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Sinusoidal obstruction syndrome/veno‐occlusive disease (SOS/VOD) is a life‐threatening complication which can develop after haemopoietic stem cell transplantation (HSCT) and some antibody–drug conjugates. Several SOS/VOD diagnostic and management guidelines exist, with the most recent and refined being the European Society for Blood and Marrow Transplantation adult and paediatric guidelines. Timely diagnosis and effective management (including the availability of therapeutic options) significantly contribute to improved patient outcomes. In Australia and New Zealand, there is variability in clinical practice and access to SOS/VOD therapies. This review aims to summarise the current evidence for SOS/VOD diagnosis, prevention and treatment and to provide recommendations for SOS/VOD in the context of contemporary Australasian HSCT clinical practice. [ABSTRACT FROM AUTHOR]

Background: The CARDOT scores have been developed for prediction of respiratory complications after thoracic surgery. This study aimed to externally validate the CARDOT score and assess the predictive value of preoperative neutrophil-to-lymphocyte ratio (NLR) for postoperative respiratory complication. Methods: A retrospective cohort study of consecutive thoracic surgical patients at a single tertiary hospital in northern Thailand was conducted. The development and validation datasets were collected between 2006 and 2012 and from 2015 to 2021, respectively. Six prespecified predictive factors were identified, and formed a predictive score, the CARDOT score (chronic obstructive pulmonary disease, American Society of Anesthesiologists physical status, right-sided operation, duration of surgery, preoperative oxygen saturation on room air, thoracotomy), was calculated. The performance of the CARDOT score was evaluated in terms of discrimination by using the area under the receiver operating characteristic (AuROC) curve and calibration. Results: There were 1086 and 1645 patients included in the development and validation datasets. The incidence of respiratory complications was 15.7% (171 of 1086) and 22.5% (370 of 1645) in the development and validation datasets, respectively. The CARDOT score had good discriminative ability for both the development and validation datasets (AuROC 0.789 (95% CI 0.753–0.827) and 0.758 (95% CI 0.730–0.787), respectively). The CARDOT score showed good calibration in both datasets. A high NLR (≥ 4.5) significantly increased the risk of respiratory complications after thoracic surgery (P < 0.001). The AuROC curve of the validation cohort increased to 0.775 (95% CI 0.750–0.800) when the score was combined with a high NLR. The AuROC of the CARDOT score with the NLR showed significantly greater discrimination power than that of the CARDOT score alone (P = 0.008). Conclusions: The CARDOT score showed a good discriminative performance in the external validation dataset. An addition of a high NLR significantly increases the predictive performance of CARDOT score. The utility of this score is valuable in settings with limited access to preoperative pulmonary function testing. [ABSTRACT FROM AUTHOR]

Simple Summary: Lung cancer diagnosis often requires invasive procedures due to the lack of effective early detection methods, particularly the insufficient specificity of current screening approaches. This study aimed to develop and validate epigenetic biomarkers from bronchoalveolar lavage fluid (BALF) exosome specimens capable of discriminating between lung cancer and benign lung diseases suspected of lung malignancy. Our findings indicate that combinations of epigenetic biomarkers derived from BALF exosomes can effectively support the discrimination of these clinical conditions with high specificity. Benign lung diseases are common and often do not require specific treatment, but they pose challenges in the distinguishing of them from lung cancer during low-dose computed tomography (LDCT). This study presents a comprehensive methylation analysis using real-time PCR for minimally invasive diagnoses of lung cancer via employing BALF exosome DNA. A panel of seven epigenetic biomarkers was identified, exhibiting specific methylation patterns in lung cancer BALF exosome DNA. This panel achieved an area under the curve (AUC) of 0.97, with sensitivity and specificity rates of 88.24% and 97.14%, respectively. Each biomarker showed significantly higher mean methylation levels (MMLs) in both non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) compared to non-cancer groups, with fold changes from 1.7 to 13.36. The MMLs of the biomarkers were found to be moderately elevated with increasing patient age and smoking history, regardless of sex. A strong correlation was found between the MMLs and NSCLC stage progression, with detection sensitivities of 79% for early stages and 92% for advanced stages. In the validation cohort, the model demonstrated an AUC of 0.95, with 94% sensitivity and specificity. Sensitivity for early-stage NSCLC detection improved from 88.00% to 92.00% when smoking history was included as an additional risk factor. [ABSTRACT FROM AUTHOR]

This paper aims to address the detection of COVID-19 by developing an accurate and efficient diagnostic system using chest X-ray images. The research utilizes open-source Kaggle data comprising four categories: COVID-19, Lung-Opacity, Normal, and Viral Pneumonia. The proposed system employs convolutional neural networks (CNNs), including VGG19, RNN-LSTM, and inceptionv3. Results vary among the methodologies, with VGG19 achieving 26% accuracy, RNN-LSTM attaining 25% accuracy (28% with preprocessing), and inceptionv3 with histogram equalization achieving 83% accuracy. A CNN designed from scratch demonstrates the highest performance, with an accuracy of 93% (96% with histogram equalization). The findings emphasize the potential of AI techniques in enhancing disease diagnosis, particularly in distinguishing COVID-19 from other conditions, thereby facilitating timely and effective interventions. [ABSTRACT FROM AUTHOR]

Simple Summary: Patients suffering from melanoma or metastatic cutaneous squamous cell carcinoma profit from immune checkpoint blockade as a therapy. Pneumonitis is a rare but potentially fatal immune-related adverse event, and even more subclinical damage is most likely to occur. The sensitive marker lung clearance index, integrated into pulmonary function testing, was used to detect possible early pulmonary impairment. As slightly impaired lung function could be observed, we recommend the sensitive marker lung clearance index as a diagnostic method that should be implemented into the clinical routine follow-ups during immune checkpoint therapy in order to enable possible further recommendations. Background: Immune checkpoint blockade (ICB) has presented a breakthrough in the treatment of malignant tumors and increased the overall survival of patients with various tumor entities. ICB may also cause immune-related adverse events, such as pneumonitis or interstitial lung disease. The lung clearance index (LCI) is a multiple-breath washout technique offering information on lung pathology in addition to conventional spirometry. It measures the degree of pulmonary ventilation inhomogeneity and allows early detection of pulmonary damage, especially that to peripheral airways. Methods: This cross-sectional study compared the lung function of patients with melanoma or metastatic cutaneous squamous cell carcinoma who received programmed cell death 1 (PD-1) and cytotoxic T-Lymphocyte-associated Protein 4 (CTLA-4) antibodies, alone or in combination, to age- and sex-matched controls. Lung function was assessed using spirometry, according to American Thoracic Society and European Respiratory Society standards, the LCI, and a diffusion capacity of carbon monoxide (DLCO) measurement. Results: Sixty-one screened patients and thirty-eight screened controls led to nineteen successfully included pairs. The LCI in the ICB-treated patients was 8.41 ± 1.15 (mean ± SD), which was 0.32 higher compared to 8.07 ± 1.17 in the control group, but the difference was not significant (p = 0.452). The patients receiving their ICB therapy for under five months showed a significantly lower LCI (7.98 ± 0.77) compared to the ICB patients undergoing therapy for over five months (9.63 ± 1.22) at the point of testing (p = 0.014). Spirometric analysis revealed that the forced expiratory volume between 25 and 75% of the forced vital capacity (FEF25–75%) in the ICB-treated patients was significantly reduced (p = 0.047) compared to the control group. DLCO (%predicted and adjusted for hemoglobin) was 94.4 ± 19.7 in the ICB patients and 93.4 ± 21.7 in the control group (p = 0.734). Conclusions: The patients undergoing ICB therapy showed slightly impaired lung function compared to the controls. Longer periods of ICB treatment led to deterioration of the LCI, which may be a sign of a subclinical inflammatory process. The LCI is feasible and may be easily integrated into the clinical daily routine and could contribute to early detection of pulmonary (auto-)inflammation. [ABSTRACT FROM AUTHOR]

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The human voice has the potential to serve as a valuable biomarker for the early detection, diagnosis, and monitoring of pediatric conditions. This scoping review synthesizes the current knowledge on the application of artificial intelligence (AI) in analyzing pediatric voice as a biomarker for health. The included studies featured voice recordings from pediatric populations aged 0–17 years, utilized feature extraction methods, and analyzed pathological biomarkers using AI models. Data from 62 studies were extracted, encompassing study and participant characteristics, recording sources, feature extraction methods, and AI models. Data from 39 models across 35 studies were evaluated for accuracy, sensitivity, and specificity. The review showed a global representation of pediatric voice studies, with a focus on developmental, respiratory, speech, and language conditions. The most frequently studied conditions were autism spectrum disorder, intellectual disabilities, asphyxia, and asthma. Mel-Frequency Cepstral Coefficients were the most utilized feature extraction method, while Support Vector Machines were the predominant AI model. The analysis of pediatric voice using AI demonstrates promise as a non-invasive, cost-effective biomarker for a broad spectrum of pediatric conditions. Further research is necessary to standardize the feature extraction methods and AI models utilized for the evaluation of pediatric voice as a biomarker for health. Standardization has significant potential to enhance the accuracy and applicability of these tools in clinical settings across a variety of conditions and voice recording types. Further development of this field has enormous potential for the creation of innovative diagnostic tools and interventions for pediatric populations globally. [ABSTRACT FROM AUTHOR]

Pulmonologists may be involved in managing pulmonary diseases in children with complex clinical pictures without a diagnosis. Moreover, they are routinely involved in the multidisciplinary care of children with rare diseases, at baseline and during follow-up, for lung function monitoring. Lysosomal storage diseases (LSDs) are a group of genetic diseases characterised by a specific lysosomal enzyme deficiency. Despite varying pathogen and organ involvement, they are linked by the pathological accumulation of exceeding substrates, leading to cellular toxicity and subsequent organ damage. Less severe forms of LSDs can manifest during childhood or later in life, sometimes being underdiagnosed. Respiratory impairment may stem from different pathogenetic mechanisms, depending on substrate storage in bones, with skeletal deformity and restrictive pattern, in bronchi, with obstructive pattern, in lung interstitium, with altered alveolar gas exchange, and in muscles, with hypotonia. This narrative review aims to outline different pulmonary clinical findings and a diagnostic approach based on key elements for differential diagnosis in some treatable LSDs like Gaucher disease, Acid Sphingomyelinase deficiency, Pompe disease and Mucopolysaccharidosis. Alongside their respiratory clinical aspects, which might overlap, we will describe radiological findings, lung functional patterns and associated symptoms to guide pediatric pulmonologists in differential diagnosis. The second part of the paper will address follow-up and management specifics. Recent evidence suggests that new therapeutic strategies play a substantial role in preventing lung involvement in early-treated patients and enhancing lung function and radiological signs in others. Timely diagnosis, driven by clinical suspicion and diagnostic workup, can help in treating LSDs effectively. [ABSTRACT FROM AUTHOR]

Background: COVID-19-associated pulmonary fibrosis remains frequent. This study aimed to investigate pulmonary redox balance in COVID-19 ARDS patients and possible relationship with pulmonary fibrosis and long-term lung abnormalities. Methods: Baseline data, chest CT fibrosis scores, N-terminal peptide of alveolar collagen III (NT-PCP-III), transforming growth factor (TGF)-β1, superoxide dismutase (SOD), reduced glutathione (GSH), oxidized glutathione (GSSG) and malondialdehyde (MDA) in bronchoalveolar lavage fluid (BALF) were first collected and compared between SARS-CoV-2 RNA positive patients with moderate to severe ARDS (n = 65, COVID-19 ARDS) and SARS-CoV-2 RNA negative non-ARDS patients requiring mechanical ventilation (n = 63, non-ARDS). Then, correlations between fibroproliferative (NT-PCP-III and TGF-β1) and redox markers were analyzed within COVID-19 ARDS group, and comparisons between survivor and non-survivor subgroups were performed. Finally, follow-up of COVID-19 ARDS survivors was performed to analyze the relationship between pulmonary abnormalities, fibroproliferative and redox markers 3 months after discharge. Results: Compared with non-ARDS group, COVID-19 ARDS group had significantly elevated chest CT fibrosis scores (p < 0.001) and NT-PCP-III (p < 0.001), TGF-β1 (p < 0.001), GSSG (p < 0.001), and MDA (p < 0.001) concentrations on admission, while decreased SOD (p < 0.001) and GSH (p < 0.001) levels were observed in BALF. Both NT-PCP-III and TGF-β1 in BALF from COVID-19 ARDS group were directly correlated with GSSG (p < 0.001) and MDA (p < 0.001) and were inversely correlated with SOD (p < 0.001) and GSH (p < 0.001). Within COVID-19 ARDS group, non-survivors (n = 28) showed significant pulmonary fibroproliferation (p < 0.001) with more severe redox imbalance (p < 0.001) than survivors (n = 37). Furthermore, according to data from COVID-19 ARDS survivor follow-up (n = 37), radiographic residual pulmonary fibrosis and lung function impairment improved 3 months after discharge compared with discharge (p < 0.001) and were associated with early pulmonary fibroproliferation and redox imbalance (p < 0.01). Conclusions: Pulmonary redox imbalance occurring early in COVID-19 ARDS patients drives fibroproliferative response and increases the risk of death. Long-term lung abnormalities post-COVID-19 are associated with early pulmonary fibroproliferation and redox imbalance. Highlights: Altering pulmonary redox balance drives an early pulmonary fibroproliferative response in COVID-19 ARDS. Pulmonary redox imbalance and fibroproliferation increase the risk of death in COVID-19 ARDS. Approximately 60% of moderate to severe COVID-19 ARDS survivors suffer residual pulmonary fibrosis and lung function impairment 3 months after hospital discharge. Pulmonary redox imbalance and fibroproliferation affect the resolution of residual pulmonary fibrosis and recovery from lung function impairment post-COVID-19. [ABSTRACT FROM AUTHOR]

Introduction: Today, the increasing number of incidentally detected peripheral pulmonary lesions (PPLs) within and outside lung cancer screening trials is a diagnostic challenge. This fact encourages further improvement of diagnostic procedures to increase the diagnostic yield of transbronchial biopsy, which has been shown to have a low complication rate. The purpose of this study was to evaluate the safety and feasibility of a new ultrathin 1.1 cryoprobe that can be placed through an ultrathin bronchoscope (UTB) using fluoroscopy and radial endobronchial ultrasonography (rEBUS) navigation for assessing PPLs. Methods: Thirty-five patients with PPL less than 4 cm in diameter were prospectively enrolled to receive transbronchial cryobiopsies (TBCBs) using the ultrathin 1.1-mm cryoprobe. Navigation to the PPL was accomplished with the UTB. Under rEBUS and fluoroscopy guidance up to 4 cryobiopsies were obtained. The sample sizes of the biopsies were compared to a historic collective derived from a 1.9-mm cryoprobe and standard forceps. The feasibility and safety of the procedure, the cumulative and overall diagnostic yield, and the cryobiopsy sizes were evaluated. Results: After detection with the rEBUS, TBCB was collected from 35 PPLs, establishing a diagnosis in 25 cases, corresponding to an overall diagnostic yield of 71.4%. There was no difference in diagnostic yield for PPL <20 mm or ≥20 mm. All cryobiopsies were representative with a mean tissue area of 11.9 ± 4.3 mm2, which was significantly larger compared to the historic collective (p = 0.003). Six mild and four moderate bleeding events and 1 case of pneumothorax were observed. Conclusions: Using the ultrathin 1.1-mm cryoprobe combined with an UTB for rEBUS-guided TBCB of PPL is feasible and safe. This diagnostic approach improves bronchoscopic techniques for diagnosing peripheral lung lesions and may contribute to improve diagnosis of lung cancer even in small PPL. [ABSTRACT FROM AUTHOR]

The aim - to determine the diagnostic value of lung ultrasound parameters in predicting outcomes of coronavirus disease 2019 (COVID-19) in oxygen-dependent patients requiring intensive care unit treatment. Materials and methods. We examined 105 patients with COVID-19 who needed supplemental oxygen and were treated in the Department of Anesthesiology and Intensive Care. The age of patients ranged between 39 and 80 years, 63 participants were male and 42 - female. To determine the diagnostic value of lung ultrasound parameters in predicting the severe course of COVID-19 in oxygen-dependent patients, they were divided into groups: Group I - recovered patients (n = 39); Group II - patients with a fatal outcome (n = 66). In all the patients, the diagnosis of COVID-19 was confirmed by RNA-SARS-CoV-2 detection in nasopharyngeal swab specimens. The patients were examined and treated according to the Protocol of the Ministry of Health of Ukraine. The lung ultrasound protocol used in the study included 14 lung examination zones and a score of lung tissue infiltration degree from 0 to 3 points. Statistical processing of the data was performed with Statistica for Windows 13 (StatSoft Inc., No. JPZ804I382130ARCN10-J). Results. In oxygen-dependent patients with severe COVID-19 and a fatal outcome, infiltrative changes in the lung parenchyma were more severe based on the lung ultrasound total score both at the time of admission (p < 0.01) and after 5 days of treatment (p < 0.01). The cutoff score of ≥19 at the time of hospitalization (AUC = 0.753, p < 0.01; sensitivity - 76.9 %, specificity - 68.2 %) and ≥17 after 5 days of treatment (AUC = 0.799, p < 0.01; sensitivity - 71.4 %, specificity - 92.1 %) had a prognostic value for assessing the risk of death in oxygen-dependent patients with severe COVID-19. A lung ultrasound score >19 at the time of admission increased the risk of death by 2.96 times (RR = 2.96, 95 % CI 1.43-2.87, p < 0.001). Lung ultrasound found pleural effusion only in oxygen-dependent COVID-19 patients who died. In the treatment dynamics after 5 days, the rate of pleural effusion detection in this group of patients was three times increased (from 9.1 % to 27.3 %, p < 0.01). Conclusions. The study has revealed the diagnostic value of lung ultrasound parameters in predicting outcomes of COVID-19 in oxygen-dependent patients requiring intensive care unit treatment. Cutoffs of the total score characterizing the degree of lung tissue infiltration have been determined, that allowing to assert a high probability for a lethal outcome of the disease. [ABSTRACT FROM AUTHOR]

Immunocompromised patients are prone to various opportunistic infections. Most of the infections are easily detectable through staining, culture, and polymerase chain reaction techniques. Nevertheless, it is also important to have wet smear examinations of samples. We present a case of pneumonia in a post-transplant recipient who was on immunosuppressants and detected to have an infection from the parasite, lophomonas blattarum, which usually resides in the hindgut of cockroaches. [ABSTRACT FROM AUTHOR]

Bullous lung disease caused by tuberculosis is rare, and complications have a poor prognosis with uncertain pathophysiologic mechanisms. We describe a 29-year-old male patient who was admitted to the emergency department due to bilateral tension pneumothorax, which was complicated by bronchopleural fistula. This was managed with the placement of chest tubes, continuity of anti-TB drug treatment, and Heimlich valve placement. [ABSTRACT FROM AUTHOR]

Background: Aorto‐left ventricular tunnel (ALVT) is a paravalvular communication between aorta and left ventricle. It is one of the rare congenital heart diseases which could present with heart failure. Case presentation: A case of ALVT was diagnosed in infancy. Preliminary assessment was possible using conventional echocardiography; however, functional assessment and accurate anatomy of ALVT were further verified via variable imaging modalities starting from speckle tracking and three‐dimensional echocardiography to cardiac CT angiogram. The tunnel was successfully repaired with uneventful recovery. Conclusions: Multimodality imaging can accurately assess cardiac function and demonstrate the anatomy of ALVT noninvasively to plan for successful intervention. [ABSTRACT FROM AUTHOR]

Non-tuberculous mycobacteria (NTM) are ubiquitous environmental organisms that can cause significant disease in both immunocompromised and immunocompetent individuals. The incidence of NTM pulmonary disease (NTM-PD) is rising globally. Diagnostic challenges persist and treatment efficacy is variable. This article provides an overview of NTM-PD for clinicians. We discuss how common it is, who is at risk, how it is diagnosed and the multidisciplinary approach to its clinical management. [ABSTRACT FROM AUTHOR]

While rare, the likelihood of encountering a case of a pulmonary endemic mycosis (PEM) in the UK is increasing. Diagnosis may be challenging, often leading to considerable delay to appropriate treatment. Clinical suspicion must be present for respiratory disease, particularly in the immunocompromised or in those not responding to empiric treatment approaches, and an extended travel history should be obtained. This article summarises the epidemiology of PEM, key clinical features, diagnostic strategies and management. [ABSTRACT FROM AUTHOR]

Background: Nontuberculous mycobacteria (NTM) represent a broad spectrum of acid-fast bacilli, excluding the pathogens responsible for tuberculosis and leprosy. Over 200 species have been identified and classified as NTM, based on shared phenotypic characteristics. These bacteria are prevalent in diverse environments and are implicated in NTM pulmonary disease (NTM-PD), resulting from interactions between the host, the environment, and the microorganism. Current Concepts: Diagnosing NTM-PD necessitates a comprehensive approach. It is essential to identify the risk factors, including underlying lung conditions, compromised immune responses, and other host-specific factors. The clinical diagnosis considers pulmonary or systemic symptoms aligned with the disease and the exclusion of alternative pulmonary disorders. Radiological evaluations, such as chest X-rays and computed tomography scans reveal patterns indicative of the disease, including fibrocavitary and nodular bronchiectatic forms. Microbiological criteria are fundamental to the diagnostic process and require a minimum of two positive cultures from separate sputum samples or a single positive result from invasive techniques, such as bronchoscopy or biopsies. Discussion and Conclusion: As there are multiple phenotypes of NTM-PD, it is necessary to assess the likelihood of the disease in individuals with increased risk factors. A combination of the clinical, radiological, and microbiological criteria is essential for the accurate diagnosis of NTM-PD. Once diagnosed, a thorough assessment is necessary to guide appropriate management decisions. [ABSTRACT FROM AUTHOR]

Introduction: The association between Mycobacterium tuberculosis and the Human Immunodeficiency Virus can accelerate the deterioration of immunological functions. The risks are even more accentuated in the situation of a Non-tuberculous Mycobacterium and Mycobacterium tuberculosis co-infection. Case presentation: We present the case of a 59-year-old male patient, who was admitted at the hospital with non-specific symptoms. Further investigations reveal a remarkable particularity about the case: The infection with Mycobacterium tuberculosis was urogenital, whereas the one with Non-tuberculous mycobacteria was pulmonary. Conclusion: Both Mycobacterium tuberculosis and Non-tuberculous strains can exist within the same infection, posing great difficulties for diagnosis, as well as the treatment scheme. [ABSTRACT FROM AUTHOR]

Neutrosophic ranking studies are an important part of medicine that determines the ranks of tests, risk factors, attributes, and medical suppliers. Neutrosophic clustering in healthcare can split data into groups (called clusters) to determine usage patterns for purposes, in which objects within the same cluster have similar properties and objects of different clusters have different properties. Like neutrosophic clustering, neutrosophic classification studies are also a data mining technique. Neutrosophic pattern recognition is a machine learning process to decipher the underlying patterns in the concerned subjects. Neutrosophic time series analysis tries to find patterns and rules depending on time, neutrosophic recognition of medical images belongs to this type of study. This article comes as an attempt to review and shed light on almost all studies and subjects that used neutrosophic studies and algorithms related to medicine and healthcare for dozens of articles and authors.

The lung disease diagnosis expert system utilizes human knowledge to diagnose various conditions affecting the lung. Diseases caused by fungal or bacterial infection in the organ can cause inflammation as well as death when it is not detected on time. A standard method to diagnose these conditions is the use of a chest X-ray (CXR), which requires careful examination of the image by an expert. In this study, several CNN and SVM architectural models were proposed to classify CXR images to diagnose whether a person has COVID-19, Viral Pneumonia, Bacterial Pneumonia, Tuberculosis (TB), and Normal. The experiment showed that InceptionV3 had the best results compared to other CNN architectures and SVM. Classification accuracy, precision, recall, and f1-score of CXR images for COVID-19, Viral Pneumonia, Bacterial Pneumonia, TB, and Normal were 0.86, 0.91, 0.91, and 0.91, respectively. This study was based on a deep learning system with different CNN and SVM architectures that can work well on the CXR images dataset for diagnosing lung disease. [ABSTRACT FROM AUTHOR]

Background: Hematologic malignancies are the fifth most common malignancies worldwide. Pulmonary symptoms are among the patient's common complaints. Early diagnosis based on patient symptoms, laboratory testing, and imaging may lead to an appropriate therapeutic approach. Objectives: To evaluate thoracic computed tomography (CT) scan findings in known cases of hematologic malignancy with acute respiratory symptoms. Methods: Across-sectional study was conducted on 200 patients with hematologic malignancies admitted to Khansari cancer center for acute pulmonary symptoms, from December 2019 to May 2020. Collected data included demographic data, physical examination, laboratory tests and findings of thoracic CT images. Descriptive analysis and chi-Square test were performed to analyze the data using SPSS version 20. Results: Non-Hodgkin lymphoma was the most common malignancy, accounting for 48% of total cases. The most common radio- logical findings included atelectasis (49%), followed by pleural effusion (42%), mediastinal lymphadenopathy(38.5%), consolidation (37%), and ground-glass opacities (33.5%). Mediastinal lymphadenopathy was more prevalent in patients diagnosed with lymphoma. Among pulmonary pathologies, pneumonia was the most prevalent disease (41.5%), followed by small airway disease (13.5%), mediastinal lymphadenopathy (12.5%), chronic pulmonary disease (6.5%), and pulmonary metastasis (6%). Normal thoracic CT scan was detected in 20% of participants. Overall assessment of clinical symptoms, laboratory tests, and imaging findings did not lead to the diagnosis of acute lung involvement in 5.5% of study participants, because complete clinical data were not available in some participants. Conclusions: Assessment of the most common thoracic imaging findings in patients diagnosed with hematologic malignancies, may help make better diagnosis and planning of a rapid therapeutic approach. [ABSTRACT FROM AUTHOR]

The utilization of computational models in the field of medical image classification is an ongoing and unstoppable trend, driven by the pursuit of aiding medical professionals in achieving swift and precise diagnoses. Post COVID-19, many researchers are studying better classification and diagnosis of lung diseases particularly, as it was reported that one of the very few diseases greatly affecting human beings was related to lungs. This research study, as presented in the paper, introduces an advanced computer-assisted model that is specifically tailored for the classification of 13 lung diseases using deep learning techniques, with a focus on analyzing chest radiograph images. The work flows from data collection, image quality enhancement, feature extraction to a comparative classification performance analysis. For data collection, an open-source data set consisting of 112,000 chest X-Ray images was used. Since, the quality of the pictures was significant for the work, enhanced image quality is achieved through preprocessing techniques such as Otsu-based binary conversion, contrast limited adaptive histogram equalization-driven noise reduction, and Canny edge detection. Feature extraction incorporates connected regions, histogram of oriented gradients, gray-level co-occurrence matrix and Haar wavelet transformation, complemented by feature selection via regularized neighbourhood component analysis. The paper proposes an optimized hybrid model, improved Aquila optimization convolutional neural networks (CNN), which is a combination of optimized CNN and DENSENET121 with applied batch equalization, which provides novelty for the model compared with other similar works. The comparative evaluation of classification performance among CNN, DENSENET121 and the proposed hybrid model is also done to find the results. The findings highlight the proposed hybrid model's supremacy, boasting 97.00% accuracy, 94.00% precision, 96.00% sensitivity, 96.00% specificity and 95.00% F1-score. In the future, potential avenues encompass exploring explainable machine learning for discerning model decisions and optimizing performance through strategic model restructuring. [ABSTRACT FROM AUTHOR]

Background: The lung Extracellular Matrix (ECM) contains a considerable part of the parenchymal cells. It contains three essential components: elastin and collagen within a proteoglycan (PG) viscoelastic network. Elastin provides the lung's elasticity property, a necessity for normal breathing, while collagen prepares structural support and strength, and PGs give stability and cushioning within tissue loading. Bacterial and viral respiratory diseases are dependent on changes in the ECM ingredients, which result in an alteration of the lung tissue strength. Purpose: In the present study, this variation was investigated by changing the volume ratio of the ECM ingredients in the viscoelastic model. Results: As a result, the relaxation curves continuously declined by reducing the volume ratios of elastin, collagen, and PGs; subsequently, the lung stiffness decreased. Also, the Standard Linear Solid (SLS) model-based results demonstrated excellent accordance with empirical data with only minor deviations. The resting relaxation modulus and the creep modulus for the ECM tissue were 51 kPa and approximately 0.02 kPa, respectively, and the maximum total modulus of elasticity reached 121 kPa. Conclusions: Moreover, this model demonstrates individual alveolar mechanical behaviours and adds another pathway to the generalized Kelvin-Voigt and Maxwell models in predicting the progress of lung diseases. [ABSTRACT FROM AUTHOR]

Objectives While chest high-resolution CT (HRCT) is correlated to severity and prognosis in asthma, it has not been studied in eosinophilic granulomatosis with polyangiitis (EGPA). Our objective is to study the prognostic value of baseline HRCT in EGPA patients. Methods Retrospective, multicentre observational study in three French hospitals, including EGPA patients with available chest HRCT before any systemic treatment. Two experienced radiologists blinded to clinical data evaluated HRCT images using semi-quantitative scoring. HRCT characteristics were correlated with clinical features and outcome. Results Among 46 patients, 38 (82.6%) had abnormal parenchymal findings on HRCT, including bronchial wall thickening (69.6%), mosaic perfusion (63.0%), ground-glass opacities (32.6%), bronchiectasis (30.4%), mucous plugging (21.7%) and consolidations (17.4%). Patients were clustered into three groups depending on HRCT features: ground-glass pattern, i.e. with ground-glass opacities with or without bronchial abnormalities (group 1, 28.3%), bronchial pattern (group 2, 41.3%) and extra-pulmonary pattern with no significant abnormality (group 3, 30.4%). Group 2 showed less frequent cardiac involvement (31.6 vs 46.2 and 42.9% in groups 1 and 3), more frequent positive ANCA (52.6 vs 0.0 and 14.3%) and higher eosinophil count (median 7510 vs 4000 and 4250/mm3). Group 1 showed worse prognosis with more frequent steroid-dependency (58.3 vs 11.1 and 28.6%) and requirement for mepolizumab (25.0 vs 11.1 and 7.1%). Conversely, group 2 showed a better outcome with higher rates of remission (88.9 vs 41.6 and 71.4%). Conclusion Chest HRCT at diagnosis of EGPA may have prognostic value and help clinicians better manage these patients. [ABSTRACT FROM AUTHOR]

Background: Differentiating between pulmonary sarcomatoid carcinoma (PSC) and pulmonary inflammatory pseudotumor (PIP) is challenging using current conventional diagnostic methods. This lack of distinction significantly impacts subsequent clinical treatment decisions. Objectives: This study was conducted to construct an effective method to distinguish between PSC and PIP based on commonly used computed tomography (CT) images. Patients and Methods: A total of 14 patients with PSC and 76 patients with PIP were retrospectively included in the study for CT imaging. Radiomics features were extracted from non-enhanced CT images, and canonical correlation analysis was performed to reduce redundancy. The final radiomics signature was then identified using the least absolute shrinkage and selection operator (LASSO). Logistic regression (LR), classification and regression trees (CART), support vector machine (SVM), k-nearest neighbors (KNN), and gradient boosting machine (GBM) were used to construct the radiomics models. The performance of these different radiomics models was evaluated using the receiver operating characteristic curve. Results: A total of 1186 radiomics features were extracted from non-enhanced CT images. After dimensionality reduction and selection, 7 valuable features were identified. The performance of 5 machine learning models was evaluated to differentiate between PSC and PIP, and the GBM-based radiomics model demonstrated the best performance. The GBM-based radiomics model achieved an accuracy of 0.922, area under the curve (AUC) of 0.98, F1 score of 0.967, and log loss of 0.161. Compared to conventional clinical-radiological diagnosis, the GBM-based radiomics model showed a significant association (odds ratio [OR] = 8.119; P = 0.006). Conclusion: The implementation of the GBM-based radiomics model has the potential to improve the ability to differentiate between PSC and PIP, thereby influencing the timeliness of subsequent surgical interventions and even the prognosis of patients. [ABSTRACT FROM AUTHOR]

Background: The lungs are enveloped by a serous membrane called visceral pleura, while the chest wall and pericardium are covered by parietal pleura. Lung hila connect these layers, and a small amount of fluid in the pleural space lubricates movement. Pleural effusion, excess fluid in the pleural cavity, indicates underlying pulmonary, pleural, or extra-pulmonary diseases. Objective: To study the various causes of unilateral pleural effusion in patients presenting to a District General Hospital in the United Kingdom. Methodology: This was a prospective study conducted at Worsecter Royal Infirmary, UK, during July 2021 to June 2022. All (58) adult patients (age above 18 years) admitted to chest ward from various sources with unilateral pleural effusion were included. Case notes were reviewed and data collected. Diagnostic pleural tap was performed in every case and aspirate was sent for biochemical, microbiological and cytological analysis. Pleural biopsies were taken where diagnosis could not be established with the help of other investigations. Results: Among 58 patients with unilateral pleural effusion (34 men, 24 women), most were aged 50-89 (mean age 69). Among study cases, 16% were referred for surgery (VATS or thoracotomies), with an average 11-day waiting period. Effusions were transudate (15) or exudate (43), and malignancy was confirmed in 31 cases. Complications included intercostal drain dislodgement (19%) and subcutaneous emphysema (12%). Malignancy was the most common cause of unilateral pleural effusion, followed by parapneumonic effusion, left ventricular failure, TB, and asbestos-related benign effusion. Conclusion: In conclusion, this study highlights malignancy as the primary cause of unilateral pleural effusion, confirmed through cytology and biopsies. Managing these patients is complex, involving prolonged hospitalization, multiple thoracocentesis attempts, and often prompt surgical intervention. Imaging, especially contrast CT chest, is crucial for lesion identification. Complications like drain dislodgement and subcutaneous emphysema underscore the challenges in pleural effusion management. [ABSTRACT FROM AUTHOR]

Current estimates indicate that 50 million people are infected with food-borne trematodes. This is a significant public health problem, but still a neglected tropical disease, because the burden of disease is in rural areas, where health care is limited. Traditional ingestion of raw or poorly cooked food contaminated by unrestrained defecation maintains the cycle of disease and school-age children bear the predominant burden. Clinical patterns of infection, current means of diagnosis, treatment and treatment failure are reviewed in sections on intestinal flukes, liver flukes and lung flukes. New therapeutic approaches are emphasized. [ABSTRACT FROM AUTHOR]

Objective: Lung disease (LD) is an increasingly recognized complication of systemic juvenile idiopathic arthritis (sJIA). As there are no currently available guidelines for pulmonary screening in sJIA, we sought to develop such an algorithm at our institution. Methods: A multidisciplinary workgroup was convened, including members representing rheumatology, pulmonary, stem cell transplantation, and patient families. The workgroup leaders drafted an initial algorithm based on published literature and experience at our center. A modified Delphi approach was used to achieve agreement through three rounds of anonymous, asynchronous voting and a consensus meeting. Statements approved by the workgroup were rated as appropriate with moderate or high levels of consensus. These statements were organized into the final approved screening algorithm for LD in sJIA. Results: The workgroup ultimately rated 20 statements as appropriate with a moderate or high level of consensus. The approved algorithm recommends pulmonary screening for newly diagnosed patients with sJIA with clinical features that the workgroup agreed may confer increased risk for LD. These "red flag features" include baseline characteristics (young age of sJIA onset, human leukocyte antigen type, trisomy 21), high disease activity (macrophage activation syndrome [MAS], sJIA‐related ICU admission, elevated MAS biomarkers), respiratory symptoms or abnormal pulmonary examination findings, and features of drug hypersensitivity‐like reactions (eosinophilia, atypical rash, anaphylaxis). The workgroup achieved consensus on the recommended pulmonary work‐up and monitoring guidelines. Conclusion: We developed a pulmonary screening algorithm for sJIA‐LD through a multidisciplinary consensus‐building process, which will be revised as our understanding of sJIA‐LD continues to evolve. [ABSTRACT FROM AUTHOR]

The article describes the case of a 22-year-old male who presented to his provider with leg shoulder pain which had been ongoing for four months and was exacerbated by movement. Topics include finding on a left shoulder X-ray, and his diagnosis of pulmonary echinococcosis which was made after his surgery, and information on echinococcosis.

Introduction: Breast cancer is the most common cancer in women worldwide. One of the treatment choices used in hormone receptor positive and HER2 expression negative metastatic breast cancer is cyclin dependent kinase 4/6 (CDK) inhibitors. There are differences between the effects and adverse events of all CDK4/6 inhibitors. In this report, we describe a 48-year-old female patient with breast cancer who developed pulmonary infiltrates secondary to drug in the second year of follow-up with Ribociclib therapy. Case Report: The patient who used ribociclib for metastatic breast cancer was admitted to hospital for routine controls. The patient, in the eighth month of ribociclib treatment, had no active complaints. In the patient's imaging, pulmonary infiltrates were detected in the lower lobe of the right lung. Management and Outcome: The drug was continued in the patient who was asymptomatic and had no infectious signs. Pneumonitis, interstitial lung disease, tuberculosis, COVID-19 and other viral agents were excluded in the patient. A minimal increase in pulmonary infiltrates was observed in the follow-up. However, the patient who does not have any complaints is currently continuing ribociclib at 600 mg/day. Discussion: The pulmonary infiltrates that developed in the patient increased with continued use of ribociclib, suggesting that this was due to ribociclib. The Naranjo Adverse Drug Reaction Probability Scale also indicates probable relationship. [ABSTRACT FROM AUTHOR]

The article points out the need to understand the role and practice of right heart catheterizations (RHC) in the evaluation of dyspnea, including its differential diagnoses and markers of cardiopulmonary functioning. Topics covered include the parameters defining oxygen delivery, the disease states that might be considered in the differential diagnosis and the benefits of exercise RHC protocols.

This review paper examines the current state of lung disease diagnosis based on deep learning (DL) methods. Lung diseases, such as Pneumonia, TB, Covid-19, and lung cancer, are significant causes of morbidity and mortality worldwide. Accurate and timely diagnosis of these diseases is essential for effective treatment and improved patient outcomes. DL methods, which utilize artificial neural networks to extract features from medical images automatically, have shown great promise in improving the accuracy and efficiency of lung disease diagnosis. This review discusses the various DL methods that have been developed for lung disease diagnosis, including convolutional neural networks (CNNs), deep neural networks (DNNs), and generative adversarial networks (GANs). The advantages and limitations of each method are discussed, along with the types of medical imaging techniques used, such as X-ray and computed tomography (CT). In addition, the review discusses the most commonly used performance metrics for evaluating the performance of DL for lung disease diagnosis: the area under the curve (AUC), sensitivity, specificity, F1-score, accuracy, precision, and the receiver operator characteristic curve (ROC). Moreover, the challenges and limitations of using DL for lung disease diagnosis, including the limited availability of annotated data, the variability in imaging techniques and disease presentation, and the interpretability and generalizability of DL models, are highlighted in this paper. Furthermore, strategies to overcome these challenges, such as transfer learning, data augmentation, and explainable AI, are also discussed. The review concludes with a call for further research to address the remaining challenges and realize DL's full potential for improving lung disease diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Background: Advances in bronchoscopy have impacted the practice patterns in the sampling of thoracic lymph nodes and lung lesions. Objectives: The aim of the study was to study the trends in utilization of mediastinoscopy, transthoracic needle aspiration (TTNA), and bronchoscopic transbronchial sampling. Methods: We conducted an analysis of patient claims for sampling of thoracic lymph nodes and lung lesions in the Medicare population and a sample of the commercial population between 2016 and 2020. We used Current Procedural Terminology codes to identify mediastinoscopy, TTNA, and bronchoscopic transbronchial sampling. Post-procedural pneumothorax rates were assessed by procedure type including subset analyses for patients with chronic obstructive pulmonary disease (COPD). Results: Between 2016 and 2020, utilization of mediastinoscopy has decreased in both the Medicare and commercial populations (−47.3% and −65.4%, respectively), while linear endobronchial ultrasound (EBUS)-guided transbronchial needle aspiration (TBNA) has increased only in the Medicare population (+28.2%). Percutaneous lung biopsy claims dropped by −17.0% in the Medicare and −41.22% in the commercial population. The use of bronchoscopic TBNA and forceps biopsy declined in both populations, but the reliance on a combination of guided technology (radial EBUS-guided and navigation) grew in the Medicare and commercial populations (+76.3% and +25%). Rates of post-procedural pneumothorax were significantly higher following percutaneous biopsy compared to bronchoscopic transbronchial biopsy. Conclusions: Linear EBUS-guided sampling has surpassed mediastinoscopy as the technique for sampling thoracic lymph nodes. Transbronchial lung sampling is increasingly being performed with guidance technology. This trend is aligned with favorable rates of post-procedure pneumothorax for transbronchial biopsy. [ABSTRACT FROM AUTHOR]

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Context • Early detection of pulmonary nodules in lung cancer and timely intervention can improve the number of diagnoses at early stages of lung cancer and can reduce mortality. At present, it’s not possible to accurately determine the degree of pathological invasion of ground-glass nodules and the probability of regional lymph node metastasis using an imaging examination before surgery. Objective • The study intended to analyze the clinical, imaging, and pathological characteristics of malignant pulmonary nodules and to explore the high-risk factors for lymph node metastasis, using logistic regression multivariate analysis. Design • The research team retrospectively analyzed lung-cancer patients’ demographic and clinical data. Setting • The study took place in the Department of Thoracic Surgery at Zhangzhou Municipal Hospital, affiliated with Fujian Medical University, in Zhangzhou, China. Participants • Participants were 1168 patients with malignant pulmonary nodules at the hospital between January 2018 and December 2020. Outcome Measures • The research team: (1) collected participant’s pulmonary nodules after surgical resection, which the hospital had confirmed were primary lung cancer and (2) analyzed the clinical characteristics of the malignant pulmonary nodules using the World Health Organization’s (WHO’s) 2021 classification standard for lung-cancer tissue. The research team also collected participants’ data, including gender, age, smoking status, nodular size, imaging characteristics, pathological type, degree of invasion, and lymph node metastasis, and analyzed the clinical characteristics of the malignant pulmonary nodules and explored the risk factors for lymph node metastasis. Results • Participants’ average age was 56.79 ± 11.53 years, and the study included 675 females (57.79%) and 493 males (42.21%), 932 of whom didn’t smoke (79.8%). Imaging indicated that most participants had nodules in the upper lobes of the lungs, 424 participants in the right lung (36.30%) and 303 in the left (25.94%). Imaging also showed that 400 participants had pure ground-glass nodules (34.25%) and 371 had solid nodules(31.76%), 355 had partial solid nodules (30.39%), the other 42 had cavitary nodules (3.60%), and 1098 participants had adenocarcinoma (94.00%). Regarding the incidence of lymph node metastasis, 67 participants had N1 metastasis (5.74%) and 34 had N2 metastasis (2.91%). The multivariate logistic regression analysis showed that an increase in the nodular size (P < .001); the presence of lower-lobe pulmonary nodules, the nodular site (P = .025); and the amount of solid components in the nodule, the nodule’s features (P<.001), were significant adverse factors for N1 lymph node metastasis, while gender, age, and smoking status didn’t affect that outcome. Conclusions • Adenocarcinoma was the most common pathological type, and the probability of lymph node metastasis was low. N1 lymph node metastasis was associated with increased nodular size and solid components and the presence of lower lobe nodules. [ABSTRACT FROM AUTHOR]

Background: Bronchoalveolar lavage (BAL) is a widely accepted investigative tool for the diagnosis of pulmonary lesions. This study was done to find out the usefulness of BAL in diagnosis of pulmonary lesions from central Indian patient population. Methods: A cross-sectional prospective study was performed over a period of three years. All the BAL specimens of patients presenting to Department of Pulmonary Medicine and Tuberculosis during a period of January 2017 to December 2019 were included in the study. Cyto-histopathologic correlation was done, wherever available. Results: Of total 277 cases, there were 178 (64.5%) males and 99 (35.5%) females. The age of patients ranged from 4 years to 82 years. In 92 (33%) cases, specific infective etiology could be identified on BAL cytology, the most common being tuberculosis (26%) followed by fungal infections (2%). Rarely, infections like nocardia, actinomycosis, and hydatidosis were also identified. Eight cases (3%) of malignancy were identified which included two cases of adenocarcinoma, one case of small cell carcinoma, three cases of poorly differentiated carcinoma, and two cases suspicious for malignancy. Some rare diagnoses like diffuse alveolar damage, pulmonary alveolar microlithiasis, and pulmonary alveolar proteinosis could be identified on BAL. Conclusion: BAL is useful in primary diagnosis of infections and malignancies of lower respiratory tract. BAL may aid in diagnostic workup of diffuse lung diseases. A combination of clinical information, high-resolution computed tomography, and BAL analysis may furnish an assured diagnosis to the clinician and obviate need for invasive procedures. [ABSTRACT FROM AUTHOR]

Background: Bronchoscopy is an essential procedure in the diagnosis and treatment of pulmonary diseases. However, the literature suggests that distractions affect the quality of bronchoscopy and affect inexperienced doctors more than experienced. Objectives: The objective of the study was as follows: does simulation-based bronchoscopy training with immersive virtual reality (iVR) improve the doctors' ability to handle distractions and thereby increase the quality, measured in procedure time, structured progression score, diagnostic completeness (%), and hand motor movements of a diagnostic bronchoscopy in a simulated scenario. Exploratory outcomes were heart rate variability and a cognitive load questionnaire (Surg-TLX). Methods: Participants were randomized. The intervention group practiced in an iVR environment with a head-mounted display (HMD) while using the bronchoscopy simulator, while the control group trained without the HMD. Both groups were tested in the iVR environment using a scenario with distractions. Results: 34 participants completed the trial. The intervention group scored significantly higher in diagnostic completeness (100 i.q.r. 100–100 vs. 94 i.q.r. 89–100, p value = 0.03) and structured progress (16 i.q.r. 15–18 vs. 12 i.q.r. 11–15, p value 0.03) but not in procedure time (367 s standard deviation [SD] 149 vs. 445 s SD 219, p value = 0.06) or hand motor movements (−1.02 i.q.r. −1.03–[−1.02] versus −0.98 i.q.r. −1.02–[–0.98], p value = 0.27). The control group had a tendency toward a lower heart rate variability (5.76 i.q.r. 3.77–9.06 vs. 4.12 i.q.r. 2.68–6.27, p = 0.25). There was no significant difference in total Surg-TLX points between the two groups. Conclusion: iVR simulation training increases the quality of diagnostic bronchoscopy in a simulated scenario with distractions compared with conventional simulation-based training. [ABSTRACT FROM AUTHOR]

Background: Cystic and cavitary lung cancer (CCLC) is infrequently observed on computed tomography (CT) scans; however, its diagnosis is often overlooked or delayed. Objectives: The current study aimed to investigate the CT and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) features of CCLC. Patients and Methods: A total of 809 patients who underwent lung tumor resection were examined in this study, and the presence of cystic and cavitary lesions on CT scans was investigated. Based on the CT scans, CCLC was identified in 102 consecutive patients. The diameters of the whole nodule and the airspace portion of the lesion, morphological patterns of cystic and cavitary lesions, presence of ground glass opacity (GGO), and loculation pattern (including the presence of a septum) were evaluated. The positron emission tomography (PET) scans of CCLC were also assessed visually and semi-quantitatively. Results: A total of 104 CCLC lesions were evaluated in this study. The histological analysis indicated 85 cases of adenocarcinoma (AD) and 19 cases of squamous cell carcinoma (SCC). The morphological patterns of cystic and cavitary lesions were classified into four types. The presence of GGO, type 4 morphological pattern (a soft-tissue-density structure intermixed within clusters of a cavitary lesion), and multilocular with septum (MS) loculation pattern were significantly different according to the histological type. The maximum standardized uptake value (SUVmax) on PET scans was significantly lower in AD compared to SCC (P = 0.002). In the solid nodule part of cystic and cavitary lesions, the MS pattern was significantly more common in AD (P = 0.044). Conclusion: When cystic and cavitary lesions are observed on CT scans, the presence of GGO and the MS pattern should be considered, as it may help differentiate the histological findings. [ABSTRACT FROM AUTHOR]

Objective: To compare non-tuberculous mycobacterial pulmonary disease (NTMPD) diagnosis by metagenomic next-generation sequencing (mNGS) with Bactec mycobacterial growth indicator tube (MGIT) 960. Methods: A total of 422 patients with suspected NTMPD in Shanghai Pulmonary Hospital between January 2020 and May 2021 were retrospectively analyzed; 194 were diagnosed with NTMPD. The diagnostic performance of mNGS and MGIT 960 for NTMPD was assessed. Receiver operating characteristic (ROC) curves and areas under curve (AUCs) were compared. Results: The sensitivity of mNGS in NTMPD diagnosis was 81.4% and higher than that of MGIT 960 (53.6%). The specificity of mNGS in NTMPD diagnosis was 97.8%, similar to that of MGIT 960 (100%). The sensitivity of combined mNGS and MGIT 960 in NTMPD diagnosis was 91.8%. The sensitivity of mNGS for bronchoalveolar lavage fluid (BALF), pulmonary puncture tissue fluid, and sputum was 84.8%, 80.6%, and 77.5%, respectively; all were higher than that of MGIT 960 (P < 0.05). The AUC of mNGS and MGIT 960 was 0.897 and 0.768, respectively. The AUC of mNGS were BALF (0.916), pulmonary puncture tissue fluid (0.903), and sputum (0.870). Conclusion: The sensitivity of mNGS was superior to that of Bactec MGIT 960; the specificity in NTMPD diagnosis was similar. mNGS shows effective performance in NTMPD diagnosis. [ABSTRACT FROM AUTHOR]

Background Early and accurate recognition of respiratory pathogens is crucial to prevent increased risk of mortality in critically ill patients. Microbial-derived volatile organic compounds (mVOCs) in exhaled breath could be used as noninvasive biomarkers of infection to support clinical diagnosis. Methods In this study, we investigated the diagnostic potential of in vitro – confirmed mVOCs in the exhaled breath of patients under mechanical ventilation from the BreathDx study. Samples were analyzed by thermal desorption–gas chromatography–mass spectrometry. Results Pathogens from bronchoalveolar lavage (BAL) cultures were identified in 45 of 89 patients and Staphylococcus aureus was the most commonly identified pathogen (n = 15). Of 19 mVOCs detected in the in vitro culture headspace of 4 common respiratory pathogens (S. aureus , Pseudomonas aeruginosa , Klebsiella pneumoniae , and Escherichia coli), 14 were found in exhaled breath samples. Higher concentrations of 2 mVOCs were found in the exhaled breath of patients infected with S. aureus compared to those without (3-methylbutanal: P <.01, area under the receiver operating characteristic curve [AUROC] = 0.81–0.87; and 3-methylbutanoic acid: P =.01, AUROC = 0.79–0.80). In addition, bacteria identified from BAL cultures that are known to metabolize tryptophan (E. coli , Klebsiella oxytoca , and Haemophilus influenzae) were grouped and found to produce higher concentrations of indole compared to breath samples with culture-negative (P =.034) and other pathogen-positive (P =.049) samples. Conclusions This study demonstrates the capability of using mVOCs to detect the presence of specific pathogen groups with potential to support clinical diagnosis. Although not all mVOCs were found in patient samples within this small pilot study, further targeted and qualitative investigation is warranted using multicenter clinical studies. [ABSTRACT FROM AUTHOR]

Cardiopulmonary ultrasound (CPUS), the combination of lung ultrasound (LUS) and targeted neonatal echocardiography (TnECHO)AA, may offer a more appropriate approach to the challenging neonatal cardiovascular and respiratory disorders. This paper reviews the possible use of CPUS in the neonatal intensive care unit (NICU). [ABSTRACT FROM AUTHOR]

The purpose of this study is to validate lung ultrasound score (LUS) for prediction of surfactant replacement therapy (SRT) in Indian infants of 27-336/7 weeks gestational age (GA). This prospective diagnostic accuracy study was conducted in a level 3 neonatal care unit in India. Consecutively born preterm infants with respiratory distress syndrome (RDS) were enrolled. Surfactant was administered if oxygen requirement exceeded > 30%. Baseline characteristics, respiratory parameters, and lung ultrasound images were recorded soon after admission and compared between surfactant and non-surfactant groups. Adjusted odds ratio (OR) and diagnostic accuracy of LUS were calculated for SRT. Among 78 infants with RDS included in the final analysis, 62 received surfactant (79.48%). Median time of performing lung ultrasound was 50 min of life in both groups. Median LUS in the anterior and posterior chest areas of either side as well as total LUS was significantly higher in the surfactant group. After adjusting for other confounders, LUS was found to be a significant predictor of SRT (adjusted OR (95%CI): 1.55 (1.15-2.087)). Diagnostic accuracy of LUS was determined by receiver operating characteristic (ROC) curve analysis (AUC (95% CI): 0.751 (0.64-0.842), p < 0.001). A cutoff score of ≥ 9 for LUS was considered optimal for SRT (sensitivity (95%CI): 70.97% (57.87-81.45), specificity (95%CI): 68.75% (41.48-87.87)).Conclusion: Lung ultrasound is a valid diagnostic tool for SRT in Indian setting with a cutoff score ≥ 9.Trial Registration: CTRI/2021/11/038269.What Is Known: • Surfactant requirement in preterm infants with RDS has been traditionally based on FiO2 criteria. • Lung ultrasound score can predict the need for surfactant although majority of the studies originated in developed countries.What Is New: • Lung ultrasound is a valid tool for surfactant replacement therapy even in developing countries like India. [ABSTRACT FROM AUTHOR]

The article describes the case of chest pain in an a 14-year-old male patient. Topics discussed include the symptoms experienced by the patient, the patient's medical history, the results of the patient's medical examinations, the surgical procedure performed on the patient, and the final diagnosis.

Background: Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may have the potential to reflect angiogenesis and proliferation of pulmonary neoplasms. Purpose: To verify whether DCE-MRI can identify pulmonary neoplasm property and evaluate the correlation of DCE-MRI perfusion parameters with microvessel density (MVD) and Ki-67 in lung cancer. Material and Methods: This study enrolled 65 patients with one pulmonary neoplasm who underwent computed tomography-guided percutaneous lung biopsy with pathological diagnosis (43 malignant, 22 benign; mean age = 59.71 ± 11.72 years). All patients did DCE-MRI before biopsy. Quantitative MRI parameters including endothelial transfer constant (Ktrans), flux rate constant (Kep), and fractional extravascular extracellular space (EES) volume (Ve) were calculated by extended Tofts linear model. MVD was evaluated by CD34-expressing tumor vessels. Proliferation was assessed by Ki-67 staining. The correlations of parameters with MVD and Ki-67 expression were analyzed. Results: Ktrans and Kep values were significantly increased in malignant lesions compared to benign lesions (P = 0.001 and 0.022, respectively), whereas no statistical difference in Ve was found. The CD34 expression was positively correlated to Ktrans (r = 0.608; P = 0.004) and Kep (r = 0.556; P = 0.001). Subsequent subtype analyses also showed positive correlations of Ktrans and Kep with MVD in adenocarcinoma group (r = 0.550 and 0.563; P = 0.012 and 0.015, respectively). No significant correlation was found between these parameters and Ki-67. Conclusion: Ktrans and Kep may distinguish benign and malignant pulmonary neoplasm. Ktrans and Kep, with their positive correlation to MVD, can be used as non-invasive parameters reflecting lung cancer angiogenesis. [ABSTRACT FROM AUTHOR]