Precision medicine: "Point of Care Ultrasound" (PoCUS) in the diagnostic approach to the patient with hyponatremia.

Hyponatremia is a multifactorial disorder defined as a decrease in plasma sodium concentration. Its differential diagnosis requires an adequate evaluation of the extracellular volume (ECV). However, ECV determination, simply based on the clinical history, vital signs, physical examination, and laboratory findings can leads to misdiagnosis and inappropriate treatment. The use of Point-of-Care Ultrasound (POCUS), through the combination of Lung Ultrasound (LUS), Venous Excess UltraSound (VExUS) and Focused Cardiac Ultrasound (FoCUS), allows a much more accurate holistic assessment of the patient's ECV status in combination with the other parameters.

Preserved Ratio Impaired Spirometry (PRISm): A Global Epidemiological Overview, Radiographic Characteristics, Comorbid Associations, and Differentiation from Chronic Obstructive Pulmonary Disease.

Preserved Ratio Impaired Spirometry (PRISm) manifests notable epidemiological disparities across the globe, with its prevalence and influential factors showcasing pronounced diversities among various geographical territories and demographics. The prevalence of PRISm fluctuates considerably among regions such as Latin America, the United States, and Asian nations, potentially correlating with a myriad of determinants, including socioeconomic status, environmental factors, and lifestyle modalities. Concurrently, the link between PRISm and health risks and other disorders, especially its distinction and interrelation with chronic obstructive pulmonary disease (COPD), has become a pivotal subject of scientific enquiry. Radiographic anomalies, such as perturbations in the pulmonary parenchyma and structural alterations, are posited as salient characteristics of PRISm. Furthermore, PRISm unveils intricate associations with multiple comorbidities, inclusive of hypertension and type 2 diabetes, thereby amplifying the intricacy in comprehending and managing this condition. In this review, we aim to holistically elucidate the epidemiological peculiarities of PRISm, its potential aetiological contributors, its nexus with COPD, and its association with radiographic aberrations and other comorbidities. An integrative understanding of these dimensions will provide pivotal insights for the formulation of more precise and personalised preventative and therapeutic strategies.

The Effect of Yoga on Early Clinical Outcomes and Pulmonary Functions in Patients Scheduled for Bariatric Surgery: a Randomized Controlled Study.

PURPOSE: The present research was undertaken to investigate the effect of yoga on pulmonary function and early clinical outcomes in patients scheduled for bariatric surgery. MATERIALS AND METHODS: This research with a randomized control group was performed on patients scheduled for bariatric surgery between October 2021 and June 2022 in the General Surgery Clinic of a University Hospital in Eastern Turkey. The sample consists of 100 randomized patients who received yoga breathing exercises and routine care. Pulmonary function test (PFT), posteroanterior chest X-rays (CXR), 6-min walk test, and oxygen saturation (SpO2) were applied as a pretest. The researcher practiced yoga for 40 min every day of the week. Post-test measurements were performed at the end of the yoga practice. Control group patients underwent the tests at the same intervals without any modifications to the standard clinical protocol. RESULTS: The difference between the control and experimental groups was significant in terms of post-test PFT measurements (p < 0.001). In the CXR of the patients, a statistically significant improvement was determined in 61.5% of the patients with yoga breathing practice (p < 0.001). Also, there was a significant increase in the 6-min walk test and SpO2 values in the experimental group (p < 0.05). CONCLUSION: Yoga practice positively affected the pulmonary function values of the patients.

Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules.

For patients with early multiple pulmonary nodules, it is essential, from a diagnostic perspective, to determine the spatial distribution, size, location, and relationship with surrounding lung tissue of these nodules throughout the entire lung. This is crucial for identifying the primary lesion and developing more scientifically grounded treatment plans for doctors. However, pattern recognition methods based on machine vision are susceptible to false positives and false negatives and, therefore, cannot fully meet clinical demands in this regard. Visualization methods based on maximum intensity projection (MIP) can better illustrate local and individual pulmonary nodules but lack a macroscopic and holistic description of the distribution and spatial features of multiple pulmonary nodules. Therefore, this study proposes a whole-lung 3D reconstruction method. It extracts the 3D contour of the lung using medical image processing technology against the background of the entire lung and performs 3D reconstruction of the lung, pulmonary artery, and multiple pulmonary nodules in 3D space. This method can comprehensively depict the spatial distribution and radiological features of multiple nodules throughout the entire lung, providing a simple and convenient means of evaluating the diagnosis and prognosis of multiple pulmonary nodules.

Diagnostic Accuracy of CT-Guided Percutaneous Pulmonary Biopsy for Distinguishing Benign and Malignant Solitary Pulmonary Nodules.

Background: Isolated pulmonary nodules (SPNs) are small, circular lesions within lung tissue, often challenging to diagnose due to their size and lack of typical imaging features. Timely diagnosis is crucial for treatment decisions. However, the difficulty in qualitative diagnosis necessitates clinical biopsies. Objective: This study aimed to assess the diagnostic accuracy of CT-guided percutaneous lung biopsy for SPNs and identify potential risk factors for malignancy. Methods: We conducted a retrospective analysis of 112 patients with SPNs who underwent CT-guided core needle biopsy (CT-CNB) between June 2020 and June 2022. Histological and cytological results were obtained for all patients, and clinical data and imaging characteristics were compared between benign and malignant SPN groups. Binary logistic regression was used to analyze risk factors for malignancy, and complications were observed. Results: Cytological and histological specimens were successfully obtained for all patients. The cohort consisted of 43 patients with benign SPNs and 69 with malignant SPNs. Among the malignant SPN group, 67 cases were confirmed via CT-CNB and 2 through surgery, resulting in a sensitivity of 97.10% and specificity of 100.00%. The malignant nodules comprised 45 adenocarcinomas, 14 squamous cell carcinomas, 8 metastatic tumors, and 2 small cell carcinomas. Notably, 2 initially diagnosed as malignant cases were found to have chronic inflammation on preoperative biopsy but revealed adenocarcinoma and squamous cell carcinoma post-surgery. The benign nodules encompassed 20 granulomatous inflammation cases, 15 chronic inflammation, 3 fungal granulomas, 2 hamartomas, and 1 fibrous tissue. Cytological smears exhibited a sensitivity of 81.3% and a specificity of 100.0% for malignancy. Significantly, age ≥60, elevated tumor markers, and specific imaging signs (burr, foliation, pleural pull) were identified as risk factors for malignant SPNs using Binary Logistic regression (all P < .05). Conclusions: CT-guided percutaneous lung biopsy demonstrates excellent diagnostic efficacy and safety for distinguishing benign and malignant SPNs.

A Study on the Efficacy of Three-Dimensional CT Bronchial Angiography in Thoracoscopic Precision Resection of Lung Segments.

Objective: This study aimed to evaluate the effectiveness of three-dimensional CT bronchial angiography (3D-CTBA) in facilitating precise lung segmental resection. Methods: A total of 80 patients with peripheral lung nodules undergoing anatomical lung segmentectomy were randomly divided into two groups: a control group (n = 40) and a study group (n = 40). The control group received surgical treatment based on chest CT prompts and traditional lung segmentation, while the study group's chest CT imaging data were reconstructed into 3D images before surgery, followed by lung segmentectomy. Surgical parameters and complication rates were compared between the two groups. Results: The study group exhibited significantly shorter operation time, drainage time, and hospitalization time, as well as reduced intraoperative bleeding, lung tissue resection size, and drainage volume, compared to the control group (P < .05). Hospitalization costs did not differ significantly between the two groups (P > .05). The incidence of lung infection, pulmonary atelectasis, and arrhythmia showed no significant difference between the groups (P > .05). However, the study group demonstrated significantly lower rates of hemoptysis and lung leakage compared to the control group (P < .05). There was no significant difference in the composition of postoperative pathological staging between the two groups (χ2 = 0.721, P > .05). Conclusions: The application of 3D-CTBA technology provides clear visualization of the lung's anatomical structure and contributes to enhanced safety and effectiveness in thoracoscopic lung segmental precision resection.

The association of clinically relevant variables with chest radiograph lung disease burden quantified in real-time by radiologists upon initial presentation in individuals hospitalized with COVID-19.

OBJECTIVES: We aimed to correlate lung disease burden on presentation chest radiographs (CXR), quantified at the time of study interpretation, with clinical presentation in patients hospitalized with coronavirus disease 2019 (COVID-19). MATERIAL AND METHODS: This retrospective cross-sectional study included 5833 consecutive adult patients, aged 18 and older, hospitalized with a diagnosis of COVID-19 with a CXR quantified in real-time while hospitalized in 1 of 12 acute care hospitals across a multihospital integrated healthcare network between March 24, 2020, and May 22, 2020. Lung disease burden was quantified in real-time by 118 radiologists on 5833 CXR at the time of exam interpretation with each lung annotated by the degree of lung opacity as clear (0%), mild (1-33%), moderate (34-66%), or severe (67-100%). CXR findings were classified as (1) clear versus disease, (2) unilateral versus bilateral, (3) symmetric versus asymmetric, or (4) not severe versus severe. Lung disease burden was characterized on initial presentation by patient demographics, co-morbidities, vital signs, and lab results with chi-square used for univariate analysis and logistic regression for multivariable analysis. RESULTS: Patients with severe lung disease were more likely to have oxygen impairment, an elevated respiratory rate, low albumin, high lactate dehydrogenase, and high ferritin compared to non-severe lung disease. A lack of opacities in COVID-19 was associated with a low estimated glomerular filtration rate, hypernatremia, and hypoglycemia. CONCLUSIONS: COVID-19 lung disease burden quantified in real-time on presentation CXR was characterized by demographics, comorbidities, emergency severity index, Charlson Comorbidity Index, vital signs, and lab results on 5833 patients. This novel approach to real-time quantified chest radiograph lung disease burden by radiologists needs further research to understand how this information can be incorporated to improve clinical care for pulmonary-related diseases.. An absence of opacities in COVID-19 may be associated with poor oral intake and a prerenal state as evidenced by the association of clear CXRs with a low eGFR, hypernatremia, and hypoglycemia.

Value of Thoracic Echocardiography in the Diagnosis of Acute Heart Failure: Systematic Review and Meta-analysis.

Context: For patients with acute heart failure (AHF), the methods of clinical diagnosis of pulmonary edema mainly include clinical symptoms, laboratory results, and an imaging examination. The common diagnostic methods, such as chest X-rays and computerized tomography (CT) scanning, haven't been completely satisfactory. Objective: The study intended to systematically, quantitatively, and comprehensively evaluate the value of a lung (pulmonary) ultrasound, performed at a patient's bedside, in the diagnosis of acute heart failure (AHF), to provide an objective basis for its clinical application and further research. Design: The research team searched PubMed, Excerpta Medica Database (EMBASE), ScienceDirect, Cochrane Library, China Journal Full-text Database (CNKI), VIP Full-text Database, Wanfang Database, and China Biomedical Literature Database (CBM) for relevant literature, from January 2010 to the present, about the use of a lung ultrasound for diagnosis of AHF patients. The team used keywords to search literature: ultrasound, AHF diagnosis, cardiogenic pulmonary edema, ultrasonic examination, AHF diagnosis, and cardiogenic pulmonary edema. The research team then conducted a meta-analysis of the collected data according to the Cochrane Handbook 5.3 with RevMan 5.3 statistical software. Setting: The study took place at Jinan. Outcome Measures: The research team: (1) evaluated the quality of the included studies; (2) examined the accuracy of a lung ultrasound in the diagnosis of AHF compared to computerized tomography (CT) as well as to the conventional ultrasonic cardiogram (echocardiogram) that a cardiologist performs; (3) determined the sensitivity, specificity, and predictive value of lung ultrasound using data from two of the included studies; (4) evaluated the data by drawing funnel charts; and (5) examined the publication bias of the included studies. Results: The research team selected six controlled clinical studies, with 345 data samples, for the meta-analysis. The team performed heterogeneity tests for the included research data. For the first test, the team compared the accuracy of lung ultrasound and CT in diagnosing AHF and found obvious heterogeneity, with χ2 = 11.40, df = 3, P = .010, and I2 = 74%. Based on an analysis using a random effects model, the team found no significant differences between the two methods in the diagnosis of AHF (P = .35). For the second test, the team compared the accuracy of lung ultrasound and an ultrasonic cardiogram in diagnosing AHF and found that the data didn't differ significantly, with χ2 = 0.08, df = 1, P = .78, I2 = 0%. Based on an analysis using a fixed effects model, the team found that the accuracy of the lung ultrasound in diagnosing AHF was significantly higher than that of ultrasonic cardiogram (P = .01). In the two studies, the sensitivity and specificity were high. The majority of the funnel charts were symmetrical, but a few were asymmetrical, suggesting a publication bias, which the heterogeneity in the studies and the limited number of examined examples may explain. Conclusions: Lung ultrasound is of great value in the diagnosis of AHF. It's highly efficient, has prospects for broad clinical application, and is worth popularizing, benefiting patients. Scholars need to verify the current study's findings in follow-up studies and in more high-quality case-control trials.

Artificial Intelligence and Interstitial Lung Disease: Diagnosis and Prognosis.

ABSTRACT: Interstitial lung disease (ILD) is now diagnosed by an ILD-board consisting of radiologists, pulmonologists, and pathologists. They discuss the combination of computed tomography (CT) images, pulmonary function tests, demographic information, and histology and then agree on one of the 200 ILD diagnoses. Recent approaches employ computer-aided diagnostic tools to improve detection of disease, monitoring, and accurate prognostication. Methods based on artificial intelligence (AI) may be used in computational medicine, especially in image-based specialties such as radiology. This review summarises and highlights the strengths and weaknesses of the latest and most significant published methods that could lead to a holistic system for ILD diagnosis. We explore current AI methods and the data use to predict the prognosis and progression of ILDs. It is then essential to highlight the data that holds the most information related to risk factors for progression, e.g., CT scans and pulmonary function tests. This review aims to identify potential gaps, highlight areas that require further research, and identify the methods that could be combined to yield more promising results in future studies.

Ayurveda management of pulmonary mycosis: an integrative approach: a case report.

BACKGROUND: Pulmonary mycosis is a fungal infection of the lung. Antifungal treatments are used in conventional treatments; however, incomplete response and toxicity are major challenges of antifungal therapies. In Ayurveda, pulmonary mycosis is diagnosed and treated based on principles of respiratory disorders (referred to as Shvaas Roga) with promising outcomes. CASE PRESENTATION: A > 60-year-old South Indian male patient visited Institute of Ayurveda and Integrative Medicine with complaints of cough, breathlessness, pedal edema, weight loss, uncontrolled diabetes, and anemia. Following chest X-ray, high-resolution computed tomography (HRCT) and bronchoscopy, the patient was diagnosed with a case of pulmonary mucormycosis. The patient had availed conventional allopathic treatment for 3 months including standard antifungal medication for 3 weeks. However, due to unresolved and persistent symptoms, the patient sought Ayurveda treatment. The patient was diagnosed and treated for 6 weeks as a case of Shvaasa Roga, a subcategory of the respiratory disorder according to Ayurveda, and was cured of the infection following an integrative Ayurveda management regime which included internal medicines, panchakarma, necessary poorvakarmas (like abhyanga and swedhana), diet and lifestyle advice, yoga and acupuncture. CONCLUSIONS: The patient was cured of fungal lung infection in 6 weeks using an integrative approach. Primary Ayurveda treatment supported with diet and lifestyle modifications, yoga, and acupuncture helped the patient to recover from illness. The patient is alive and free of disease for more than one year to date.

Spherical pneumonia caused by Ralstonia mannitolilytica: a case report and literature review.

BACKGROUND: Spherical pneumonia is an extremely rare condition that is difficult to diagnose. It is a specific type of lung infection that often manifests as a round or round-like mass on chest imaging. Spherical pneumonia is easily misdiagnosed as a pulmonary tumor; therefore, awareness of this disease must be strengthened. CASE PRESENTATION: The patient was a 29-year-old female who had persistent cough and sputum for approximately 1 month and fever for 5 days. Chest computed tomography (CT) at our hospital revealed a mass in the lower lobe of the right lung near the hilar region, with obstructive pulmonary atelectasis and obstructive pneumonia. Although lung cancer was suspected, Ralstonia mannitolilytica was detected by metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid, and no cancer cells or Mycobacterium tuberculosis were detected. Finally, the patient was diagnosed with spherical pneumonia caused by R. mannitolilytica. Anti-infective treatment, symptomatic treatment, and administration of a traditional Chinese medicine decoction were performed based on the syndrome differentiation. After 10 days of treatment, chest CT revealed few lesions in the lower lobe of the right lung, which were significantly reduced compared with those in the past. CONCLUSIONS: Spherical pneumonia caused by R. mannitolilytica has not yet been reported and differential diagnosis is key in clinical diagnosis. When spherical pneumonia is difficult to diagnose, mNGS may be a better alternative.

Xenon-enhanced dual-energy tomosynthesis for functional imaging of respiratory disease-Concept and phantom study.

BACKGROUND: Xenon-enhanced dual-energy (DE) computed tomography (CT) and hyperpolarized noble-gas magnetic resonance imaging (MRI) provide maps of lung ventilation that can be used to detect chronic obstructive pulmonary disease (COPD) early in its development and predict respiratory exacerbations. However, xenon-enhanced DE-CT requires high radiation doses and hyper-polarized noble-gas MRI is expensive and only available at a handful of institutions globally. PURPOSE: To present xenon-enhanced dual-energy tomosynthesis (XeDET) for low-dose, low-cost functional imaging of respiratory disease in an experimental phantom study. METHODS: We propose using digital tomosynthesis to produce Xe-enhanced low-energy (LE) and high-energy (HE) coronal images. DE subtraction of the LE and HE images is used to suppress soft tissues. We used an imaging phantom to investigate image quality in terms of the area under the reciever operating characteristic curve (AUC) for the Non-PreWhitening model observer with an Eye filter and internal noise (NPWEi). The phantom simulated anatomic clutter due to lung parenchyma and attenuation due to soft tissue and lung tissue. Aluminum slats were used to simulate rib structures. A stepwedge consisting of an acrylic casing with sealed cylindrical air-filled cavities was used to simulate ventilation defects with step thicknesses of 0.5, 1, and 2 cm and cylindrical radii of 0.5, 0.75, and 1 cm. The phantom was ventilated with Xe and projection data were acquired using a flat-panel detector, a tube-voltage combination of 60/140 kV with 1.2  mm of copper filtration on the HE spectrum and an angular range of ± 15 ∘ $\pm 15^{\circ}$ in 1° increments. The AUC of a NPWEi observer that has access only to a single coronal slice was calculated from measurements of the three-dimensional noise power spectrum and signal template. The AUC was calculated as a function of ventilation defect thickness and radius for total patient entrance air kermas ranging from 1.42 to 2.84 mGy with and without rib-simulating Al slats. For the AUC analysis, the observer internal noise level was obtained from an ad hoc calibration to a high-dose data set. RESULTS: XeDET was able to suppress parenchyma-simulating clutter in coronal images enabling visualization of the simulated ventilation defects, but the limited angle acquisition resulted in residual clutter due to out-of-plane bone-mimmicking structures. The signal power of the defects increased linearly with defect radius and showed a ten-fold to fifteen-fold increase in signal power when the defect thickness increased from 0.5 to 2 cm. These trends agreed with theoretical predictions. Along the depth dimension, the power of the defects decreased exponentially with distance from the center of the defects with full-width half maxima that varied from 1.85 to 2.85 cm depending on the defect thickness and radius. The AUCs of the 1-cm-radius defect that was 2 cm in thickness ranged from good (0.8-0.9) to excellent (0.9-1.0) over the range of air kermas considered. CONCLUSIONS: Xenon-enhanced DE tomosynthesis has the potential to enable functional imaging of respiratory disease and should be further investigated as a low-cost alternative to MRI-based approaches and a low-dose alternative to CT-based approaches.

Dual-energy CT lung perfusion in systemic sclerosis: preliminary experience in 101 patients.

OBJECTIVES: To investigate lung perfusion in systemic sclerosis (SSc). METHODS: The study population included 101 patients who underwent dual-energy CT (DECT) in the follow-up of SSc with pulmonary function tests obtained within 2 months. Fifteen patients had right heart catheterization-proven PH. RESULTS: Thirty-seven patients had no SSc-related lung involvement (Group A), 56 patients had SSc-related interstitial lung disease (Group B) of variable extent (Group B mild: ≤ 10% of lung parenchyma involved: n = 17; Group B moderate: between 11 and 50%: n = 31; Group B severe: > 50%: n = 8), and 8 patients had PVOD/PCH (Group C). Lung perfusion was abnormal in 8 patients in Group A (21.6%), 14 patients in Group B (25%), and 7 patients in Group C (87.5%). In Group A and Group B mild (n = 54), (a) patients with abnormal lung perfusion (n = 14; 26%) had a higher proportion of NYHA III/IV scores of dyspnea (7 [50%] vs 7 [17.5%]; p = 0.031) and a shorter mean walking distance at the 6MWT (397.0 [291.0; 466.0] vs 495.0 [381.0; 549.0]; p = 0.042) but no evidence of difference in the DLCO% predicted (61.0 [53.0; 67.0] vs 68.0 [61.0; 78.0]; p = 0.055) when compared to patients with normal lung perfusion (n = 40; 74%); (b) a negative correlation was found between the iodine concentration in both lungs and the DLCO% predicted but it did not reach statistical significance (r = -0.27; p = 0.059) and no correlation was found with the PAPs (r = 0.16; p = 0.29) and walking distance during the 6MWT (r = -0.029; p = 0.84). CONCLUSIONS: DECT lung perfusion provides complementary information to standard HRCT scans, depicting perfusion changes in SSc patients with normal or minimally infiltrated lung parenchyma. KEY POINTS: • In a retrospective observational study of 101 consecutive patients with SSc, dual-energy CT pulmonary angiography was obtained to evaluate lung perfusion. • Lung perfusion was abnormal in 14 out of 54 patients (26%) with no or mild SSc-related lung infiltration. • Patients with abnormal perfusion and no or mild SSc-related lung infiltration had more severe scores of dyspnea and shorter walking distance than patients with similar lung findings and normal perfusion, suggesting the presence of small vessel vasculopathy.

Pulmonary and Systemic Pathology in COVID-19­Holistic Pathological Analyses

BACKGROUND: The COVID-19 pandemic is the third worldwide coronavirus-associated disease outbreak in the past 20 years. Lung involvement, with acute respiratory distress syndrome (ARDS) in severe cases, is the main clinical feature of this disease; the cardiovascular system, the central nervous system, and the gastrointestinal tract can also be affected. The pathophysiology of both pulmonary and extrapulmonary organ damage was almost completely unknown when the pandemic began. METHODS: This review is based on pertinent publications retrieved by a selective search concerning the structural changes and pathophysiology of COVID-19, with a focus on imaging techniques. RESULTS: Immunohistochemical, electron-microscopic and molecular pathological analyses of tissues obtained by autopsy have improved our understanding of COVID-19 pathophysiology, including molecular regulatory mechanisms. Intussusceptive angiogenesis (IA) has been found to be a prominent pattern of damage in the affected organs of COVID-19 patients. In IA, an existing vessel changes by invagination of the endothelium and formation of an intraluminal septum, ultimately giving rise to two new lumina. This alters hemodynamics within the vessel, leading to a loss of laminar flow and its replacement by turbulent, inhomogeneous flow. IA, which arises because of ischemia due to thrombosis, is itself a risk factor for the generation of further microthrombi; these have been detected in the lungs, heart, liver, kidneys, brain, and placenta of COVID-19 patients. CONCLUSION: Studies of autopsy material from various tissues of COVID-19 patients have revealed ultrastructural evidence of altered microvascularity, IA, and multifocal thrombi. These changes may contribute to the pathophysiology of post-acute interstitial fibrotic organ changes as well as to the clinical picture of long COVID.

Sansoninto-induced Lung Injury.

A man in his 70s visited our department for dyspnea with pulmonary infiltrate that was unresolved by antibiotics. He had been taking Sansoninto for five years and doubled its dose a month ago. After discontinuing Sansoninto without any additional medications, his symptoms gradually disappeared, and pulmonary infiltration improved. Drug lymphocyte stimulation tests showed a positive result for Sansoninto. We diagnosed this patient with Sansoninto-induced lung injury. Sansoninto is a combination drug that consists of sansonin, bukuryo, senkyo, chimo, and kanzo. This paper reports the first case of Sansoninto-induced lung injury and discusses the mechanism considering its components.

Inhalation injury in adult males: Evaluation of the short-term efficacy of transcutaneous electrical acupoint stimulation on pulmonary functions and diaphragmatic mobility after burn: A double-blind randomized controlled study.

BACKGROUND: Inhalation injuries can cause problems with diaphragmatic mobility and pulmonary function, which are accompanied by significant morbidity and mortality. No previous studies have determined the outcomes of acupoint transcutaneous electrical stimulation (Acu-TENS) in the treatment of inhalation burn injuries. The current study is therefore aimed at evaluating the influences of Acu-TENS on pulmonary functions and diaphragmatic mobility in adult-male patients experiencing after burn inhalation injury. METHODS: This randomized controlled study was double blinded in an inpatient setting and was conducted between June 2018 and July 2019. Forty-male participants with inhalation-injury (20-40 yrs.) were randomly allocated into two study and control groups equal in numbers; the same pulmonary rehabilitation program plus early mobility exercise was conducted in both groups. The study group (group A) received additional Acu-TENS while shame Acu-TENS was carried out on the control group (group B). The intervention program continued for four weeks, three sessions a week for 45 min bilaterally on the bilateral Ding-Chuan points (Ex-B1). Spirometry was used to assess pulmonary functions, the 5-points-Likert scale was used to assess dyspnea, and ultrasonography was used to assess diaphragmatic mobility (DM), and evaluations were performed before and after interventions. RESULTS: At baseline assessment, no significant differences were detected between the two study groups (p˃0.05). In the post-interventional program, a noteworthy difference was detected in all outcome measures in the two study groups (p˂0.05), supporting group A. After 4 weeks of intervention, the mean (SD) for FVC, FEV1, and DM was 83.7 ± 4.34, 86.75 ± 4.59, and 5.93 ± 1.13 in group A, 79.65 ± 5.14, 83.1 ± 4.44, and 5.08 ± 1.15, in-group B. The mean difference for FVC, FEV1, and DM was 4.05 (1: 7.09), 3.65 (0.75: 6.54), and 0.85 (0.11: 1.57) between groups after treatment, respectively. CONCLUSION: Depending on the study findings, Acu-TENS on bilateral Ding-Chuan points could be considered an effective approach for improving pulmonary functions and diaphragmatic mobility in patients with inhalation injuries after thermal burn. Future studies with a larger sample size and longer duration on different types of burn injuries are recommended.

Chest X-Ray Diagnostic Quality Assessment: How Much Is Pixel-Wise Supervision Needed?

Chest X-ray is an important imaging method for the diagnosis of chest diseases. Chest radiograph diagnostic quality assessment is vital for the diagnosis of the disease because unqualified radiographs have negative impacts on doctors' diagnosis and thus increase the burden on patients due to the re-acquirement of the radiographs. So far no algorithms and public data sets have been developed for chest radiograph diagnostic quality assessment. Towards effective chest X-ray diagnostic quality assessment, we analyze the image characteristics of four main chest radiograph diagnostic quality issues, i.e. Scapula Overlapping Lung, Artifact, Lung Field Loss, and Clavicle Unflatness. Our experiments show that general image classification methods are not competent for the task because the detailed information used for quality assessment by radiologists cannot be fully exploited by deep CNNs and image-level annotations. Then we propose to leverage a multi-label semantic segmentation framework to find the problematic regions, and then classify the quality issues based on the results of segmentation. However, subsequent classification is often negatively affected by certain small segmentation errors. Therefore, we propose to estimate a distance map that measures the distance from a pixel to its nearest segment, and use it to force the prediction of semantic segmentation more holistic and suitable for classification. Extensive experiments validate the effectiveness of our semantic-segmentation-based solution for chest X-ray diagnostic quality assessment. However, general segmentation-based algorithms requires fine pixel-wise annotations in the era of deep learning. In order to reduce reliance on fine annotations and further validate how important pixel-wise annotations are, weak supervision for segmentation is applied, and demonstrates its ability close to that of full supervision. Finally, we present ChestX-rayQuality, a chest radiograph data set, which comprises 480 frontal-view chest radiographs with semantic segmentation annotations and four labels of quality issue. Also, other 1212 chest radiographs with limited annotations are imported to validate our algorithms and arguments on larger data set. These two data set will be made publicly available.

Pycnogenol®-Centellicum® supplementation improves lung fibrosis and post-COVID-19 lung healing.

BACKGROUND: The aim of this study was to evaluate the combination of Pycnogenol® (150 mg/day) (Horphag Research, London, UK) and Centella asiatica (Centellicum® 3×225 mg/day; Horphag Research) (PY-CE) for 8 months in subjects with sequelae of idiopathic interstitial pneumonia (IIP). Recently, post-COVID-19 lung disease is emerging with large numbers of patients left with chronic lung conditions. Considering the antifibrotic activity of the combination PY-CE, we also tested this supplementary management in post-COVID-19 lung patients. METHODS: Nineteen subjects with idiopathic interstitial pneumonia (IIP) were included in the study. High Resolution CT scans at inclusion confirmed the presence of lung fibrosis: 10 patients were treated with the Pycnogenol® Centellicum® combination and 9 subjects with standard management (SM) served as controls. Oxidative stress that was very high in all subjects at inclusion, decreased significantly in the supplement group (P<0.05). The Karnofsky Performance Scale Index significantly improved in the supplement group in comparison with controls (P<0.05). The symptoms (fatigue, muscular pain, dyspnea) were significantly lower after 8 months in supplemented patients (P<0.05) as compared with controls. RESULTS: At the end of the study, the small cystic lesions (honeycombing) and traction bronchiectasis were stable or in partial regression in 4 subjects in the supplemented group (vs. none in the control group) with a significant improvement in tissue edema in the supplemented subjects. On ultrasound lung scans the white (more echogenic) fibrotic component at inclusion was 18.5±2.2% in the images in controls vs. 19.4±2.7% in the supplement group. At the end of the study, there was no improvement in controls (18.9±2.5%) vs. a significant improvement in supplemented subjects (16.2±2.1%; P<0.05). In addition, 18 subjects with post-COVID-19 lung disease were included in the study; 10 patients were treated with the Pycnogenol® Centellicum® combination and evaluated after 4 weeks; 8 patients served as controls. Preliminary results show that symptoms associated with post-COVID-19 lung disease after 4 weeks were significantly improved with the supplement combination (P<0.05). Oxidative stress and the Karnofsky Performance Scale Index were significantly improved in the supplements group as compared with controls (P<0.05). CONCLUSIONS: According to these observations, Pycnogenol® controls and decreases edema and Centellicum® by modulating the apposition of collagen, slows down the development of irregular cicatrization, the keloidal scarring and fibrosis. More time is needed to evaluate this effect in a larger number of post-COVID-19 patients with lung disease. This disease has affected millions of subjects worldwide, leaving severe consequences. Pycnogenol® and Centellicum® may improve the residual clinical picture in post-COVID-19 lung disease (PCL) patients and may reduce the number of subjects evolving into lung fibrosis. The evolution from edema to fibrosis seems to be slower or attenuated with this supplement combination both in Idiopathic pulmonary fibrosis (IPF) and in PCL patients.

The Impact of Interstitial Diseases Patterns on Lung CT Segmentation.

Lung segmentation represents a fundamental step in the development of computer-aided decision systems for the investigation of interstitial lung diseases. In a holistic lung analysis, eliminating background areas from Computed Tomography (CT) images is essential to avoid the inclusion of noise information and spend unnecessary computational resources on non-relevant data. However, the major challenge in this segmentation task relies on the ability of the models to deal with imaging manifestations associated with severe disease. Based on U-net, a general biomedical image segmentation architecture, we proposed a light-weight and faster architecture. In this 2D approach, experiments were conducted with a combination of two publicly available databases to improve the heterogeneity of the training data. Results showed that, when compared to the original U-net, the proposed architecture maintained performance levels, achieving 0.894 ± 0.060, 4.493 ± 0.633 and 4.457 ± 0.628 for DSC, HD and HD-95 metrics, respectively, when using all patients from the ILD database for testing only, while allowing a more effficient computational usage. Quantitative and qualitative evaluations on the ability to cope with high-density lung patterns associated with severe disease were conducted, supporting the idea that more representative and diverse data is necessary to build robust and reliable segmentation tools.