Assessment of pulmonary vascular anatomy: comparing augmented reality by holograms versus standard CT images/reconstructions using surgical findings as reference standard.

BACKGROUND: We compared computed tomography (CT) images and holograms (HG) to assess the number of arteries of the lung lobes undergoing lobectomy and assessed easiness in interpretation by radiologists and thoracic surgeons with both techniques. METHODS: Patients scheduled for lobectomy for lung cancer were prospectively included and underwent CT for staging. A patient-specific three-dimensional model was generated and visualized in an augmented reality setting. One radiologist and one thoracic surgeon evaluated CT images and holograms to count lobar arteries, having as reference standard the number of arteries recorded at surgery. The easiness of vessel identification was graded according to a Likert scale. Wilcoxon signed-rank test and κ statistics were used. RESULTS: Fifty-two patients were prospectively included. The two doctors detected the same number of arteries in 44/52 images (85%) and in 51/52 holograms (98%). The mean difference between the number of artery branches detected by surgery and CT images was 0.31 ± 0.98, whereas it was 0.09 ± 0.37 between surgery and HGs (p = 0.433). In particular, the mean difference in the number of arteries detected in the upper lobes was 0.67 ± 1.08 between surgery and CT images and 0.17 ± 0.46 between surgery and holograms (p = 0.029). Both radiologist and surgeon showed a higher agreement for holograms (κ = 0.99) than for CT (κ = 0.81) and found holograms easier to evaluate than CTs (p < 0.001). CONCLUSIONS: Augmented reality by holograms is an effective tool for preoperative vascular anatomy assessment of lungs, especially when evaluating the upper lobes, more prone to anatomical variations. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04227444 RELEVANCE STATEMENT: Preoperative evaluation of the lung lobe arteries through augmented reality may help the thoracic surgeons to carefully plan a lobectomy, thus contributing to optimize patients' outcomes. KEY POINTS: • Preoperative assessment of the lung arteries may help surgical planning. • Lung artery detection by augmented reality was more accurate than that by CT images, particularly for the upper lobes. • The assessment of the lung arterial vessels was easier by using holograms than CT images.

Novel Scoring Scale for Quality Assessment of Lung Ultrasound in the Emergency Department.

Introduction: The use of a reliable scoring system for quality assessment (QA) is imperative to limit inconsistencies in measuring ultrasound acquisition skills. The current grading scale used for QA endorsed by the American College of Emergency Physicians (ACEP) is non-specific, applies irrespective of the type of study performed, and has not been rigorously validated. Our goal in this study was to determine whether a succinct, organ-specific grading scale designed for lung-specific QA would be more precise with better interobserver agreement. Methods: This was a prospective validation study of an objective QA scale for lung ultrasound (LUS) in the emergency department. We identified the first 100 LUS performed in normal clinical practice in the year 2020. Four reviewers at an urban academic center who were either emergency ultrasound fellowship-trained or current fellows with at least six months of QA experience scored each study, resulting in a total of 400. The primary outcome was the level of agreement between the reviewers. Our secondary outcome was the variability of the scores given to the studies. For the agreement between reviewers, we computed the intraclass correlation coefficient (ICC) based on a two-way random-effect model with a single rater for each grading scale. We generated 10,000 bootstrapped ICCs to construct 95% confidence intervals (CI) for both grading systems. A two-sided one-sample t-test was used to determine whether there were differences in the bootstrapped ICCs between the two grading systems. Results: The ICC between reviewers was 0.552 (95% CI 0.40-0.68) for the ACEP grading scale and 0.703 (95% CI 0.59-0.79) for the novel grading scale (P < 0.001), indicating significantly more interobserver agreement using the novel scale compared to the ACEP scale. The variance of scores was similar (0.93 and 0.92 for the novel and ACEP scales, respectively). Conclusion: We found an increased interobserver agreement between reviewers when using the novel, organ-specific scale when compared with the ACEP grading scale. Increased consistency in feedback based on objective criteria directed to the specific, targeted organ provides an opportunity to enhance learner education and satisfaction with their ultrasound education.

Clinical application of computed tomographic volumetric imaging in postoperative lung function assessment in patients with lung cancer.

BACKGROUND: To evaluate the effectiveness of the computed tomographic (CT) volumetric analysis in postoperative lung function assessment and the predicting value for postoperative complications in patients who had segmentectomy for lung cancer. METHODS: CT scanning and pulmonary function examination were performed for 100 patients with lung cancer. CT volumetric analyses were performed by specific software, for the volume of the inspiratory phase (Vin), the mean inspiratory lung density (MLDin), the volume of expiratory phase (Vex), and the mean lung density at expiratory phase (MLDex). Pulmonary function examination results and CT volumetric analysis results were used to predict postoperative lung function. The concordance and correlations of these values were assessed by Bland-Altman analysis and Pearson correlation analysis, respectively. Multivariate binomial logistic regression analysis was executed to assess the associations of CT data with complication occurrence. RESULTS: Correlations between CT scanning data and pulmonary function examination results were significant in both pre- and post-operation (0.8083 ≤ r ≤ 0.9390). Forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), and the ratio of FVC and FEV1 estimated by CT volumetric analyses showed high concordance with those detected by pulmonary function examination. Preoperative (Vin-Vex) and (MLDex- MLDin) values were identified as predictors for post-surgery complications, with hazard ratios of 5.378 and 6.524, respectively. CONCLUSIONS: CT volumetric imaging analysis has the potential to determine the pre- and post-operative lung function, as well as to predict post-surgery complication occurrence in lung cancer patients with pulmonary lobectomy.

Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study.

BACKGROUND: Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligence (AI)-based segmentation could be applied to identify ILAs using two COPD cohorts. METHODS: ILAs were diagnosed visually based on the Fleischner Society definition. Using an AI-based method, ground-glass opacities, reticulations, and honeycombing were segmented, and their volumes were summed to obtain the percentage ratio of interstitial lung disease-associated volume to total lung volume (ILDvol%). The optimal ILDvol% threshold for ILA detection was determined in cross-sectional data of the discovery and validation cohorts. The 5-year longitudinal changes in ILDvol% were calculated in discovery cohort patients who underwent baseline and follow-up CT scans. RESULTS: ILAs were found in 32 (14%) and 15 (10%) patients with COPD in the discovery (n = 234) and validation (n = 153) cohorts, respectively. ILDvol% was higher in patients with ILAs than in those without ILA in both cohorts. The optimal ILDvol% threshold in the discovery cohort was 1.203%, and good sensitivity and specificity (93.3% and 76.3%) were confirmed in the validation cohort. 124 patients took follow-up CT scan during 5 ± 1 years. 8 out of 124 patients (7%) developed ILAs. In a multivariable model, an increase in ILDvol% was associated with ILA development after adjusting for age, sex, BMI, and smoking exposure. CONCLUSION: AI-based CT quantification of ILDvol% may be a reproducible method for identifying and monitoring ILAs in patients with COPD.

Assessment of Left Lung Remodeling With Magnetic Resonance Imaging in a Murine Model Following Exposure to Douglas Fir Smoke.

Wildland firefighters (WLFFs) experience lung function decline due to occupational exposure to fire smoke. WLFFs typically do not wear respiratory personal protective equipment, and if they do, it is a simple bandana, which is not effective at filtering smoke. To pinpoint the biological underpinnings of abnormal respiratory function following 3-7 years of WLFF service, we exposed mice to Douglas fir smoke (DFS) over 8 weeks. Following exposure, we assessed changes in lung structure through Magnetic Resonance Imaging (MRI) and histological analysis, which was supported by immunohistochemistry staining. With MRI, we found that the signal decay time, T2*, from ultrashort echo time (UTE) images was significantly shorter in mice exposed to DFS compared to air controls. In addition, the variation in T2* was more heterogeneously distributed throughout the left lung in DFS-exposed mice, compared to air controls. As confirmed by histological analysis, shorter T2* was caused by larger parenchyma airspace sizes and not fibrotic remodeling. Destruction of the alveolar spaces was likely due to inflammation, as measured by an influx of CD68+ macrophages and destruction due to enhanced neutrophil elastase. In addition, measurements of airspace dimensions from histology were more heterogeneously distributed throughout the lung, corroborating the enhanced relative dispersion of T2*. Findings from this study suggest that the decline in lung function observed in WLFFs may be due to emphysema-like changes in the lung, which can be quantified with MRI.

Pulmonary abscess with atypical topography - computed tomography assessment before and after treatment.

INTRODUCTION: We present a clinical case of a patient with neurological sequelae, dementia, gastrostomy and tracheostomy with a metal canula, who developed a lung abscess in an atypical topography, in the anterior segment of the left upper lobe, being attended to in the emergency department. CASE PRESENTATION: A 79-year-old man who was bedridden and with neurological sequelae resulting from a hemorrhagic stroke, with gastrostomy and tracheostomy with a metal canula, was attended for daily fever and increased secretion trough the canula, and a diagnosis of bronchoaspiration pneumonia was made. The chest X-ray was unremarkable with an evaluation impaired by the patient's posture. The chest CT showed a characteristic image of an abscess in the topography of the anterior segment of the upper lobe. Improvement in the patient`s clinical condition was accompanied by an improvement in the CT imaging results. And the other exams carried out did not show any other associated lung disease. DISCUSSION: Chest X-ray is still the initial method for studying infectious lung lesions, and CT is indicated in cases where the appearance of the lesion is not well defined, if doubts persist, whether the patient is immunosuppressed or oncological. CT can provide better definition of abscess imaging findings and is particularly useful for visualizing cavities not well delineated by X-ray, especially when a malignant neoplastic tumor lesion is suspected or when there is an associated pleural collection.

Severity-stratification of interstitial lung disease by deep learning enabled assessment and quantification of lesion indicators from HRCT images.

BACKGROUND: Interstitial lung disease (ILD) represents a group of chronic heterogeneous diseases, and current clinical practice in assessment of ILD severity and progression mainly rely on the radiologist-based visual screening, which greatly restricts the accuracy of disease assessment due to the high inter- and intra-subjective observer variability. OBJECTIVE: To solve these problems, in this work, we propose a deep learning driven framework that can assess and quantify lesion indicators and outcome the prediction of severity of ILD. METHODS: In detail, we first present a convolutional neural network that can segment and quantify five types of lesions including HC, RO, GGO, CONS, and EMPH from HRCT of ILD patients, and then we conduct quantitative analysis to select the features related to ILD based on the segmented lesions and clinical data. Finally, a multivariate prediction model based on nomogram to predict the severity of ILD is established by combining multiple typical lesions. RESULTS: Experimental results showed that three lesions of HC, RO, and GGO could accurately predict ILD staging independently or combined with other HRCT features. Based on the HRCT, the used multivariate model can achieve the highest AUC value of 0.755 for HC, and the lowest AUC value of 0.701 for RO in stage I, and obtain the highest AUC value of 0.803 for HC, and the lowest AUC value of 0.733 for RO in stage II. Additionally, our ILD scoring model could achieve an average accuracy of 0.812 (0.736 - 0.888) in predicting the severity of ILD via cross-validation. CONCLUSIONS: In summary, our proposed method provides effective segmentation of ILD lesions by a comprehensive deep-learning approach and confirms its potential effectiveness in improving diagnostic accuracy for clinicians.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations.

The American College of Radiology created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

The role of lung and cardiac ultrasound for cardiovascular hemodynamic assessment of women with preeclampsia.

Preeclampsia remains the leading cause of maternal morbidity and mortality and is associated with abnormal body fluid homeostasis and cardiovascular dysfunction. Moreover, 2 distinct hemodynamic phenotypes have been described in preeclampsia, which might require different therapeutic approaches. Fluid restriction is mandatory in women at risk of pulmonary edema, whereas additional fluid administration may be required to correct tissue hypoperfusion in women with intravascular volume depletion. As clinical examination alone cannot discriminate among different hemodynamic patterns, optimal management of women with preeclampsia remains challenging. Noninvasive bedside ultrasound has become an important diagnostic and monitoring tool in critically ill patients, and it has been demonstrated that it can also be used in the monitoring of women with preeclampsia. Echocardiography in combination with lung ultrasound provides information on hemodynamic status, cardiac function, lung congestion, and fluid responsiveness and, therefore, could help clinicians identify women at higher risk of life-threatening complications. This review describes the cardiovascular changes in preeclampsia and provides an overview of the ultrasound methodologies that could be efficiently used for better hemodynamic assessment and management of women with preeclampsia.

A systematic assessment and optimization of photon-counting CT for lung density quantifications.

BACKGROUND: Photon-counting computed tomography (PCCT) has recently emerged into clinical use; however, its optimum imaging protocols and added benefits remains unknown in terms of providing more accurate lung density quantification compared to energy-integrating computed tomography (EICT) scanners. PURPOSE: To systematically assess the performance of a clinical PCCT scanner for lung density quantifications and compare it against EICT. METHODS: This cross-sectional study involved a retrospective analysis of subjects scanned (August-December 2021) using a clinical PCCT system. The influence of altering reconstruction parameters was studied (reconstruction kernel, pixel size, slice thickness). A virtual CT dataset of anthropomorphic virtual subjects was acquired to demonstrate the correspondence of findings to clinical dataset, and to perform systematic imaging experiments, not possible using human subjects. The virtual subjects were imaged using a validated, scanner-specific CT simulator of a PCCT and two EICT (defined as EICT A and B) scanners. The images were evaluated using mean absolute error (MAE) of lung and emphysema density against their corresponding ground truth. RESULTS: Clinical and virtual PCCT datasets showed similar trends, with sharper kernels and smaller voxel sizes increasing percentage of low-attenuation areas below -950 HU (LAA-950) by up to 15.7 ± 6.9% and 11.8 ± 5.5%, respectively. Under the conditions studied, higher doses, thinner slices, smaller pixel sizes, iterative reconstructions, and quantitative kernels with medium sharpness resulted in lower lung MAE values. While using these settings for PCCT, changes in the dose level (13 to 1.3 mGy), slice thickness (0.4 to 1.5 mm), pixel size (0.49 to 0.98 mm), reconstruction technique (70 keV-VMI to wFBP), and kernel (Qr48 to Qr60) increased lung MAE by 15.3 ± 2.0, 1.4 ± 0.6, 2.2 ± 0.3, 4.2 ± 0.8, and 9.1 ± 1.6 HU, respectively. At the optimum settings identified per scanner, PCCT images exhibited lower lung and emphysema MAE than those of EICT scanners (by 2.6 ± 1.0 and 9.6 ± 3.4 HU, compared to EICT A, and by 4.8 ± 0.8 and 7.4 ± 2.3 HU, compared to EICT B). The accuracy of lung density measurements was correlated with subjects' mean lung density (p < 0.05), measured by PCCT at optimum setting under the conditions studied. CONCLUSION: Photon-counting CT demonstrated superior performance in density quantifications, with its influences of imaging parameters in line with energy-integrating CT scanners. The technology offers improvement in lung quantifications, thus demonstrating potential toward more objective assessment of respiratory conditions.

Transfer Learning-Based B-Line Assessment of Lung Ultrasound for Acute Heart Failure.

OBJECTIVE: B-lines assessed by lung ultrasound (LUS) outperform physical exam, chest radiograph, and biomarkers for the associated diagnosis of acute heart failure (AHF) in the emergent setting. The use of LUS is however limited to trained professionals and suffers from interpretation variability. The objective was to utilize transfer learning to create an AI-enabled software that can aid novice users to automate LUS B-line interpretation. METHODS: Data from an observational AHF LUS study provided standardized cine clips for AI model development and evaluation. A total of 49,952 LUS frames from 30 patients were hand scored and trained on a convolutional neural network (CNN) to interpret B-lines at the frame level. A random independent evaluation set of 476 LUS clips from 60 unique patients assessed model performance. The AI models scored the clips on both a binary and ordinal 0-4 multiclass assessment. RESULTS: A multiclassification AI algorithm had the best performance at the binary level when applied to the independent evaluation set, AUC of 0.967 (95% CI 0.965-0.970) for detecting pathologic conditions. When compared to expert blinded reviewer, the 0-4 multiclassification AI algorithm scale had a reported linear weighted kappa of 0.839 (95% CI 0.804-0.871). CONCLUSIONS: The multiclassification AI algorithm is a robust and well performing model at both binary and ordinal multiclass B-line evaluation. This algorithm has the potential to be integrated into clinical workflows to assist users with quantitative and objective B-line assessment for evaluation of AHF.

90Y post-radioembolization clinical assessment with whole-body Biograph Vision Quadra PET/CT: image quality, tumor, liver and lung dosimetry.

PURPOSE: Evaluation of 90Y liver radioembolization post-treatment clinical data using a whole-body Biograph Vision Quadra PET/CT to investigate the potential of protocol optimization in terms of scan time and dosimetry. METHODS: 17 patients with hepatocellular carcinoma with median (IQR) injected activity 2393 (1348-3298) MBq were included. Pre-treatment dosimetry plan was based on 99mTc-MAA SPECT/CT with Simplicit90Y™ and post-treatment validation with Quadra using Simplicit90Y™ and HERMIA independently. Regarding the image analysis, mean and peak SNR, the coefficient of variation (COV) and lesion-to-background ratio (LBR) were evaluated. For the post-treatment dosimetry validation, the mean tumor, whole liver and lung absorbed dose evaluation was performed using Simplicit90Y and HERMES. Images were reconstructed with 20-, 15-, 10-, 5- and 1- min sinograms with 2, 4, 6 and 8 iterations. Wilcoxon signed rank test was used to show statistical significance (p < 0.05). RESULTS: There was no difference of statistical significance between 20- and 5- min reconstructed times for the peak SNR, COV and LBR. In addition, there was no difference of statistical significance between 20- and 1- min reconstructed times for all dosimetry metrics. Lung dosimetry showed consistently lower values than the expected. Tumor absorbed dose based on Simplicit90Y™ was similar to the expected while HERMES consistently underestimated significantly the measured tumor absorbed dose. Finally, there was no difference of statistical significance between expected and measured tumor, whole liver and lung dose for all reconstruction times. CONCLUSION: In this study we evaluated, in terms of image quality and dosimetry, whole-body PET clinical images of patients after having been treated with 90Y microspheres radioembolization for liver cancer. Compared to the 20-min standard scan, the simulated 5-min reconstructed images provided equal image peak SNR and noise behavior, while performing also similarly for post-treatment dosimetry of tumor, whole liver and lung absorbed doses.

Lung Ultrasound Assessment of Lung Hyperinflation in Patients with Stable COPD: An Effective Diagnostic Tool.

Purpose: To evaluate the degree of lung hyperinflation (LH) in patients with stable chronic obstructive pulmonary disease (COPD) by lung ultrasound score (LUS) and assess its value. Patients and Methods: We conducted a study of 149 patients with stable COPD and 100 healthy controls recruited by the Second Affiliated Hospital of Fujian Medical University. The pleural sliding displacement (PSD) was measured, the sliding of the pleura in different areas was observed, and LUS was calculated from both of them. The diaphragm excursion (DE), residual capacity (RV), total lung capacity (TLC), inspiratory capacity (IC) and functional residual capacity (FRC) were measured. We described the correlation between ultrasound indicators and pulmonary function indicators reflecting LH. Multiple linear regression analysis was used. The ROC curves of LUS and DE were drawn to evaluate their diagnostic efficacy, and De Long method was used for comparison. Results: (1) The LUS of patients with stable COPD were positively correlated with RV, TLC, RV/TLC and FRC and negatively correlated with IC and IC/TLC (r1=0.72, r2=0.41, r3=0.72, r4=0.70, r5=-0.56, r6=-0.65, P < 0.001). The correlation was stronger than that between DE at maximal deep inspiration and the corresponding pulmonary function indices (r1=-0.41, r2=-0.26, r3=-0.40, r4=-0.43, r5=0.30, r6=0.37, P < 0.001). (2) Multiple linear regression analysis showed that LUS were significantly correlated with IC/TLC and RV/TLC. (3) With IC/TLC<25% and RV/TLC>60% as the diagnostic criterion of severe LH, the areas under the ROC curves of LUS and DE at maximal deep inspiration for diagnosing severe LH were 0.914 and 0.385, 0.845 and 0.543, respectively (P < 0.001). Conclusion: The lung ultrasound score is an important parameter for evaluating LH. LUS is better than DE at maximal deep inspiration for diagnosing severe LH and is expected to become an effective auxiliary tool for evaluating LH.

[Radiological assessment of interstitial lung disease: what can lung ultrasound do?]

The use of lung ultrasound in the screening, diagnosis, and evaluation of interstitial lung disease has been relatively well studied, but has not been widely accepted and applied in clinical practice. There are also some differences in the examination methods applied in these studies. This paper summarized the application, advantages, and disadvantages of lung ultrasound in the diagnosis and follow-up of interstitial lung disease by comprehensively reviewing the examination methods, research results and progress of new technologies of lung ultrasound in interstitial lung disease.

Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis.

The integration of artificial intelligence (AI) with Digital Twins (DTs) has emerged as a promising approach to revolutionize healthcare, particularly in terms of diagnosis and management of thoracic disorders. This study proposes a comprehensive framework, named Lung-DT, which leverages IoT sensors and AI algorithms to establish the digital representation of a patient's respiratory health. Using the YOLOv8 neural network, the Lung-DT system accurately classifies chest X-rays into five distinct categories of lung diseases, including "normal", "covid", "lung_opacity", "pneumonia", and "tuberculosis". The performance of the system was evaluated employing a chest X-ray dataset available in the literature, demonstrating average accuracy of 96.8%, precision of 92%, recall of 97%, and F1-score of 94%. The proposed Lung-DT framework offers several advantages over conventional diagnostic methods. Firstly, it enables real-time monitoring of lung health through continuous data acquisition from IoT sensors, facilitating early diagnosis and intervention. Secondly, the AI-powered classification module provides automated and objective assessments of chest X-rays, reducing dependence on subjective human interpretation. Thirdly, the twin digital representation of the patient's respiratory health allows for comprehensive analysis and correlation of multiple data streams, providing valuable insights as to personalized treatment plans. The integration of IoT sensors, AI algorithms, and DT technology within the Lung-DT system demonstrates a significant step towards improving thoracic healthcare. By enabling continuous monitoring, automated diagnosis, and comprehensive data analysis, the Lung-DT framework has enormous potential to enhance patient outcomes, reduce healthcare costs, and optimize resource allocation.

CT-based Assessment at 6-Month Follow-up of COVID-19 Pneumonia patients in China.

This study aimed to assess pulmonary changes at 6-month follow-up CT and predictors of pulmonary residual abnormalities and fibrotic-like changes in COVID-19 pneumonia patients in China following relaxation of COVID restrictions in 2022. A total of 271 hospitalized patients with COVID-19 pneumonia admitted between November 29, 2022 and February 10, 2023 were prospectively evaluated at 6 months. CT characteristics and Chest CT scores of pulmonary abnormalities were compared between the initial and the 6-month CT. The association of demographic and clinical factors with CT residual abnormalities or fibrotic-like changes were assessed using logistic regression. Follow-up CT scans were obtained at a median of 177 days (IQR, 170-185 days) after hospital admission. Pulmonary residual abnormalities and fibrotic-like changes were found in 98 (36.2%) and 39 (14.4%) participants. In multivariable analysis of pulmonary residual abnormalities and fibrotic-like changes, the top three predictive factors were invasive ventilation (OR 13.6; 95% CI 1.9, 45; P < .001), age > 60 years (OR 9.1; 95% CI 2.3, 39; P = .01), paxlovid (OR 0.11; 95% CI 0.04, 0.48; P = .01) and invasive ventilation (OR 10.3; 95% CI 2.9, 33; P = .002), paxlovid (OR 0.1; 95% CI 0.03, 0.48; P = .01), smoker (OR 9.9; 95% CI 2.4, 31; P = .01), respectively. The 6-month follow-up CT of recent COVID-19 pneumonia cases in China showed a considerable proportion of the patients with pulmonary residual abnormalities and fibrotic-like changes. Antivirals against SARS-CoV-2 like paxlovid may be beneficial for long-term regression of COVID-19 pneumonia.

Pilot study of paediatric regional lung function assessment via X-ray velocimetry (XV) imaging in children with normal lungs and in children with cystic fibrosis.

INTRODUCTION: Cystic fibrosis (CF) is a life-limiting autosomal recessive genetic condition. It is caused by mutations in the gene that encodes for a chloride and bicarbonate conducting transmembrane channel. X-ray velocimetry (XV) is a novel form of X-ray imaging that can generate lung ventilation data through the breathing cycle. XV technology has been validated in multiple animal models, including the ß-ENaC mouse model of CF lung disease. It has since been assessed in early-phase clinical trials in adult human subjects; however, there is a paucity of data in the paediatric cohort, including in CF. The aim of this pilot study was to investigate the feasibility of performing a single-centre cohort study in paediatric patients with CF and in those with normal lungs to demonstrate the appropriateness of proceeding with further studies of XV in these cohorts. METHODS AND ANALYSIS: This is a cross-sectional, single-centre, pilot study. It will recruit children aged 3-18 years to have XV lung imaging performed, as well as paired pulmonary function testing. The study will aim to recruit 20 children without CF with normal lungs and 20 children with CF. The primary outcome will be the feasibility of recruiting children and performing XV testing. Secondary outcomes will include comparisons between XV and current assessments of pulmonary function and structure. ETHICS AND DISSEMINATION: This project has ethical approval granted by The Women's and Children's Hospital Human Research Ethics Committee (HREC ID 2021/HRE00396). Findings will be disseminated through peer-reviewed publication and conferences. TRIAL REGISTRATION NUMBER: ACTRN12623000109606.

Assessment of mediastinal shift angles in congenital pulmonary airway malformation: a new fetal magnetic resonance imaging indicator of congenital lung disease.

BACKGROUND: The mediastinal shift angle is a new fetal magnetic resonance imaging (MRI) index that is reportedly correlated with postnatal survival in fetuses with congenital diaphragmatic hernia. However, its correlation in patients with congenital pulmonary airway malformation (CPAM) has not been assessed. OBJECTIVE: This study aimed to establish a normal range for the right/left mediastinal shift angles, to evaluate the mediastinal shift angle in fetuses with CPAM, to compare the mediastinal shift angle with the CPAM volume ratio, and to evaluate the predictive value of the mediastinal shift angle measurements. MATERIALS AND METHODS: To establish the normal range, we measured the mediastinal shift angle bilaterally in 124 fetuses without any lung abnormality (the control group). Subsequently, the mediastinal shift angle was measured in 32 fetuses pathologically diagnosed with CPAM. Moreover, the mediastinal shift angle and CPAM volume ratio were compared using fetal MRI. RESULTS: The mean values for the right/left mediastinal shift angles were 18.6°/26.3° and 39.2°/35.9° for control fetuses and fetuses with CPAM, respectively. The mediastinal shift angle and the CPAM volume ratio showed a positive statistical correlation. The area under the curve demonstrated high discriminatory accuracy for the mediastinal shift angle (0.76). CONCLUSION: The mediastinal shift angle has potential to replace the CPAM volume ratio for evaluating the severity of CPAM in fetal MRI.

A novel gelatinized barium sulfate injection method for assessment of bronchoalveolar lavage parameters.

INTRODUCTION: Bronchoalveolar lavage (BAL) is frequently used in pulmonary medicine though it requires further optimization. Practical obstacles such as patient safety and procedural limitation have to date precluded large, controlled trials aimed at standardization of BAL procedure. Indeed, BAL guidelines are based on observational data. Innovative research methods are necessary to advance the clinical practice of BAL. METHODS: In our study, we evaluated the effect of injecting a gelatinized barium solution into different lobes and segments of cadaveric lungs. As the technique requires an irreversible injection into lung airspaces, it is not suitable for in vivo purposes. We measured the volume returned from BAL as well as the distribution of BAL injection via dissection. Segmental anatomic orientation was compared to a radiologist's impression of plain film radiographs taken of injected lungs. RESULTS: Mean injected volume distributions were greatest in the upper lobes and lowest in the lower lobes; mean ratios of injected volume distribution to lung lobe volume also followed this trend. Cannulated bronchi orders favored lower branches in the upper lobe and higher branches in the lower lobes. Segmental anatomy varied by the lung lobe injected and was most varied in the lower lobes. CONCLUSION: This novel gelatinized-barium injection technique provides a minimally complex method to yield clinically meaningful feedback on the performance of BAL. The technique is also adaptable to study of procedural parameters in the context of variable lung anatomies and pathologies.

Lung function assessment in children with Long-Covid syndrome.

INTRODUCTION: A significant percentage of patients who survived the Coronavirus Infection Disease 2019 (COVID-19) showed persistent general and respiratory symptoms even months after recovery. This condition, called Post-Acute Sequelae of COVID-19 or Long-Covid syndrome (LCS), has been described also in children with positive history for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Little is known about the pathophysiologic mechanisms underlying this syndrome. The aim of this study was to investigate any difference between children with LCS and asymptomatic peers with previous COVID-19 in terms of lung function and lung ultrasound (LUS) patterns. Secondly, we tested associations between lung function abnormalities and LUS findings with Long-Covid. METHODS: We carried out a prospective, descriptive, observational study including 58 children aged 5-17 years: 28 with LCS compared to 30 asymptomatic children with previous COVID-19. We collected demographic data, history of asthma, allergy or smoke exposure, and acute COVID-19 symptoms. After a median period of 4.5 months (1%-95% range 2-21) since the infection, lung function was assessed by spirometry, body plethysmography, diffusion lung capacity for carbon monoxide (DLCO). Airways inflammation was investigated by fractional exhaled nitric oxide (FeNO). LUS was performed independently by two experienced clinicians. RESULTS: We found that children with LCS were older than controls (mean (SD) 12 (4.1) vs. 9.7 (2.6); p = .04). Children with LCS complained more frequently fatigue (46.4%), cough (17.9%), exercise intolerance (14.3%) and dyspnea (14.3%). Lung function was normal and similar between the two groups. The frequency of LUS abnormalities was similar between the two groups (43.3% children with LCS vs. 56.7% controls; p = .436). Children with LCS showed lower FeNO values (log difference -0.30 (CI 95% -0.50, -0.10)), but no association of LCS with a lower lung function and abnormal LUS findings was found. CONCLUSIONS: LCS seems to be more frequent in older age children. Lung functional and structural abnormalities were not different between children with LCS and asymptomatic subjects with previous COVID-19. In addition, children with LCS showed lower FeNO values than controls, suggesting its potential role as a marker in LCS. However, further and larger studies are needed to confirm our findings.