Relevance of lung ultrasound in the diagnostic algorithm of respiratory diseases in a real-life setting: A multicentre prospective study

Application and internal validation of lung ultrasound score in COVID-19 setting: The ECOVITA observational study

BACKGROUND

The severe acute respiratory syndrome Coronarovirus-2 associated still causes a significant number of deaths and hospitalizations mainly by the development of respiratory failure. We aim to validate lung ultrasound score in order to predict mortality and the severity of the clinical course related to the need of respiratory support.

METHODS

In this prospective multicenter hospital-based cohort study, all adult patients with diagnosis of SARS-CoV-2 infection, performed by real-time reverse transcription polymerase chain reaction were included. Upon admission, all patients underwent blood gas analysis and lung ultrasound by expert operators. The acquisition of ultrasound scan was performed on 12 peculiar anatomic landmarks of the chest. Lung ultrasound findings were classified according to a scoring method, ranging 0 to 3: Score 0: normal A-lines. Score 1: multiple separated B-lines. Score 2: coalescent B-lines, alteration of pleural line. Score 3: consolidation area.

RESULTS

One thousand and seven patients were included in statistical analysis (male 62.4 %, mean age 66.3). Oxygen support was needed in 811 (80.5 %) patients. The median ultrasound score was 24 and the risk of having more invasive respiratory support increased in relation to higher values score computed. Lung ultrasound score showed negative strong correlation (rho: -0.71) with the P/F ratio and a significant association with in-hospital mortality (OR 1.11, 95 %CI 1.07-1.14; p < 0.001), even after adjustment with the following variables (age, sex, P/F ratio, SpO2, lactate, hypertension, chronic renal failure, diabetes, and obesity).

CONCLUSIONS

The novelty of this research corroborates and validates the 12-field lung ultrasound score as tool for predicting mortality and severity clinical course in COVID-19 patients. Baseline lung ultrasound score was associated with in-hospital mortality and requirement of intensive respiratory support and predict the risk of IOT among COVID-19 patients.

Predicting Hospitalization Length in Geriatric Patients Using Artificial Intelligence and Radiomics

(1) Background: Predicting hospitalization length for COVID-19 patients is crucial for optimizing resource allocation and patient management. Radiomics, combined with machine learning (ML), offers a promising approach by extracting quantitative imaging features from CT scans. The aim of the present study is to use and adapt machine learning (ML) architectures, exploiting CT radiomics information, and analyze algorithms' capability to predict hospitalization at the time of patient admission. (2) Methods: The original CT lung images of 168 COVID-19 patients underwent two segmentations, isolating the ground glass area of the lung parenchyma. After an isotropic voxel resampling and wavelet and Laplacian of Gaussian filtering, 92 intensity and texture radiomics features were extracted. Feature reduction was conducted by applying a last absolute shrinkage and selection operator (LASSO) to the radiomic features set. Three ML classification algorithms, linear support vector machine (LSVM), medium neural network (MNN), and ensemble subspace discriminant (ESD), were trained and validated through a 5-fold cross-validation technique. Model performance was assessed using accuracy, sensitivity, specificity, precision, F1-score, and the area under the receiver operating characteristic curve (AUC-ROC). (3) Results: The LSVM classifier achieved the highest predictive performance, with an accuracy of 86.0% and an AUC of 0.93. However, reliable outcomes are also registered when MNN and ESD architecture are used. (4) Conclusions: The study shows that radiomic features can be used to build a machine learning framework for predicting patient hospitalization duration. The findings suggest that radiomics-based ML models can accurately predict COVID-19 hospitalization length.

Molecular Diagnostic Yield and Safety Profile of Ultrasound-Guided Lung Biopsies: A Cross-Sectional Study

BACKGROUND

The recent advances in precision oncology for lung cancer treatment has focused attention on the importance of obtaining appropriate specimens for tissue diagnosis as well as comprehensive molecular profiling. CT scan-guided biopsies and bronchoscopy are currently the main procedures employed for tissue sampling. However, growing evidence suggests that ultrasound-guided biopsies may represent an effective as well as safe approach in this diagnostic area. This study explores the safety and the diagnostic yield for cancer molecular profiling in ultrasound-guided percutaneous lung lesion biopsies (US-PLLB).

METHODS

One hundred consecutive patients with suspected lung cancer, between January 2021 and May 2024, who had ultrasound-guided lung biopsies have been retrospectively analyzed. Molecular profiling was conducted with next-generation sequencing Genexus using Oncomine precision assay or polymerase chain reaction according to specimen quality. Qualitative immunohistochemical assay of programmed death ligand 1 (PD-L1) expression was evaluated by the Dako PD-L1 immunohistochemistry 22C3 pharmDx assay. The co-primary endpoints were the molecular diagnostic yield and the safety profile of US-guided lung biopsies.

RESULTS

From January 2021 to May 2024, 100 US-guided lung biopsies were carried out and 95 were considered for inclusion in the study. US-PLLB provided informative tissue for a histological evaluation in 93 of 95 patients with an overall diagnostic accuracy of 96.84% [Sensitivity: 92.63%; Specificity: 96.84%; PPV: 100%; NPV: 100%]. Sixty-Six patients were diagnosed with NSCLC (69.47%) and were considered for molecular diagnostic yield evaluation and PD-L1 testing. Four patients had malignant lymphoid lesions. US-PLLB was not adequate to achieve a final diagnosis in three patients (3.16%). Complete molecular profiling and PD-L1 evaluation were achieved in all patients with adenocarcinoma (molecular diagnostic yield: 100%). PD-L1 evaluation was achieved in 28 of 29 patients (96.55%) with either SCC or NOS lung cancer. The overall complication rate was 9.47% (n = 9). Six patients (6.31%) developed pneumothorax, while three patients (3.16%) suffered mild haemoptysis without desaturation.

CONCLUSIONS

According to our findings, US-guided lung biopsy is a safe, minimally invasive procedure in patients with suspected lung malignancies, providing an excellent diagnostic yield for both comprehensive molecular profiling and PD-L1 testing. In addition, our results suggest that US-guided biopsy may also be an effective diagnostic approach in patients with suspected lung lymphoma.

Diagnostic Accuracy of Ultrasound Guided Percutaneous Pleural Needle Biopsy for Malignant Pleural Mesothelioma

Background/Objectives: Ultrasound (US) has been progressively spreading as the most useful technique for guiding biopsies and fine-needle aspirations that are performed percutaneously. Malignant pleural mesothelioma (MPM) represents the most common malignant pleural tumour. Thoracoscopy represents the gold standard for diagnosis, although conditions hampering such diagnostic approach often coexist. The Objective was to determine whether ultrasound-guided percutaneous needle biopsy (US-PPNB) has a high diagnostic accuracy and represents a safe option for diagnosis of MPM. Methods: US-PPNB of pleural lesions suspected for MPM in patients admitted from January 2021 to June 2023 have been retrospectively analyzed. An 18-gauge semi-automatic spring-loaded biopsy system (Medax Velox 2®) was used by experienced pneumologists. The obtained specimens were histologically evaluated and defined as adequate or non-adequate for diagnosis according to whether the material was considered appropriate or not for immunohistochemistry (IHC) analysis. The primary objective of the study was the diagnostic yield for a tissue diagnosis. Results: US-PPNB was diagnostic of MPM in 15 out of 18 patients (sensitivity: 83.39%; specificity: 100%; PPV: 100%). Three patients with non-adequate US-PPNB underwent thoracoscopy for diagnosis. We found significant differences in terms of mean pleural lesion thickness between patients with adequate and not-adequate biopsy (15.4 mm (SD: 9.19 mm) and 3.77 mm (SD: 0.60 mm), p < 0.0010. In addition, a significant positive correlation has been observed between diagnostic accuracy and FDG-PET avidity value. Conclusions: US-PPNB performed by a pneumologist represents a valid procedure with a high diagnostic yield and accuracy for the diagnosis of MPM, and may be considered as an alternative option in patients who are not suitable for thoracoscopy.

CARdioimaging in Lung Cancer PatiEnts Undergoing Radical RadioTherapy: CARE-RT Trial

BACKGROUND

Non-small-cell lung cancer (NSCLC) is a common, steady growing lung tumour that is often discovered when a surgical approach is forbidden. For locally advanced inoperable NSCLC, the clinical approach consists of a combination of chemotherapy and radiotherapy, eventually followed by adjuvant immunotherapy, a treatment that is useful but may cause several mild and severe adverse effect. Chest radiotherapy, specifically, may affect the heart and coronary artery, impairing heart function and causing pathologic changes in myocardial tissues. The aim of this study is to evaluate the damage coming from these therapies with the aid of cardiac imaging.

METHODS

This is a single-centre, prospective clinical trial. Patients with NSCLC who are enrolled will undergo computed tomography (CT) and magnetic resonance imaging (MRI) before chemotherapy 3 months, 6 months, and 9-12 months after the treatment. We expect to enrol 30 patients in 2 years.

CONCLUSIONS

Our clinical trial will be an opportunity not only to highlight the timing and the radiation dose needed for pathological cardiac tissue changes to happen but will also provide useful data to set new follow-up schedules and strategies, keeping in mind that, more often than not, patients affected by NSCLC may present other heart- and lung-related pathological conditions.

COVID-19 Clinical Features and Outcomes in Elderly Patients during Six Pandemic Waves

Many elderly patients with severe SARS-CoV-2 infections and COVID-19 infections are admitted to intensive care units. Age was previously identified as an independent risk factor for death and contributed to the greater severity of COVID-19. The elderly may have diminished lung functions, poor reactions to artificial ventilation, and compromised immune systems. However, it is yet uncertain how each pandemic wave and the predominant SARS-CoV-2 strains contribute to varying results and how patient groups such as the elderly are impacted. Comparing six COVID-19 pandemic waves, the objective of this study was to examine the variation in case severity, symptomatology, ICU hospitalizations, and mortality among SARS-CoV-2-infected elderly individuals. The study followed a retrospective design, including 60 eligible patients older than 70 years in each of the six pandemic wave groups, after matching them by the number of comorbidities and gender. SARS-CoV-2 infection during the first, third, and fourth pandemic waves had a significantly higher risk of mortality for hospitalized patients. Confusion and dyspnea at admission were significant risk factors for ICU admission in elderly patients (β = 1.92, respectively β = 3.65). The laboratory parameters identified decreased lymphocytes (β = 2.11), elevated IL-6 (β = 1.96), and procalcitonin (β = 2.46) as the most significant risk factors. The third and fourth COVID-19 waves had considerably more severe infections (31.7% and 26.7%) than the sixth wave (13.3%). Median ICU stay and percentage of patients receiving oxygen support also differed across pandemic waves. However, mortality rates between the six pandemic waves were similar. The average length of hospitalization varied dramatically among the six pandemic waves. Although senior patients are more likely to have worse COVID-19 outcomes after hospitalization, this risk is mitigated by the greater prevalence of comorbidities and frailty among the elderly. The six pandemic waves that were specifically evaluated did not reveal considerably disproportionate variations in terms of patient mortality; however, during the fourth pandemic wave, there were likely more hospitalized patients with severe COVID-19 in Romania. It is probable that certain circulating SARS-CoV-2 strains were more infectious, resulting in an increase in infections and a strain on healthcare systems, which might explain the variations found in our research.

The Role of Lung Ultrasound in SARS-CoV-19 Pneumonia Management

Purpose: We aimed to assess the role of lung ultrasound (LUS) in the diagnosis and prognosis of SARS-CoV-2 pneumonia, by comparing it with High Resolution Computed Tomography (HRCT). Patients and methods: All consecutive patients with laboratory-confirmed SARS-CoV-2 infection and hospitalized in COVID Centers were enrolled. LUS and HRCT were carried out on all patients by expert operators within 48−72 h of admission. A four-level scoring system computed in 12 regions of the chest was used to categorize the ultrasound imaging, from 0 (absence of visible alterations with ultrasound) to 3 (large consolidation and cobbled pleural line). Likewise, a semi-quantitative scoring system was used for HRCT to estimate pulmonary involvement, from 0 (no involvement) to 5 (>75% involvement for each lobe). The total CT score was the sum of the individual lobar scores and ranged from 0 to 25. LUS scans were evaluated according to a dedicated scoring system. CT scans were assessed for typical findings of COVID-19 pneumonia (bilateral, multi-lobar lung infiltration, posterior peripheral ground glass opacities). Oxygen requirement and mortality were also recorded. Results: Ninety-nine patients were included in the study (male 68.7%, median age 71). 40.4% of patients required a Venturi mask and 25.3% required non-invasive ventilation (C-PAP/Bi-level). The overall mortality rate was 21.2% (median hospitalization 30 days). The median ultrasound thoracic score was 28 (IQR 20−36). For the CT evaluation, the mean score was 12.63 (SD 5.72), with most of the patients having LUS scores of 2 (59.6%). The bivariate correlation analysis displayed statistically significant and high positive correlations between both the CT and composite LUS scores and ventilation, lactates, COVID-19 phenotype, tachycardia, dyspnea, and mortality. Moreover, the most relevant and clinically important inverse proportionality in terms of P/F, i.e., a decrease in P/F levels, was indicative of higher LUS/CT scores. Inverse proportionality P/F levels and LUS and TC scores were evaluated by univariate analysis, with a P/F−TC score correlation coefficient of −0.762, p < 0.001, and a P/F−LUS score correlation coefficient of −0.689, p < 0.001. Conclusions: LUS and HRCT show a synergistic role in the diagnosis and disease severity evaluation of COVID-19.

Integrated Basic Heart and Lung Ultrasound Examination for the Differentiation between Bacterial Pneumonia and Lung Neoplasm in Dogs—A New Diagnostic Algorithm

Simple Summary

Dyspnea is a highly alarming sign both for dog owners and veterinarians. Although its recognition is usually easy due to prominent suffering of an animal, finding its cause is challenging because many diseases of the heart, lungs, and airways may manifest themselves this way. Echocardiography and lung ultrasound allow for relatively quick and accurate identification of heart diseases. Dyspneic dogs without a heart and upper airway disease are usually suspected of either bacterial pneumonia or lung neoplasm. Although prognosis in these two conditions is diametrically different, differentiation between them is challenging. Chest radiography is performed in a lateral position, which is barely tolerated by a dyspneic dog, and intensive chest movements often make X-ray scans inconclusive. Computed tomography, although much more accurate, requires general anesthesia, which is difficult and potentially life-threating in a dyspneic dog. Therefore, lung ultrasound, which can be performed quickly in a conscious dog, standing or in sternal position, seems to be the method of choice. We develop and evaluate a diagnostic algorithm based on detection of three well-defined abnormalities in the lung ultrasound. The algorithm allows one to distinguish between bacterial pneumonia and lung neoplasm in a dyspneic dog with high probability of a conclusive result (91%) and high accuracy (>95%).

Abstract

The diagnostics of two of the most prevalent lung diseases in dogs, bacterial pneumonia (BP) and lung neoplasm (LN), are challenging as their clinical signs are identical and may also occur in extrapulmonary diseases. This study aims to identify ultrasonographic criteria and develop a lung ultrasound (LUS)-based diagnostic algorithm which could help distinguish between these two conditions. The study is carried out in 66 dyspneic dogs in which a heart disease was excluded using echocardiography. Based on imaging and laboratory diagnostic tests, as well as follow-up, the dogs are classified into LN (35 dogs) and BP (31 dogs) groups. LUS is performed at admission and the presence of seven lung abnormalities (pleural thickening, B-lines, subpleural consolidations, hepatization with or without aeration, nodule sign and mass classified together as a tumor, and free pleural fluid) and classification and regression trees are used to develop an LUS-based diagnostic algorithm. Distribution of all LUS abnormalities except for aerations differs significantly between groups; however, their individual differentiating potential is rather low. Therefore, we combine them in an algorithm which allows for definitive classification of 60 dogs (91%) (32 with LN and 28 with BP) with correct diagnosis of LN and BP in 31 dogs and 27 dogs, respectively.

Ultrasound Image under Artificial Intelligence Algorithm to Evaluate the Intervention Effect of Accelerated Rehabilitation Surgery Nursing on Laparoscopic Hysterectomy

To explore the application value of accelerated rehabilitation surgery (ERAS) nursing in laparoscopic total hysterectomy, 120 patients who underwent laparoscopic total hysterectomy for benign uterine diseases in the hospital were selected as the research object. According to different nursing schemes, they were divided into 60 cases in the experimental group (ERAS nursing program) and 60 cases in the control group (traditional perioperative nursing). All patients underwent postoperative ultrasonography, and the intraoperative and postoperative rehabilitation indexes of the two groups were analyzed. Moreover, an improved standard Capon beamforming (ISCB) algorithm is proposed, which is compared with SCB algorithm, sequential regression algorithm (SER), and recursive least square (RLS) algorithm. The results showed that the center average power and background average power (−46.92, −33.85) of the ISCB algorithm were significantly lower than those of SCB algorithm (−36.18, −23.64), SER algorithm (−39.02, −27.31), and RLS algorithm (−34.88, −24.66), while the contrast and resolution (19.11, 15.57) were significantly higher than those of SCB algorithm (12.74, 9.01), SER algorithm (13.86, 7.89), and RLS algorithm (13.26, 8.26) $\left(P<0.05\right)$ . The anal exhaust time (11.84 ± 2.15 hours), analgesic effect score (3.37 ± 1.03 points), hospitalization days (3.72 ± 0.74 days), and hospitalization expenses (11859.03 ± 735.24 ¥) in the experimental group were significantly lower than those in the control group (20.95 ± 3.44 hours, 6.12 ± 1.46 points, 5.48 ± 0.91 days, 16135.22 ± 680.55 ¥) $\left(P<0.05\right)$ . The score of NRS evaluation scale in the experimental group (2.28 ± 0.37) was significantly better than that in the control group (4.09 ± 0.65) $\left(P<0.05\right)$ . The proportion of patients in the experimental group (very satisfied + satisfied + generally satisfied) (100%) was significantly better than that in the control group (71%), and the difference was statistically significant $\left(P<0.05\right)$ . In the experimental group, there were 2 cases of postoperative fever, 1 case of nausea and vomiting, and 2 cases of lower extremity venous thrombosis. In the control group, there were 4 cases of postoperative fever, 4 cases of nausea and vomiting, and 2 cases of lower extremity venous thrombosis. In summary, ultrasound imaging based on the ISCB algorithm can display the pelvic floor structure of patients undergoing laparoscopic total hysterectomy with high quality and improve the diagnostic rate of doctors. ERAS nursing can accelerate patients’ postoperative rehabilitation, reduce postoperative pain, and improve patients’ satisfaction. It was worthy to be popularized and applied in the clinic.

Lung Ultrasound in COVID-19: Clinical Correlates and Comparison with Chest Computed Tomography

Lung ultrasound (LUS) and chest computed tomography (chest CT) are largely employed to evaluate coronavirus disease 2019 (COVID-19) pneumonia. We investigated semi-quantitative LUS and CT scoring in hospitalized COVID-19 patients. LUS and chest CT were performed within 24 h upon admission. Both were analyzed according to semi-quantitative scoring systems. Subgroups were identified according to median LUS score. Patients within higher LUS score group were older (79 vs 60 years, p<0.001), had higher C-reactive protein (CRP) (7.2 mg/dl vs 1.3 mg/dl, p<0.001) and chest CT score (10 vs 4, p=0.027) as well as lower PaO2/FiO2 (286 vs 356, p=0.029) as compared to patients within lower scores. We found a significant correlation between scores (r=0.390, p=0.023). Both LUS and CT scores correlated directly with patients age (r=0.586, p<0.001 and r=0.399, p=0.021 respectively) and CRP (r=0.472, p=0.002 and r=0.518, p=0.002 respectively), inversely with PaO2/FiO2 (r=-0.485, p=0.003 and r=-0.440, p=0.017 respectively). LUS score only showed significant correlation with hs-troponin T, NT-pro-BNP, and creatinine (r=0.433, p=0.019; r=0.411, p=0.027, and r=0.497, p=0.001, respectively). Semi-quantitative bedside LUS is related to the severity of COVID-19 pneumonia similarly to chest CT. Correlation of LUS score with markers of cardiac and renal injury suggests that LUS might contribute to a more comprehensive evaluation of this heterogeneous population.

Remarkable vessel enlargement within lung consolidation in COVID-19 compared to AH1N1 pneumonia: A retrospective study in Italy

Purpose

To investigate the early CT findings in COVID-19 pneumonia as compared to influenza A virus H1N1 (AH1N1), with focus on vascular enlargement within consolidation or ground glass opacity (GGO) areas.

Methods

50 patients with COVID-19 pneumonia were retrospectively compared to 50 patients with AH1N1 pneumonia diagnosed during the 2009 pandemic. Two radiologists reviewed chest CT scans independently and blindly, with discordance resolved by consensus. Dilated or tortuous vessels within hyperdense lesions were recorded.

Results

COVID-19 pneumonia presented with bilateral (96%), peripheral areas of GGO (22%), consolidation (4%) or combined GGO-consolidation (74%). The vascular enlargement sign in COVID-19 pneumonia was much more commonly present in COVID-19 (45/50, 90%) versus AH1N1 pneumonia (12/50, 24%) (p < 0.001). Vascular enlargement was more often present in lower lobes with a peripheral distribution.

Conclusions

Vascular enlargement in consolidative/GGO areas may represent a reasonably common early CT marker in COVID-19 patients and is of uncertain etiology. Although speculative, theoretical mechanisms could potentially reflect acute inflammatory changes, pulmonary endothelial activation, or acute stasis. Further studies are necessary to verify specificity and to study if prognostic for clinical outcomes.

Recommendations for Lung Ultrasound in Internal Medicine

A growing amount of evidence prompts us to update the first version of recommendations for lung ultrasound in internal medicine (POLLUS-IM) that was published in 2018. The recommendations were established in several stages, consisting of: literature review, assessment of literature data quality (with the application of QUADAS, QUADAS-2 and GRADE criteria) and expert evaluation carried out consistently with the modified Delphi method (three rounds of on-line discussions, followed by a secret ballot by the panel of experts after each completed discussion). Publications to be analyzed were selected from the following databases: Pubmed, Medline, OVID, and Embase. New reports published as of October 2019 were added to the existing POLLUS-IM database used for the original publication of 2018. Altogether, 528 publications were systematically reviewed, including 253 new reports published between September 2017 and October 2019. The new recommendations concern the following conditions and issues: pneumonia, heart failure, monitoring dialyzed patients' hydration status, assessment of pleural effusion, pulmonary embolism and diaphragm function assessment. POLLUS-IM 2020 recommendations were established primarily for clinicians who utilize lung ultrasound in their everyday clinical work.

COVID-19 and the elderly: insights into pathogenesis and clinical decision-making

The elderly may represent a specific cluster of high-risk patients for developing COVID-19 with rapidly progressive clinical deterioration. Indeed, in older individuals, immunosenescence and comorbid disorders are more likely to promote viral-induced cytokine storm resulting in life-threatening respiratory failure and multisystemic involvement. Early diagnosis and individualized therapeutic management should be developed for elderly subjects based on personal medical history and polypharmacotherapy. Our review examines the pathogenesis and clinical implications of ageing in COVID-19 patients; finally, we discuss the evidence and controversies in the management in the long-stay residential care homes and aspects of end-of-life care for elderly patients with COVID-19.