-reported persistence of LCS at 12 months after discharge.

RESULTS

Self-reported LCS was detected in 76% of participants at 3 months and in 43% at 12 months after discharge. Patients who reported incomplete recovery at 1 year were characterised by a higher burden of comorbidities (Charlson index of 0.69±0.96 vs 0.31±0.51, p=0.001) and residual pulmonary consolidations (1.56±1.78 vs 0.98±1.56, p=0.034), worse blood pressure (BP) control (systolic BP of 138.1±16.2 vs 132.2±15.8 mm Hg, p=0.041), renal (estimated glomerular filtration rate of 59.5±14.7 vs 69.8±20.7 mL/min/1.73 m2, p=0.007) and endothelial function (flow-mediated dilation of the brachial artery of 10.4±5.4 vs 12.4±5.6%, p=0.048), higher in-hospital levels of liver enzymes (alanine aminotransferase (ALT) of 76.3±60.8 vs 46.3±25.3 IU/L, p=0.002) and erythrocyte sedimentation rate (ESR) (34.3±12.1 vs 28.3±12.6 mm/h, p=0.008), slightly higher indices of ventricular longitudinal function (left ventricular (LV) global longitudinal strain (GLS) of 18.0±2.4 vs 17.0±2.3%, p=0011) and higher levels of Hospital Anxiety and Depression Scale anxiety (7.3±4.2 vs 5.6±3.8, p=0.011) and depression scores (6.4±3.9 vs 4.9±4.3, p=0.022) and EFTER-COVID study physical symptoms score (12.3±3.8 vs 9.2±4.2, p<0.001). At 1 month postdischarge, the persisting differences included marginally higher LV GLS, mitral E/e' ratio and significantly higher levels of both resting and exertional physical symptoms versus patients who reported complete recovery. Logistic regression and machine learning-based binary classification models have been developed to predict the persistence of LCS symptoms at 12 months after discharge.

CONCLUSIONS

Compared with post-COVID-19 patients who have completely recovered by 12 months after hospital discharge, those who have subsequently developed 'very long' COVID were characterised by a variety of more pronounced residual predischarge abnormalities that had mostly subsided by 1 month, except for steady differences in the physical symptoms levels. A simple artificial neural networks-based binary classification model using peak ESR, creatinine, ALT and weight loss during the acute phase, predischarge 6-minute walk distance and complex survey-based symptoms assessment as inputs has shown a 92% accuracy with an area under receiver-operator characteristic curve 0.931 in prediction of LCS symptoms persistence at 12 months.

Point-of-Care Lung Ultrasound in Small Animal Emergency and Critical Care Medicine: A Clinical Review

Thoracic point-of-care ultrasound (T-POCUS) has grown in popularity and usage in small animal emergencies and critical care settings due to its non-invasive nature, mobility, and ability to acquire images in real time. This review summarizes current understanding about T-POCUS in dogs and cats with respiratory illnesses, including normal thoracic ultrasonography appearance and numerous pathological situations. The basics of T-POCUS are covered, including equipment, scanning procedures, and picture settings. Practical applications in patients with respiratory distress are discussed, with an emphasis on pleural space abnormalities and lung diseases. Ultrasound results define pulmonary disorders such as pneumonia, atelectasis, cardiogenic and non-cardiogenic pulmonary edema, lung lobe torsion, pulmonary fibrosis, pulmonary thromboembolism, pulmonary neoplasms, and pulmonary bleeding. The evaluation focuses on T-POCUS diagnostic skills in a variety of clinical settings. Limitations and the need for more study to standardize techniques, establish agreed terminology, and create specialized educational routes are highlighted.

Integrated Lung, Diaphragm and Lower Limb Muscular Ultrasound: Clinical Correlations in Geriatric Patients with Acute Respiratory Illness

Background/Objectives: Point-of-care lung ultrasonography (LUS) represents an accurate diagnostic tool in older patients with respiratory failure. The integration of LUS with ultrasonographic assessment of diaphragm thickness and excursion, right vastus lateralis (RVL) muscle thickness and cross-sectional area (CSA) could provide real-time information on frailty and sarcopenia. The primary aim of this proof-of-concept prospective study was to evaluate clinical correlates of thoracic, diaphragmatic, and muscular ultrasound to characterize the associations between frailty, respiratory failure, and sarcopenia in older patients hospitalized for acute respiratory complaints. Methods: Each of 52 participants (age median 84, IQR 80-89 years old) underwent integrated LUS, diaphragm and RVL ultrasound examination upon admission (T0) and after 72 h of hospitalization (T1). LUS score was used to estimate lung interstitial syndrome severity. Diaphragm excursion, thickness, RVL thickness and CSA were measured following a standardized protocol. Frailty was assessed with the PC-FI (Primary Care-Frailty Index). Results: All patients exhibited multifactorial causes of respiratory symptoms. The LUS score on T0 predicted 3-month rehospitalization. Frail patients exhibited higher LUS scores on T1. Diaphragm excursion on T0 was reduced in patients with COPD and heart failure and in those developing delirium during hospitalization. Diaphragm excursion on T1 was negatively associated with PC-FI. Diaphragm thickness, RVL thickness, and CSA exhibited a positive association with obesity. Right vastus lateralis CSA on T1, however, was also negatively associated with PC-FI. Conclusions: Integrated lung, diaphragm, and RVL ultrasound shows clinical correlations with several aspects of frailty that may help to improve the management of geriatric patients with respiratory illness.

Ultrasound Lung Aeration Map via Physics-Aware Neural Operators

Lung ultrasound is a growing modality in clinics for diagnosing and monitoring acute and chronic lung diseases due to its low cost and accessibility. Lung ultrasound works by emitting diagnostic pulses, receiving pressure waves and converting them into radio frequency (RF) data, which are then processed into B-mode images with beamformers for radiologists to interpret. However, unlike conventional ultrasound for soft tissue anatomical imaging, lung ultrasound interpretation is complicated by complex reverberations from the pleural interface caused by the inability of ultrasound to penetrate air. The indirect B-mode images make interpretation highly dependent on reader expertise, requiring years of training, which limits its widespread use despite its potential for high accuracy in skilled hands. To address these challenges and democratize ultrasound lung imaging as a reliable diagnostic tool, we propose Luna (the Lung Ultrasound Neural operator for Aeration), an AI model that directly reconstructs lung aeration maps from RF data, bypassing the need for traditional beamformers and indirect interpretation of B-mode images. Luna uses a Fourier neural operator, which processes RF data efficiently in Fourier space, enabling accurate reconstruction of lung aeration maps. From reconstructed aeration maps, we calculate lung percent aeration, a key clinical metric, offering a quantitative, reader-independent alternative to traditional semi-quantitative lung ultrasound scoring methods. The development of Luna involves synthetic and real data: We simulate synthetic data with an experimentally validated approach and scan ex vivo swine lungs as real data. Trained on abundant simulated data and fine-tuned with a small amount of real-world data, Luna achieves robust performance, demonstrated by an aeration estimation error of 9% in ex-vivo swine lung scans. We demonstrate the potential of directly reconstructing lung aeration maps from RF data, providing a foundation for improving lung ultrasound interpretability, reproducibility and diagnostic utility.

Integrated Multi-Organ Ultrasound

Integrated multi-organ ultrasound is increasingly used across various medical specialties. It should be performed in conjunction with history, physical examination, and other investigations in the diagnostic process to enhance the detection of conditions in the lung, heart, and abdomen. Multi-organ ultrasound has been shown to improve diagnostic accuracy in a sizeable portion of patients, potentially altering treatment plans. Specifically, it aids in assessing shock, sepsis, dyspnea, delirium, and in the perioperative setting, contributing to a more comprehensive patient assessment process.

Impact of ultrasound settings on lung vertical artefacts: an observational study in mechanically ventilated patients

Introduction

The number of vertical artefacts (VAs) in lung ultrasound (LUS) impacts patients' clinical management. This study aimed to demonstrate the influence of ultrasound settings on the number of VAs in patients under invasive mechanical ventilation (IMV).

Methods

Patients under IMV were recruited for LUS, including three breathing cycles with a motionless curvilinear probe on the thoracic region with the most VAs. Three experts in LUS were asked about the number of VAs at random, and blinded after altering the settings for a total of 20 test recordings per patient. The correlation between expert classifications was tested after grading the classifications. The number of VAs across clinicians was compared between baseline recordings and test condition recordings to determine statistical differences.

Results

29 patients were enrolled with a median Sequential Organ Failure Assessment score of 6 (interquartile range (IQR) 3). IMV was mainly due to stroke (n=10) and pneumonia (n=6). LUS was made between days 1 and 6 (IQR). Baseline recordings showed a median of 2±2 VAs in inspiration and a median of 1±2 in expiration from a total of 3636 expert classifications, with a strong agreement within patients. A probe frequency of 8 MHz, artefact filtering, speckle reduction and frame average reduced the median VA number by one. A power of -20 dB and dynamic range of 32 dB abolished the VAs. A gain above 90% increased the median number of VAs by one.

Conclusion

In this in vivo study, the LUS settings influenced the VA number in IMV patients, after controlling for physiological and operator confounders.

Basic Lung Ultrasound and Clinical Applications in General Medicine

Proficiency in basic lung ultrasound is highly recommended for clinicians in general and internal medicine. This article will review and provide guidance for novice users on how to use lung ultrasound in clinical practice, through a pathology-oriented approach. The authors recommend a 12-zone protocol and describe how to perform and apply it in clinical practice while examining patients with clinical suspicion for the following diseases: pleural effusion, heart failure, pneumonia (bacterial and viral), interstitial lung disease, and pneumothorax.

Point-of-Care Ultrasound in Post-acute and Long-Term Care: A Scoping Review

OBJECTIVES

Point-of-care ultrasound (POCUS) is an emerging application of ultrasonography that is being integrated into patient care in many medical specialties. The post-acute and long-term care (PALTC) setting has opportunities to adopt POCUS as a diagnostic aid to improve patient outcomes. We aim (1) to describe the current use of POCUS in PALTC and (2) to examine how the use of POCUS can advance in PALTC settings.

DESIGN

Scoping review.

SETTING AND PARTICIPANTS

PALTC facilities and residents.

METHODS

The MEDLINE, Embase, CINAHL Complete, and Web of Science databases were searched by a medical librarian for studies on the use of POCUS in PALTC. All studies underwent dual, independent review during 2 phases of screening. We included all study designs where POCUS was obtained and interpreted by a provider at the bedside.

RESULTS

Six studies met inclusion criteria. Most studies were conducted in the setting of COVID19 outbreaks in nursing homes and communities. The organ systems examined using POCUS were lung and vasculature. Lung ultrasound was shown to have variable diagnostic and prognostic utility in assessing lung injury secondary to COVID19. Ultrasound measurements of the vasculature were not useful for predicting hydration status.

CONCLUSION AND IMPLICATIONS

Implementation of POCUS in PALTC is feasible, but current literature is limited to use in only 2 organ systems. These results suggest potential for expanding POCUS in PALTC. Further work is required to ascertain if POCUS use can improve patient outcomes in this health care setting.

The Role of Lung Ultrasound Scan in Different Heart Failure Scenarios: Current Applications and Lacks of Evidences

Pulmonary congestion is a critical factor influencing the clinical presentation, therapeutic decisions, and outcomes of heart failure (HF) patients. Lung ultrasound (LUS) offers a simple, rapid, and accurate method for assessing pulmonary congestion, surpassing the diagnostic capabilities of traditional clinical evaluation and chest radiography. Due to the wide availability of ultrasound equipment, congestion can be evaluated in multiple settings, ranging from emergency departments to intensive care units, including outpatient settings. A combined cardiopulmonary imaging approach, integrating LUS with other imaging modalities, enhances congestion assessment in both acute and chronic HF. This comprehensive approach provides valuable insights for HF management and risk stratification. However, optimizing the utilization of LUS remains a challenge, as standardized imaging protocols and B-line thresholds may vary across different clinical scenarios and HF phenotypes. Despite the widespread use of LUS in various HF settings, physician adoption and interpretation of LUS findings remain suboptimal. This review aims to provide a practical and clinical overview of LUS in HF, guiding clinicians towards the correct application and interpretation of this valuable tool in diverse HF contexts.

Ten Questions on Using Lung Ultrasonography to Diagnose and Manage Pneumonia in the Hospital-at-Home Model: Part I-Techniques and Patterns

The hospital-at-home (HaH) model delivers hospital-level acute care, including diagnostics, monitoring, and treatments, in a patient's home. It is particularly effective for managing conditions such as pneumonia. Point-of-care ultrasonography (PoCUS) is a key diagnostic tool in the HaH model, and it often serves as a substitute for imaging-based diagnosis in the HaH setting. Both standard and handheld ultrasound equipment are suitable for lung ultrasound (LUS) evaluation. Curvelinear and linear probes are typically used. Patient positioning depends on their clinical condition and specific diagnostic protocols. To enhance sensitivity, we recommend using at least 10-point protocols supported by studies for pneumonia. Five essential LUS patterns should be identified, including A-line, multiple B-lines (alveolar-interstitial syndrome), confluent B-lines, subpleural consolidation, and consolidation with air bronchogram. Pleural effusion is common, and its internal echogenicity can indicate severity and the need for invasive procedures. The current evidence on various etiologies and types of pneumonia is limited, but LUS demonstrates good sensitivity in detecting abnormal sonographic patterns in atypical pneumonia, tuberculosis, and ventilator-associated pneumonia. Further LUS studies in the HaH setting are required to validate and generalize the findings.

[Use of clinical ultrasound in primary care: Markers in congestive heart failure]

The patient with heart failure (HF) is a frequent scenario in primary care consultations. The presence of subclinical congestion is a predictor of rehospitalization and adverse events in these patients. The assessment of congestion is complex due to the low sensitivity of classic symptoms and signs, which leads to underdiagnosis, delayed initiation of treatment and a greater likelihood of complications. The family doctor should be familiar with new techniques for congestion assessment, such as the study of venous congestion with ultrasound and pulmonary ultrasound. This makes it possible to know the existence of subclinical congestion in a more realistic way. Clinical ultrasound in the hands of the family doctor individualizes decongestive therapy in patients with HF in an accurate, fast and safe way.

The role of point-of-care ultrasound to monitor response of fluid replacement therapy in pregnancy

Fluid management in obstetrical care is crucial because of the complex physiological conditions of pregnancy, which complicate clinical manifestations and fluid balance management. This expert review examined the use of point-of-care ultrasound to evaluate and monitor the response to fluid therapy in pregnant patients. Pregnancy induces substantial physiological changes, including increased cardiac output and glomerular filtration rate, decreased systemic vascular resistance, and decreased plasma oncotic pressure. Conditions, such as preeclampsia, further complicate fluid management because of decreased intravascular volume and increased capillary permeability. Traditional methods for assessing fluid volume status, such as physical examination and invasive monitoring, are often unreliable or inappropriate. Point-of-care ultrasound provides a noninvasive, rapid, and reliable means to assess fluid responsiveness, which is essential for managing fluid therapy in pregnant patients. This review details the various point-of-care ultrasound modalities used to measure dynamic changes in fluid status, focusing on the evaluation of the inferior vena cava, lung ultrasound, and left ventricular outflow tract. Inferior vena cava ultrasound in spontaneously breathing patients determines diameter variability, predicts fluid responsiveness, and is feasible even late in pregnancy. Lung ultrasound is crucial for detecting early signs of pulmonary edema before clinical symptoms arise and is more accurate than traditional radiography. The left ventricular outflow tract velocity time integral assesses stroke volume response to fluid challenges, providing a quantifiable measure of cardiac function, which is particularly beneficial in critical care settings where rapid and accurate fluid management is essential. This expert review synthesizes current evidence and practice guidelines, suggesting the integration of point-of-care ultrasound as a fundamental aspect of fluid management in obstetrics. It calls for ongoing research to enhance techniques and validate their use in broader clinical settings, aiming to improve outcomes for pregnant patients and their babies by preventing complications associated with both under- and overresuscitation.

Lung ultrasound in children with primary ciliary dyskinesia or cystic fibrosis

INTRODUCTION

Primary ciliary dyskinesia (PCD) and cystic fibrosis (CF) are respiratory conditions requiring regular chest radiography (CXR) surveillance to monitor pulmonary disease. However, CXR is insensitive for lung disease in CF and PCD. Lung ultrasound (LU) is a radiation-free alternative showing good correlation with severity of lung disease in CF but has not been studied in PCD.

METHOD

Standardized, six-zone LU studies and CXR were performed on a convenience sample of children with PCD or CF during a single visit when well. LU studies were graded using the LU scoring system, while CXR studies received a modified Chrispin-Norman score. Scores were correlated with clinical outcomes.

RESULT

Data from 30 patients with PCD and 30 with CF (median age PCD 11.5 years, CF 9.1 years) with overall mild pulmonary disease (PCD median FEV1 90% predicted, CF FEV1 100%) were analyzed. LU abnormalities appear in 11/30 (36%) patients with PCD and 9/30 (30%) with CF. Sensitivity, specificity, positive predictive, and negative predictive values for abnormal LU compared to the gold standard of CXR are 42%, 61%, 42%, and 61% in PCD, and 44%, 81%, 50%, and 77% in CF, respectively. Correlation between LU and CXR scores are poor for both diseases (PCD r = -0.1288, p = 0.4977; CF r = 0.0343, p = 0.8571), and LU score does not correlate with clinical outcomes in PCD.

CONCLUSION

The correlation of LU findings with CXR surveillance studies is poor in patients with mild disease burdens from PCD or CF, and LU scores do not correlate with clinical outcomes in PCD.

Deep learning approaches for automated classification of neonatal lung ultrasound with assessment of human-to-AI interrater agreement

Neonatal respiratory disorders pose significant challenges in clinical settings, often requiring rapid and accurate diagnostic solutions for effective management. Lung ultrasound (LUS) has emerged as a promising tool to evaluate respiratory conditions in neonates. This evaluation is mainly based on the interpretation of visual patterns (horizontal artifacts, vertical artifacts, and consolidations). Automated interpretation of these patterns can assist clinicians in their evaluations. However, developing AI-based solutions for this purpose is challenging, primarily due to the lack of annotated data and inherent subjectivity in expert interpretations. This study aims to propose an automated solution for the reliable interpretation of patterns in LUS videos of newborns. We employed two distinct strategies. The first strategy is a frame-to-video-level approach that computes frame-level predictions from deep learning (DL) models trained from scratch (F2V-TS) along with fine-tuning pre-trained models (F2V-FT) followed by aggregation of those predictions for video-level evaluation. The second strategy is a direct video classification approach (DV) for evaluating LUS data. To evaluate our methods, we used LUS data from 34 neonatal patients comprising of 70 exams with annotations provided by three expert human operators (3HOs). Results show that within the frame-to-video-level approach, F2V-FT achieved the best performance with an accuracy of 77% showing moderate agreement with the 3HOs. while the direct video classification approach resulted in an accuracy of 72%, showing substantial agreement with the 3HOs, our proposed study lays down the foundation for reliable AI-based solutions for newborn LUS data evaluation.

The Application of Diaphragm Ultrasound in Chronic Obstructive Pulmonary Disease: A Narrative Review

Chronic Obstructive Pulmonary Disease (COPD) is a prevalent condition that poses a significant burden on individuals and society due to its high morbidity and mortality rates. The diaphragm is the main respiratory muscle, its function has a direct impact on the quality of life and prognosis of COPD patients. This article aims to review the structural measurement and functional evaluation methods through the use of diaphragmatic ultrasound and relevant research on its application in clinical practice for COPD patients. Thus, it serves to provide valuable insights for clinical monitoring of diaphragm function in COPD patients, facilitating early clinical intervention and aiding in the recovery of diaphragm function.

Lung ultrasound for the diagnosis of subpleural consolidations - a review of the veterinary and human literature

Lung ultrasound (LUS) is an imaging modality of growing importance in human medicine. LUS has been extensively applied to human patients. Guidelines have been created for internal medicine, describing ultrasonographic features of various lung pathologic processes. Such guidelines do not exist for veterinary medicine, and studies on the utility of LUS in companion animals are limited. Therefore, this review compares conclusions from veterinary studies to recommendations in human medicine for the detection of subpleural consolidations beyond the application of LUS as a point-of-care modality in emergency and critical care.

D-PRISM: a global survey-based study to assess diagnostic and treatment approaches in pneumonia managed in intensive care

BACKGROUND

Pneumonia remains a significant global health concern, particularly among those requiring admission to the intensive care unit (ICU). Despite the availability of international guidelines, there remains heterogeneity in clinical management. The D-PRISM study aimed to develop a global overview of how pneumonias (i.e., community-acquired (CAP), hospital-acquired (HAP), and Ventilator-associated pneumonia (VAP)) are diagnosed and treated in the ICU and compare differences in clinical practice worldwide.

METHODS

The D-PRISM study was a multinational, survey-based investigation to assess the diagnosis and treatment of pneumonia in the ICU. A self-administered online questionnaire was distributed to intensive care clinicians from 72 countries between September to November 2022. The questionnaire included sections on professional profiles, current clinical practice in diagnosing and managing CAP, HAP, and VAP, and the availability of microbiology diagnostic tests. Multivariable analysis using multiple regression analysis was used to assess the relationship between reported antibiotic duration and organisational variables collected in the study.

RESULTS

A total of 1296 valid responses were collected from ICU clinicians, spread between low-and-middle income (LMIC) and high-income countries (HIC), with LMIC respondents comprising 51% of respondents. There is heterogeneity across the diagnostic processes, including clinical assessment, where 30% (389) did not consider radiological evidence essential to diagnose pneumonia, variable collection of microbiological samples, and use and practice in bronchoscopy. Microbiological diagnostics were least frequently available in low and lower-middle-income nation settings. Modal intended antibiotic treatment duration was 5-7 days for all types of pneumonia. Shorter durations of antibiotic treatment were associated with antimicrobial stewardship (AMS) programs, high national income status, and formal intensive care training.

CONCLUSIONS

This study highlighted variations in clinical practice and diagnostic capabilities for pneumonia, particularly issues with access to diagnostic tools in LMICs were identified. There is a clear need for improved adherence to existing guidelines and standardized approaches to diagnosing and treating pneumonia in the ICU. Trial registration As a survey of current practice, this study was not registered. It was reviewed and endorsed by the European Society of Intensive Care Medicine.

[Diagnostic comparison of bedside lung ultrasound and chest radiography in the intensive care unit]

BACKGROUND

Bedside lung ultrasound (POCUS) offers advantages over chest X-ray, including better cost-effectiveness for diagnosing certain pulmonary pathologies. This study compares the diagnostic concordance between portable chest X-rays and bedside lung ultrasounds in the intensive care unit (ICU).

METHODS

Adult ICU patients were included. POCUS was performed using the abbreviated BLUE protocol. Diagnostic results from POCUS and chest radiographies were compared using the intensivist clinical diagnosis - based on clinical examinations and lung ultrasounds - as the reference. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the ultrasounds were calculated.

RESULTS

A total of 100 patients were included, 71 with pulmonary pathologies. The average time to perform the ultrasound was 308 seconds. Ultrasound identified pathology in 20 patients with a normal chest radiographs. Diagnostic discrepancies occurred in 30 patients, highlighting ultrasound´s superior sensitivity in detecting atelectasis, pleural effusions, and pulmonary edema. Ultrasound demonstrated sensitivity (S) of 85%, specificity (E) of 100%, positive predictive value (PPV) of 100%, and negative predictive value (NPV) of 55%.

CONCLUSION

Lung point-of-care ultrasound at ICU admission detects more pathologies and does not miss significant abnormalities seen on chest X-rays. It also shows good diagnostic accuracy. These findings suggest that pulmonary POCUS, using an abbreviated protocol, could be a viable alternative to chest radiography for initial evaluation and follow-up of pulmonary pathologies in critically ill patients, potentially improving care quality and management.

Delphi Consensus Recommendations for the Development of the Emergency Medicine Point of Care Ultrasound (POCUS) Curriculum in Nepal

Introduction: Emergency Medicine Point of Care Ultrasound (EM-POCUS) is a diagnostic bedside tool for quick and accurate clinical decision-making. Comprehensive training in POCUS is a mandatory part of EM training in developed countries. In Nepal, we need to build an educational curriculum based on the local medical system, available resources, and educational environment. We used the modified Delphi method to develop a EM-POCUS curriculum. Methods: We formed an EM-POCUS core working group based on expertise in key identified areas. The core working group developed criteria for expert panelist selection and synthesized the data for panelists after each Delphi round. We recruited 46 expert panelists to participate in a series of electronic surveys. The literature review and the results of the first Delphi round identified a set of competencies. Quantitative methodology was performed for subsequent surveys. Data analysis of the frequency, percentage, median, and interquartile range of the 9-point Likert scale was performed. We deemed a minimum threshold of 80% agreement to retain items across Delphi rounds. The result of every round was disseminated before subsequent rounds for the expert panelists to review responses in light of the group's response. Results: We identified 10 specific global competency categories and 132 objectives (Round 1, response rate 85%). Rounds 2 and 3 (response rates 78% and 81% respectively) developed consensus on 45 core objectives (34%). The list of EM-POCUS competencies with the median (IQR) was finalized. Conclusion: This expert, consensus-generated EM-POCUS curriculum provides detailed guidance for EM-POCUS education and applications in clinical practice in Nepal.

A study of machine learning to predict NRDS severity based on lung ultrasound score and clinical indicators

Objective

To develop predictive models for neonatal respiratory distress syndrome (NRDS) using machine learning algorithms to improve the accuracy of severity predictions.

Methods

This double-blind cohort study included 230 neonates admitted to the neonatal intensive care unit (NICU) of Yantaishan Hospital between December 2020 and June 2023. Of these, 119 neonates were diagnosed with NRDS and placed in the NRDS group, while 111 neonates with other conditions formed the non-NRDS (N-NRDS) group. All neonates underwent lung ultrasound and various clinical assessments, with data collected on the oxygenation index (OI), sequential organ failure assessment (SOFA), respiratory index (RI), and lung ultrasound score (LUS). An independent sample test was used to compare the groups' LUS, OI, RI, SOFA scores, and clinical data. Use Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify predictor variables, and construct a model for predicting NRDS severity using logistic regression (LR), random forest (RF), artificial neural network (NN), and support vector machine (SVM) algorithms. The importance of predictive variables and performance metrics was evaluated for each model.

Results

The NRDS group showed significantly higher LUS, SOFA, and RI scores and lower OI values than the N-NRDS group (p < 0.01). LUS, SOFA, and RI scores were significantly higher in the severe NRDS group compared to the mild and moderate groups, while OI was markedly lower (p < 0.01). LUS, OI, RI, and SOFA scores were the most impactful variables for the predictive efficacy of the models. The RF model performed best of the four models, with an AUC of 0.894, accuracy of 0.808, and sensitivity of 0.706. In contrast, the LR, NN, and SVM models have lower AUC values than the RF model with 0.841, 0.828, and 0.726, respectively.

Conclusion

Four predictive models based on machine learning can accurately assess the severity of NRDS. Among them, the RF model exhibits the best predictive performance, offering more effective support for the treatment and care of neonates.

[Chest ultrasound for imaging of pneumonia]

Diagnosis of pneumonia can be challenging, particularly the differential diagnosis of lower respiratory tract infection and pneumonia, acute respiratory failure, the diagnosis of nosocomial pneumonia and in case of treatment failure. As compared to conventional chest radiography and CT of the scan, sonography of the chest offers advantages. It could be demonstrated that it was even superior to chest radiography in the identification of pneumonic consolidations. Since most pneumonias affect the lower lobes and include the pleura, pneumonic substrates could be identified in up to 90% of cases despite the limited penetration depth of lung ultrasound. Sonography of the chest has become an established method in the diagnosis of both adult as well as in pediatric community-acquired pneumonia. In addition, it is particularly powerful when used within a point of care (POCUS) approach which also includes the evaluation of the heart. Finally, it appears to have significant potential also in the diagnosis of nosomomial pneumonia and in the evaluation of treatment response, both in the ward as in the ICU.

Factors associated with antibiotics for respiratory infections in Swiss long-term care facilities

BACKGROUND

Long-term care facility (LTCF) residents are twice as likely to receive antibiotics compared with elderly living in the community, and studies have reported up to half of prescriptions in LTCFs as inappropriate.

AIM

To identify factors contributing to general and inappropriate antibiotic prescription among LTCF residents with lower respiratory tract infections (LRTIs).

METHODS

In this prospective, multicentric, observational study, residents with LRTIs were recruited among 32 LTCFs in Western Switzerland during winter 2022-2023. Residents underwent lung ultrasound (LUS) within three days of LRTI onset, serving as the pneumonia diagnosis reference standard. Multivariate logistic regression and backward selection were used with P < 0.1 cut-off to identify factors among demographics, vital signs, diagnostic tests, and LTCF characteristics associated with (i) antibiotic prescription and (ii) inappropriate prescription.

FINDINGS

A total of 114 residents were included, 63% female, median age 87 years. Fifty-nine (52%) residents underwent diagnostic tests: 50 (44%) polymerase chain reaction (PCR) for respiratory viruses and 16 (14%) blood test with C-reactive protein and/or blood count. Sixty-three (55%) residents received antibiotics. Factors associated with antibiotic prescriptions were Rockwood Clinical Frailty Scale score ≥7, oxygen saturation <92%, performing a blood test, rural LTCFs, and female physician. Among residents receiving antibiotics, 48 (74%) had inappropriate prescriptions, with performance of respiratory virus PCR test as the only protective factor.

CONCLUSION

Whereas half of LRTI residents received antibiotics, falling within lower ranges of European LTCFs prescription rates (53-80%), most antibiotic prescriptions were inappropriate. Utilization of diagnostic tests correlates with lower overall and inappropriate prescription, advocating for their use to optimize prescription practices in LTCFs.

Comments and Illustrations of the European Federation of Societies for Ultrasound in Medicine (EFSUMB) Guidelines: Rare Malignant Pulmonal and Pleural Tumors: Primary Pulmonary Sarcoma and Mesothelioma, Imaging Features on Transthoracic Ultrasound

Primary pulmonary sarcoma and mesothelioma are rare malignancies. The review article discusses the appearance of these tumors in B-mode ultrasound (US), color Doppler ultrasound and contrast-enhanced ultrasound (CEUS). In particular, the article is intended to inspire the examination of thoracic wall tumors and pleural masses with the possibilities of ultrasonography and to obtain histologically evaluable material using US or CEUS-guided sampling.

Establishment of seven lung ultrasound phenotypes: a retrospective observational study of an LUS registry

BACKGROUND

Lung phenotypes have been extensively utilized to assess lung injury and guide precise treatment. However, current phenotypic evaluation methods rely on CT scans and other techniques. Although lung ultrasound (LUS) is widely employed in critically ill patients, there is a lack of comprehensive and systematic identification of LUS phenotypes based on clinical data and assessment of their clinical value.

METHODS

Our study was based on a retrospective database. A total of 821 patients were included from September 2019 to October 2020. 1902 LUS examinations were performed in this period. Using a dataset of 55 LUS examinations focused on lung injuries, a group of experts developed an algorithm for classifying LUS phenotypes based on clinical practice, expert experience, and lecture review. This algorithm underwent validation and refinement with an additional 140 LUS images, leading to five iterative revisions and the generation of 1902 distinct LUS phenotypes. Subsequently, a validated machine learning algorithm was applied to these phenotypes. To assess the algorithm's effectiveness, experts manually verified 30% of the phenotypes, confirming its efficacy. Using K-means cluster analysis and expert image selection from the 1902 LUS examinations, we established seven distinct LUS phenotypes. To further explore the diagnostic value of these phenotypes for clinical diagnosis, we investigated their auxiliary diagnostic capabilities.

RESULTS

A total of 1902 LUS phenotypes were tested by randomly selecting 30% to verify the phenotypic accuracy. With the 1902 LUS phenotypes, seven lung ultrasound phenotypes were established through statistical K-means cluster analysis and expert screening. The acute respiratory distress syndrome (ARDS) exhibited gravity-dependent phenotypes, while the cardiogenic pulmonary edema exhibited nongravity phenotypes. The baseline characteristics of the 821 patients included age (66.14 ± 11.76), sex (560/321), heart rate (96.99 ± 23.75), mean arterial pressure (86.5 ± 13.57), Acute Physiology and Chronic Health Evaluation II (APACHE II)score (20.49 ± 8.60), and duration of ICU stay (24.50 ± 26.22); among the 821 patients, 78.8% were cured. In severe pneumonia patients, the gravity-dependent phenotype accounted for 42% of the cases, whereas the nongravity-dependent phenotype constituted 58%. These findings highlight the value of applying different LUS phenotypes in various diagnoses.

CONCLUSIONS

Seven sets of LUS phenotypes were established through machine learning analysis of retrospective data; these phenotypes could represent the typical characteristics of patients with different types of critical illness.

Lung Ultrasound Spectroscopy Applied to the Differential Diagnosis of Pulmonary Diseases: An In Vivo Multicenter Clinical Study

Lung ultrasound (LUS) is an important imaging modality to assess the state of the lung surface. However, current LUS approaches are based on subjective interpretation of imaging artifacts, which results in poor specificity as quantitative evaluation lacks. The latter could be improved by adopting LUS spectroscopy of vertical artifacts. Indeed, parameterizing these artifacts with native frequency, bandwidth, and total intensity ( [Formula: see text]) already showed potentials in differentiating pulmonary fibrosis (PF). In this study, we acquired radio frequency (RF) data from 114 patients. These data (representing the largest LUS RF dataset worldwide) were acquired by utilizing a multifrequency approach, implemented with an ULtrasound Advanced Open Platform (ULA-OP). Convex (CA631) and linear (LA533) probes (Esaote, Florence, Italy) were utilized to acquire RF data at three (2, 3, and 4 MHz), and four (3, 4, 5, and 6 MHz) imaging frequencies. A multifrequency analysis was conducted on vertical artifacts detected in patients having cardiogenic pulmonary edema (CPE), pneumonia, or PF. These artifacts were characterized by the three abovementioned parameters, and their mean values were used to project each patient into a feature space having up to three dimensions. Binary classifiers were used to evaluate the performance of these three mean features in differentiating patients affected by CPE, pneumonia, and PF. Acquisitions of multifrequency data performed with linear probe lead to accuracies up to 85.43% in the differential diagnosis of these diseases (convex probes' maximum accuracy was 74.51%). Moreover, the results showed high potentials of mean [Formula: see text] (by itself or combined with other features) in improving LUS specificity.

Role of Lung Ultrasound in the Detection of Lung Sequelae in Post-COVID-19 Patients: A Systematic Review and Meta-Analysis

Background: During the COVID-19 pandemic, several studies demonstrated the effectiveness of lung ultrasound (LUS) as a frontline tool in diagnosing and managing acute SARS-CoV-2 pneumonia. However, its role in detecting post-COVID-19 lung sequelae remains to be fully determined. This study aims to evaluate the diagnostic accuracy of LUS in identifying lung parenchymal damage, particularly fibrotic-like changes, following COVID-19 pneumonia, comparing its performance to that of CT. Methods: Relevant studies published before July 2024 were identified through a comprehensive search of PubMed, Embase, and Cochrane library. The search terms were combinations of the relevant medical subject heading (MeSH) terms, key words and word variants for "lung", "post-COVID", "long-COVID", and "ultrasound". The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver-operating characteristic (SROC) curve were used to examine the accuracy of CEUS. The selected works used different thresholds for the detection and counting of B-lines by ultrasound. This led to dividing our analysis into two models, the first based on the lower thresholds for detection of B-lines found in the works, and the second on data obtained using a higher detection threshold. Results: In terms of the diagnostic accuracy of LUS in detecting residual fibrotic-like changes in patients post-COVID-19 infection, a low-threshold model displayed a pooled sensitivity of 0.98 [95% confidence interval (CI): 0.95-0.99] and a pooled specificity of 0.54 (95% CI: 0.49-0.59). The DOR was 44.9 (95% CI: 10.8-187.1). The area under the curve (AUC) of SROC was 0.90. In the second analysis, the model with the higher threshold to detect B-lines showed a pooled sensitivity of 0.90 (95% CI: 0.85-0.94) and a pooled specificity of 0.88 (95% CI: 0.84-0.91). The DOR was 50.4 (95% CI: 15.9-159.3). The AUC of SROC was 0.93. Conclusions: In both analyses (even using the high threshold for the detection of B-lines), excellent sensitivity (98% in model 1 and 90% in model 2) is maintained. The specificity has a significant variation between the two models from 54 (model 1) to 87% (model 2). The model with the highest threshold for the detection of B-lines displayed the best diagnostic accuracy, as confirmed by the AUC values of the SROC (0.93).

The LUSBI Protocol (Lung Ultrasound/BREST Score/Inferior Vena Cava)-Its Role in a Differential Diagnostic Approach to Dyspnea of Cardiogenic and Non-Cardiogenic Origin

Background and Objectives: PoCUS ultrasound applications are widely used in everyday work, especially in the field of emergency medicine. The main goal of this research was to create a diagnostic and therapeutic protocol that will integrate ultrasound examination of the lungs, ultrasound measurements of the inferior vena cava (assessment of central venous pressure) and BREST scores (risk stratification for heart failure), with the aim of establishing a more effective differential diagnostic approach for dyspneic patients. Materials and Methods: A cross-sectional study was conducted in the emergency medicine department with the educational center of the community health center of Banja Luka. Eighty patients of both sexes were included and divided into experimental and control groups based on the presence or absence of dyspnea as a dominant subjective complaint. Based on the abovementioned variables, the LUSBI protocol (lung ultrasound/BREST score/inferior vena cava) was created, including profiles to determine the nature of the origin of complaints. The biochemical marker of heart failure NT pro-BNP served as a laboratory confirmation of the cardiac origin of the complaints. Results: The distribution of NT pro BNP values in the experimental group showed statistically significant differences between individual profiles of the LUSBI protocol (p < 0.001). Patients assigned to group B PLAPS 2 had significantly higher average values of NT pro-BNP (20159.00 ± 3114.02 pg/mL) compared to other LUSBI profiles. Patients from the experimental group who had a high risk of heart failure according to their BREST scores also had a significantly higher average maximum expiratory diameter compared to those without heart failure (p = 0.004). A statistically significant difference (p = 0.001) in LUSBI profiles was observed between the groups of patients divided according to CVP categories. Conclusion: The integration of the LUSBI protocol into the differential diagnosis of dyspnea has been shown to be very effective in confirming or excluding a cardiac cause of the disease in patients.

A versatile role for lung ultrasound in systemic autoimmune rheumatic diseases related pulmonary involvement: a narrative review

Systemic autoimmune rheumatic diseases (SARDs) related pulmonary disease is highly prevalent, with variable clinical presentation and behavior, and thus is associated with poor outcomes and negatively impacts quality of life. Chest high resolution computed tomography (HRCT) is still considered a fundamental imaging tool in the screening, diagnosis, and follow-up of pulmonary disease in patients with SARDs. However, radiation exposure, economic burden, as well as lack of point-of-care CT equipment limits its application in some clinical situation. Ultrasound has found a place in numerous aspects of the rheumatic diseases, including the vasculature, skin, muscle, joints, kidneys and in screening for malignancies. Likewise it has found increasing use in the lungs. In the past two decades, lung ultrasound has started to be used for pulmonary parenchymal diseases such as pneumonia, pulmonary edema, lung fibrosis, pneumothorax, and pleural lesions, although the lung parenchymal was once considered off-limits to ultrasound. Lung ultrasound B-lines and irregularities of the pleural line are now regarded two important sonographic artefacts related to diffuse parenchymal lung disease and they could reflect the lesion extent and severity. However, its role in the management of SARDs related pulmonary involvement has not been fully investigated. This review article will focus on the potential applications of lung ultrasound in different pulmonary scenarios related with SARDs, such as interstitial lung disease, diffuse alveolar hemorrhage, diaphragmatic involvement, and pulmonary infection, in order to explore its value in clinical daily practice.

RATTUS (Rat Thoracic Ultrasound): diagnosis of pneumothorax in pet rats

Introduction

Rat thoracic ultrasound (RATTUS) is a non-invasive, easy-to-perform method for the evaluation of the pleural space and lungs in pet rats. The aim of the article is to present species-specific differences in the sonographic diagnosis of pneumothorax (PTX) in pet rats.

Methods

In total, 158 client-owned pet rats were examined during the period from July 2023 to January 2024. PTX was diagnosed in 20 of the examined rats (13.25%, the age of the animals ranged from 2 months to 32 months (19.08 ± 6.93 months; mean ± SD) and their body weight ranged from 97 g to 885 g (461.27 ± 138.97 g; mean ± SD). Radiographic confirmation of PTX was performed in all these 20 rats, in the control group radiography was used to confirm that PTX was not present.

Results

The lung point and the barcode sign was found in 7/20 animals with sensitivity of 33.3% (95% CI, 0.16-0.59) and specificity of 100% (95% CI, 0.97-1.0). The abnormal curtain sign was found in 19/20 of animals with the sensitivity of 95% (95% CI, 0.73-0.99.7) and the specificity of 89% (95% CI, 0.82-0.93). The abnormalities in the substernal access were in 17/20 of animals with the sensitivity of 85% (95% CI, 0.61-0.96) and the specificity of 71% (95% CI, 0.62-0.78).

Discussion

In conclusion, RATTUS is a non-invasive method for the diagnosis of PTX in rats. Lung point and barcode sign are specific but not easily diagnosed signs. The curtain sign in RATTUS is not specific for PTX, as there are e.g. geriatric rats (rats older than 1,5 years) in which the abnormal curtain sign is visible without the presence of PTX. The presence of moderate to severe PTX can be assessed by the substernal approach based on the presence of cardiac displacement toward the collapsed lung lobe, and on evaluation of the lung inflation symmetry. This sign is not specific for PTX but in conjunction with other ultrasonic signs described makes the RATTUS a feasible tool for PTX diagnosis in rats.

FLUEnT: Transformer for detecting lung consolidations in videos using fused lung ultrasound encodings

Pneumonia is the leading cause of death among children around the world. According to WHO, a total of 740,180 lives under the age of five were lost due to pneumonia in 2019. Lung ultrasound (LUS) has been shown to be particularly useful for supporting the diagnosis of pneumonia in children and reducing mortality in resource-limited settings. The wide application of point-of-care ultrasound at the bedside is limited mainly due to a lack of training for data acquisition and interpretation. Artificial Intelligence can serve as a potential tool to automate and improve the LUS data interpretation process, which mainly involves analysis of hyper-echoic horizontal and vertical artifacts, and hypo-echoic small to large consolidations. This paper presents, Fused Lung Ultrasound Encoding-based Transformer (FLUEnT), a novel pediatric LUS video scoring framework for detecting lung consolidations using fused LUS encodings. Frame-level embeddings from a variational autoencoder, features from a spatially attentive ResNet-18, and encoded patient information as metadata combiningly form the fused encodings. These encodings are then passed on to the transformer for binary classification of the presence or absence of consolidations in the video. The video-level analysis using fused encodings resulted in a mean balanced accuracy of 89.3 %, giving an average improvement of 4.7 % points in comparison to when using these encodings individually. In conclusion, outperforming the state-of-the-art models by an average margin of 8 % points, our proposed FLUEnT framework serves as a benchmark for detecting lung consolidations in LUS videos from pediatric pneumonia patients.

Feline friendly POCUS: how to implement it into your daily practice

PRACTICAL RELEVANCE

Cats are great pretenders; they often hide illness until they are critical. This makes patients of this species challenging to assess and manage in the emergency setting where quick and stress-free diagnosis and treatment are necessary. Veterinary point-of-care ultrasound (POCUS) is a rapid, evidence-based, non-invasive, repeatable, cage-side ultrasonographic examination designed to answer clinically driven questions without compromising feline wellbeing. Integrating feline friendly POCUS as an extension of the physical examination to streamline diagnostic and therapeutic interventions, thereby limiting stress and improving overall patient care, is advocated by the authors of this article.

EQUIPMENT

Given the multitude of ultrasound machines and probes available that are portable, meaning they can be moved around the clinic and used patient-side, it should be possible for most practitioners to integrate POCUS into daily practice. The authors' preferred equipment for feline POCUS is a microconvex probe and a portable machine with a fixed pre-set. This set-up allows the clinician to complete all POCUS (abdominal, lung and pleural space, and heart) without needing to move the patient, change probes or restrain the patient in a particular position, ultimately saving time, personnel and cost while maintaining patient comfort and safety.

AIM

This review aims to serve as a valuable resource for veterinarians seeking to improve their feline patient care through the judicious utilisation of POCUS. In this article, the complex challenges posed by cats are addressed, and the different POCUS techniques, applications and clinical recommendations are discussed.

EVIDENCE BASE

This review draws on the published literature, as well as the authors' own collective experience when providing recommendations.

Knowledge fused latent representation from lung ultrasound examination for COVID-19 pneumonia severity assessment

COVID-19 pneumonia severity assessment is of great clinical importance, and lung ultrasound (LUS) plays a crucial role in aiding the severity assessment of COVID-19 pneumonia due to its safety and portability. However, its reliance on qualitative and subjective observations by clinicians is a limitation. Moreover, LUS images often exhibit significant heterogeneity, emphasizing the need for more quantitative assessment methods. In this paper, we propose a knowledge fused latent representation framework tailored for COVID-19 pneumonia severity assessment using LUS examinations. The framework transforms the LUS examination into latent representation and extracts knowledge from regions labeled by clinicians to improve accuracy. To fuse the knowledge into the latent representation, we employ a knowledge fusion with latent representation (KFLR) model. This model significantly reduces errors compared to approaches that lack prior knowledge integration. Experimental results demonstrate the effectiveness of our method, achieving high accuracy of 96.4 % and 87.4 % for binary-level and four-level COVID-19 pneumonia severity assessments, respectively. It is worth noting that only a limited number of studies have reported accuracy for clinically valuable exam level assessments, and our method surpass existing methods in this context. These findings highlight the potential of the proposed framework for monitoring disease progression and patient stratification in COVID-19 pneumonia cases.

Integration of Diagnostic Lung Ultrasound Into Clinical Practice by Hospitalists in an Academic Medical Center: A Retrospective Chart Review

Background Point-of-care lung ultrasound (LUS) is a guideline-recommended imaging modality that has been shown to be more accurate than chest radiography for multiple causes of dyspnea. This study was conducted to understand the impact of LUS on real-world clinical decision-making among hospitalists. Methods  A retrospective chart review was conducted of patients who received a LUS while hospitalized at a quaternary care academic medical center between July 2020 and June 2022. Data was extracted from the electronic health record (EHR) into a standardized REDCap form. Cases were defined as patients who had received a LUS that (1) had images archived and accessible to viewing through the EHR and (2) had an imaging report documented in the EHR. Results Of the 820 LUSs reviewed, 297 (36.2%) were performed to evaluate for appropriateness of thoracentesis, 205 (25%) for diagnosing or monitoring of pneumonia related to COVID-19, 169 (20.6%) for volume status assessment, 136 (16.6%) for worsening respiratory status, 114 (13.9%) for monitoring pleural effusions, 64 (7.8%) for diagnosing or monitoring of pneumonia not related to COVID-19, and 12 (1.5%) for monitoring of diuresis. Documentation was sufficient to determine clinical decision-making in 730 (89%) of LUSs reviewed, 739 (90.1%) were considered to be diagnostically useful, and 327 (39.9%) changed management. Conclusions These findings suggest LUS was diagnostically useful and routinely changed management in hospitalist practice. Further, documentation in the EHR was sufficient to allow for the evaluation of real-world clinical decision-making using LUS, which is an important gap in both the education and health services research literature.