Systematic review and meta-analysis of the accuracy of lung ultrasound and chest radiography in diagnosing community acquired pneumonia in children.

Chest radiography (CXR) is commonly used for diagnosing childhood pneumonia, but concerns about radiation exposure have raised interest in using radiation-free lung ultrasound (LUS) as an alternative imaging modality. Therefore, we designed this meta-analysis to compare the accuracy of LUS and CXR for diagnosing childhood pneumonia. We searched 8 databases and 1 clinical trial registry for studies published from inception to March 2023. Studies assessing lung ultrasound and chest radiography for diagnosing childhood pneumonia were included. Two reviewers independently screened literature, extracted data, and assessed the risk of bias using the QUADAS-2 tool for each study. Meta-analysis was conducted using a random-effects model, and pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristic (SROC) curve were assessed. Statistical analyses were performed using Meta-Disc 1.4, RevMan 5.4, and Stata 17.0 software. Heterogeneity was examined, and subgroup analysis was conducted to explore the accuracy of lung ultrasound in diagnosing childhood pneumonia. Out of the 4089 screened articles, 30 studies were included, encompassing a total of 4546 children. Of those, 3257 were diagnosed with pneumonia, 3190 through LUS, and 2925 via CXR. The meta-analysis showed that the sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio of LUS were 0.940 (95% CI 0.930-0.949), 0.855 (95% CI 0.835-0.873), 7.561 (95% CI 4.956-11.536), 0.08 (95% CI 0.056-0.113), and 110.77 (95% CI 62.156-197.40), respectively. The combined area under the SROC curve was 0.9712, Q index = 0.9218. For CXR, the sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were 0.893 (95% CI 0.881-0.905), 0.906 (95% CI 0.889-0.921), 18.742 (95% CI 7.551-46.520), 0.105 (95% CI 0.062-0.180), and 237.43 (95% CI 74.080-760.99), respectively. The combined area under the SROC curve was 0.9810, Q index = 0.9391. Subgroup analysis showed that the implementation location, interval between lung ultrasound and chest radiography, and operator experience had no impact on the accuracy of lung ultrasound in diagnosing childhood pneumonia. Existing evidence suggests that lung ultrasound has high accuracy for diagnosing childhood community-acquired pneumonia. Compared with chest radiography, lung ultrasound has higher sensitivity, similar specificity, and advantages such as radiation-free, lower cost, simplicity of operation, and ease of follow-up, making it an important imaging modality for diagnosing childhood pneumonia.

Role of Imaging in Diagnosis and Management of COVID-19: Evidence-Based Approaches.

Imaging has been demonstrated to play a crucial role in both the diagnosis and management of COVID-19. Depending on resources, pre-test probability, and risk factors for severe disease progression, real-time polymerase chain reaction (RT-PCR) testing may be followed by chest radiography (CXR) or chest computed tomography (CT) to further aid in diagnosis or excluding COVID-19 disease. SARS-CoV-2 has been shown not only to pathologically impact the pulmonary system, but also the cardiovascular, gastrointestinal, and neurological systems to name a few. Imaging has again proven useful in further investigating and managing extrapulmonary disease, with the use of echocardiogram, CT angiography of the cardiovascular and cerebrovascular structures, MRI of the brain, as well as ultrasound of the abdomen and CT of the abdomen and pelvis proving particularly useful. Research in artificial intelligence and its application in the diagnosis of COVID-19 and disease severity prediction is underway, and point-of-care ultrasound is an emerging bedside technique that may allow for more efficient and timely diagnosis of COVID-19.

Noise-induced modality-specific pretext learning for pediatric chest X-ray image classification.

Introduction: Deep learning (DL) has significantly advanced medical image classification. However, it often relies on transfer learning (TL) from models pretrained on large, generic non-medical image datasets like ImageNet. Conversely, medical images possess unique visual characteristics that such general models may not adequately capture. Methods: This study examines the effectiveness of modality-specific pretext learning strengthened by image denoising and deblurring in enhancing the classification of pediatric chest X-ray (CXR) images into those exhibiting no findings, i.e., normal lungs, or with cardiopulmonary disease manifestations. Specifically, we use a VGG-16-Sharp-U-Net architecture and leverage its encoder in conjunction with a classification head to distinguish normal from abnormal pediatric CXR findings. We benchmark this performance against the traditional TL approach, viz., the VGG-16 model pretrained only on ImageNet. Measures used for performance evaluation are balanced accuracy, sensitivity, specificity, F-score, Matthew's Correlation Coefficient (MCC), Kappa statistic, and Youden's index. Results: Our findings reveal that models developed from CXR modality-specific pretext encoders substantially outperform the ImageNet-only pretrained model, viz., Baseline, and achieve significantly higher sensitivity (p < 0.05) with marked improvements in balanced accuracy, F-score, MCC, Kappa statistic, and Youden's index. A novel attention-based fuzzy ensemble of the pretext-learned models further improves performance across these metrics (Balanced accuracy: 0.6376; Sensitivity: 0.4991; F-score: 0.5102; MCC: 0.2783; Kappa: 0.2782, and Youden's index:0.2751), compared to Baseline (Balanced accuracy: 0.5654; Sensitivity: 0.1983; F-score: 0.2977; MCC: 0.1998; Kappa: 0.1599, and Youden's index:0.1327). Discussion: The superior results of CXR modality-specific pretext learning and their ensemble underscore its potential as a viable alternative to conventional ImageNet pretraining for medical image classification. Results from this study promote further exploration of medical modality-specific TL techniques in the development of DL models for various medical imaging applications.

Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage.

OBJECTIVES: Computer-aided detection (CAD) software packages quantify tuberculosis (TB)-compatible chest X-ray (CXR) abnormality as continuous scores. In practice, a threshold value is selected for binary CXR classification. We assessed the diagnostic accuracy of an alternative approach to applying CAD for TB triage: incorporating CAD scores in multivariable modeling. METHODS: We pooled individual patient data from four studies. Separately, for two commercial CAD, we used logistic regression to model microbiologically confirmed TB. Models included CAD score, study site, age, sex, human immunodeficiency virus status, and prior TB. We compared specificity at target sensitivities ≥90% between the multivariable model and the current threshold-based approach for CAD use. RESULTS: We included 4,733/5,640 (84%) participants with complete covariate data (median age 36 years; 45% female; 22% with prior TB; 22% people living with human immunodeficiency virus). A total of 805 (17%) had TB. Multivariable models demonstrated excellent performance (areas under the receiver operating characteristic curve [95% confidence interval]: software A, 0.91 [0.90-0.93]; software B, 0.92 [0.91-0.93]). Compared with threshold scores, multivariable models increased specificity (e.g., at 90% sensitivity, threshold vs model specificity [95% confidence interval]: software A, 71% [68-74%] vs 75% [74-77%]; software B, 69% [63-75%] vs 75% [74-77%]). CONCLUSION: Using CAD scores in multivariable models outperformed the current practice of CAD-threshold-based CXR classification for TB diagnosis.

Screening Patient Misidentification Errors Using a Deep Learning Model of Chest Radiography: A Seven Reader Study.

We aimed to evaluate the ability of deep learning (DL) models to identify patients from a paired chest radiograph (CXR) and compare their performance with that of human experts. In this retrospective study, patient identification DL models were developed using 240,004 CXRs. The models were validated using multiple datasets, namely, internal validation, CheXpert, and Chest ImaGenome (CIG), which include different populations. Model performance was analyzed in terms of disease change status. The performance of the models to identify patients from paired CXRs was compared with three junior radiology residents (group I), two senior radiology residents (group II), and two board-certified expert radiologists (group III). For the reader study, 240 patients (age, 56.617 ± 13.690 years, 113 females, 160 same pairs) were evaluated. A one-sided non-inferiority test was performed with a one-sided margin of 0.05. SimChest, our similarity-based DL model, demonstrated the best patient identification performance across multiple datasets, regardless of disease change status (internal validation [area under the receiver operating characteristic curve range: 0.992-0.999], CheXpert [0.933-0.948], and CIG [0.949-0.951]). The radiologists identified patients from the paired CXRs with a mean accuracy of 0.900 (95% confidence interval: 0.852-0.948), with performance increasing with experience (mean accuracy:group I [0.874], group II [0.904], group III [0.935], and SimChest [0.904]). SimChest achieved non-inferior performance compared to the radiologists (P for non-inferiority: 0.015). The findings of this diagnostic study indicate that DL models can screen for patient misidentification using a pair of CXRs non-inferiorly to human experts.

Use of reporting templates for chest radiographs in a coronavirus disease 2019 context: measuring concordance of radiologists with three international templates.

Purpose: Reporting templates for chest radiographs (CXRs) for patients presenting or being clinically managed for severe acute respiratory syndrome coronavirus 2 [coronavirus disease 2019 (COVID-19)] has attracted advocacy from international radiology societies. We aim to explore the effectiveness and useability of three international templates through the concordance of, and between, radiologists reporting on the presence and severity of COVID-19 on CXRs. Approach: Seventy CXRs were obtained from a referral hospital, 50 from patients with COVID-19 (30 rated "classic" COVID-19 appearance and 20 "indeterminate") and 10 "normal" and 10 "alternative pathology" CXRs. The recruited radiologists were assigned to three test sets with the same CXRs but with different template orders. Each radiologist read their test set three times and assigned a classification to the CXR using the Royal Australian New Zealand College of Radiology (RANZCR), British Society of Thoracic Imaging (BSTI), and Modified COVID-19 Reporting and Data System (Dutch; mCO-RADS) templates. Inter-reader variability and intra-reader variability were measured using Fleiss' kappa coefficient. Results: Twelve Australian radiologists participated. The BSTI template had the highest inter-reader agreement (0.46; "moderate" agreement), followed by RANZCR (0.45) and mCO-RADS (0.32). Concordance was driven by strong agreement in "normal" and "alternative" classifications and was lowest for "indeterminate." General consistency was observed across classifications and templates, with intra-reader variability ranging from "good" to "very good" for COVID-19 CXRs (0.61), "normal" CXRs (0.76), and "alternative" (0.68). Conclusions: Reporting templates may be useful in reducing variation among radiology reports, with intra-reader variability showing promise. Feasibility and implementation require a wider approach including referring and treating doctors plus the development of training packages for radiologists specific to the template being used.

Chest X-ray Findings and Prognostic Factors in Survival Analysis in Peritoneal Dialysis and Hemodialysis Patients: A Retrospective Cross-Sectional Study.

Background and Objectives: This study aims to analyze survival in peritoneal and hemodialysis patients using chest radiography and biochemical parameters, determine common dialysis etiologies and causes of death, reveal prognostic factors, and contribute to clinical practice. Materials and Methods: A retrospective cross-sectional study was conducted with data from 33 peritoneal dialysis and 37 hemodialysis patients collected between October 2018 and February 2020. Survival and mortality were retrospectively tracked over 70 months (October 2018-June 2024). Chest X-ray measurements (cardiothoracic index, pulmonary vascular pedicle width, right pulmonary artery diameter, diaphragmatic height) and biochemical parameters (urea, albumin, creatinine, parathormone, ferritin, hemoglobin, arterial blood gas, potassium) were analyzed for their impact on survival. Statistical analyses included descriptive statistics, chi-square test, Fisher's exact test, Bayesian analysis, McNemar test, Kaplan-Meier survival analysis, Cox regression, Bayesian correlation test, linear regression analysis (scatter plot), and ROC analysis. SPSS 20.0 was used for data analysis, with p < 0.05 considered statistically significant. Results: Hypertension, type 2 diabetes, and urogenital disorders were the main dialysis etiologies. Peritonitis (38.5%) and cardiovascular diseases (47.4%) were the leading causes of death in peritoneal and hemodialysis patients, respectively. Significant chest X-ray differences included pulmonary vascular pedicle width and pulmonary artery diameter in hemodialysis and diaphragm height in peritoneal dialysis. Kaplan-Meier showed no survival difference between methods. Cox regression identified age, intact parathormone levels, iPTH/PVPW ratio, and clinical status as survival and mortality factors. The iPTH/PVPW ratio cut-off for mortality prediction was ≤6.8. Conclusions: Age, intact parathormone levels, pulmonary vascular pedicle width, and clinical status significantly impact survival in dialysis patients. Management of hypertension and diabetes, management and follow-up of urogenital disorders, infection control, patient education, and regular cardiovascular check-ups may improve survival rates. Additionally, the iPTH/PVPW ratio can predict mortality risk.

Investigation of diaphragmatic motion and projected lung area in diaphragm paralysis patients using dynamic chest radiography.

Background: Dynamic chest radiography (DCR) is a novel and supplementary examination in respiratory diseases. The investigation of other chest diseases using DCR has been explored, identifying a certain correlation of the pulmonary function test (PFT). However, there is a lack of research using DCR parameters to quantitatively evaluate chest disease. The purpose of this study was to investigate the diagnostic value of DCR for diaphragm paralysis (DP). Methods: This retrospective study recruited 118 participants, which include 18 patients with DP, 48 healthy volunteers, and 52 patients with respiratory disease. Comparison of DCR parameters relationships among 3 groups was performed using one-way analysis of variance (ANOVA) and Kruskal-Wallis test. The receiver operating characteristic (ROC) curve was used to compare the value of the DCR parameters to diagnose DP. Results: The differences of excursion of diaphragm (ED) in normal (nb) and forced breathing (fb), ED(fb)-ED(nb), and the parameters of projected lung area (PLA) in inspiratory (ins) and expiratory phase (exp), PLA.exp(fb), PLA.ins(fb)-PLA.ins(nb), and PLA.exp(fb)-PLA.exp(nb) among the 3 groups were statistically significant. The highest area under the curve (AUC) of right-side parameter was the ED(fb)-ED(nb), for which the AUC was 0.8950 [95% confidence interval (CI): 0.7618-1.000], whereas that of the left-side parameter was ED(fb), for which the AUC was 0.9176 [95% confidence interval (CI): 0.8524-0.9829]. Conclusions: The parameters of DCR have good diagnostic value for DP. The highest diagnostic efficiency for DP on the right side is the ED(fb)-ED(nb), with a sensitivity of 95% and a specificity of 78.6%, whereas on the left side is ED(fb), with a sensitivity of 80% and a specificity of 88.2%.

Visual analysis of pulmonary blood flow in pulmonary circulation assessment: differences between two variant algorithms for processing dynamic images.

Background: In the quantitative assessment of pulmonary blood flow, two different processing algorithms [cross-correlation calculation processing (CCC-pro) and reference frame subtraction processing (RFS-pro)] within dynamic imaging systems have been reported to exhibit high correlations with conventional measurement methods. However, reports still need to evaluate these two processing algorithms regarding the different aspects of pulmonary blood flow. This study aimed to analyze the differences in pulmonary circulation. Methods: We conducted a cross-sectional study to evaluate patients with lung cancer who underwent radical surgery, simultaneous dynamic chest radiography (DCR), and pulmonary perfusion scintigraphy (PPS). We assessed the correlation between PPS and two algorithms (CCC-pro and RFS-pro) regarding calculated blood flow ratio (BFR) using Pearson's correlation and linear regression analysis. Additionally, we evaluated consistency using the Bland-Altman analysis. We compared the pulmonary blood flow distributions across six-division lung fields and evaluated each method's blood flow images and histograms of pixel values. Results: From May 2018 to December 2020, we consecutively enrolled 46 patients with lung cancer who met the inclusion criteria (40 male patients, with a mean age of 72.91 years). In these patients, CCC-pro and RFS-pro were correlated (R=0.718, P<0.01); however, CCC-pro was more strongly correlated with PPS than RFS-pro (R=0.859, P<0.01 vs. R=0.549, P<0.01). The Bland-Altman analysis showed high agreement, although systematic errors were observed in relationships other than RFS-pro to PPS. CCC-pro and RFS-pro showed similar blood flow distributions in the upper and lower lung fields, with RFS-pro being dominant in the middle. RFS-pro showed higher pixel values in the hilar region and a histogram shape similar to PPS; however, posture affected the right upper lung field gradient. RFS-pro showed no difference in the BFR when the pulmonary artery region was symmetric; however, potential inaccuracies existed when it overlapped with the cardiovascular shadow. Conclusions: The CCC-pro algorithm was useful for quantifying BFRs, whereas the RFS-pro algorithm accurately evaluated blood flow distribution in lung fields. Further algorithm development is required to enable versatile pulmonary blood flow analysis.

Automated Quality Control Solution for Radiographic Imaging of Lung Diseases.

Background/Objectives: Radiography is an essential and low-cost diagnostic method in pulmonary medicine that is used for the early detection and monitoring of lung diseases. An adequate and consistent image quality (IQ) is crucial to ensure accurate diagnosis and effective patient management. This pilot study evaluates the feasibility and effectiveness of the International Atomic Energy Agency (IAEA)'s remote and automated quality control (QC) methodology, which has been tested in multiple imaging centers. Methods: The data, collected between April and December 2022, included 47 longitudinal data sets from 22 digital radiographic units. Participants submitted metadata on the radiography setup, exposure parameters, and imaging modes. The database comprised 968 exposures, each representing multiple image quality parameters and metadata of image acquisition parameters. Python scripts were developed to collate, analyze, and visualize image quality data. Results: The pilot survey identified several critical issues affecting the future implementation of the IAEA method, as follows: (1) difficulty in accessing raw images due to manufacturer restrictions, (2) variability in IQ parameters even among identical X-ray systems and image acquisitions, (3) inconsistencies in phantom construction affecting IQ values, (4) vendor-dependent DICOM tag reporting, and (5) large variability in SNR values compared to other IQ metrics, making SNR less reliable for image quality assessment. Conclusions: Cross-comparisons among radiography systems must be taken with cautious because of the dependence on phantom construction and acquisition mode variations. Awareness of these factors will generate reliable and standardized quality control programs, which are crucial for accurate and fair evaluations, especially in high-frequency chest imaging.

Association between the cardiothoracic ratio on chest X-rays and the respiratory function in patients with interstitial lung diseases: A cross-sectional study.

Objective Patients with advanced interstitial lung disease (ILD) struggle to undergo spirometry to evaluate the respiratory function. The cardiothoracic ratio (CTR) on chest radiography can potentially reflect the lung volume; however, this has not yet been fully established. This study aimed to clarify the relationship between the CTR and the respiratory function in patients with interstitial lung diseases. Patients and Methods We reviewed 120 consecutive patients with idiopathic interstitial lung disease who were admitted to our department between April 2018 and March 2023 and who underwent chest radiography, spirometry, and echocardiography. A multiple linear regression analysis was used to identify the factors associated with the CTR. Correlations between the CTR and the respiratory or cardiac function were assessed using Pearson's correlation coefficient. Results A multiple linear regression analysis showed the percent vital capacity (ß = -0.598, p <0.001), age (ß = 0.405, p <0.001), and female sex (ß = 0.177, p = 0.047) to be independently associated with the CTR, whereas no relationship was observed between the left ventricular ejection fraction, body mass index, and smoking habits. The CTR was significantly negatively correlated with the vital capacity (r = -0.490, p <0.001). Conclusions An increased CTR might reflect a decreased vital capacity, but not a decreased cardiac function, in patients with interstitial lung diseases. Measuring the CTR can thus be beneficial for predicting progression in patients with ILD.

Next-generation digital chest tomosynthesis.

The objective of this study was to demonstrate the performance characteristics and potential utility of a novel tomosynthesis device as applied to imaging the chest, specifically relating to lung nodules. The imaging characteristics and quality of a novel digital tomosynthesis prototype system was assessed by scanning, a healthy volunteer, and an andromorphic lung phantom with different configurations of simulated pulmonary nodules. The adequacy of nodule detection on the phantoms was rated by chest radiologists using a standardized scale. Results from using this tomosynthesis device demonstrate in plane resolution of 16lp/cm, with estimated effective radiation doses of 90% less than low dose CT. Nodule detection was adequate across various anatomic locations on a phantom. These proof-of-concept tests showed this novel tomosynthesis device can detect lung nodules with low radiation dose to the patient. This technique has potential as an alternative to low dose chest CT for lung nodule screening and tracking.

Survey on Findings and Utilization of Preoperative Chest Radiography in Ophthalmic Surgery.

Objective: The objective of this paper is to reconsider the significance of preoperative chest radiography (CXR) before ophthalmic surgery through investigation of imaging findings and usage status. Methods: This retrospective observational clinical study involved 1616 patients who underwent ophthalmic surgery at Saga University Hospital from 1 January 2019 to 31 December 2020. The patients' radiology reports were obtained from the electronic medical records, and their CXR findings, therapeutic interventions, and progress were investigated. Results: Among all patients, 539 (33.4%) had abnormal preoperative CXR findings. Of these patients, 74 (4.6%) had newly identified abnormal findings. In both patient groups, approximately 70% of patients with abnormal findings were aged ≥70 years, and interstitial shadows were the most common finding. Among all patients with abnormal findings, three (0.19%) received preoperative therapeutic interventions, and all surgeries were performed safely. Forty-three patients with abnormal findings were referred to our hospital or other hospitals for further investigation and treatment postoperatively. Among those patients, eight (0.5%) had primary lung cancer, seven underwent surgery, and one received chemoradiation. The other patients were also followed up and received appropriate therapeutic interventions. Conclusions: Before ophthalmic surgery, few patients required actual therapeutic interventions based on their CXR results. However, many abnormal findings were revealed in elderly patients, including some serious diseases. Furthermore, research has suggested that appropriate therapeutic intervention after ophthalmologic surgery may reduce the risk of a poor life prognosis. This study clearly shows that preoperative CXR is not only useful for perioperative systemic management but also ultimately benefits patients. It is also considered particularly meaningful for patients aged ≥70 years.

Utility of chest x-ray for tracheostomy tube placement in pediatric patients.

Objective: To evaluate the utility of ordering chest x-rays after pediatric tracheostomy tube placement in identifying acute, post-operative complications and how it impacts clinical decision-making. Methods: In this retrospective cohort study, we identified tracheostomies performed in 139 pediatric patients through CPT codes over a 5-year period from 2013 to 2018. Manual chart review was performed for demographic and clinical characteristics, pre-procedure and post-procedure chest x-ray interpretations, and the presence of complications. Each complication was reviewed to see if action was taken due to post-procedure chest x-ray findings. Multivariable logistic regression was performed to determine associations with changes in pre-procedure versus post-procedure chest x-rays. Results: In a cohort of 139 pediatric patients with pre-procedure and post-procedure chest x-rays, 40 (28.8%) of patients had new significant post-procedure chest x-ray findings compared to pre-procedure chest x-ray findings. Of these 40 instances of changes in pre-procedure versus post-procedure chest x-ray findings, only eight resulted in action being taken due to the observed findings. Among these eight instances of action being taken, only one instance involved in invasive action being taken with a bronchoscopy. With multivariable regression analysis, patient age, race, gender, and the presences of genetic syndromes, were not found to be significant risk factors in predicting changes in pre-procedure versus post-procedure chest x-ray. Conclusion: In our study, post-procedure chest x-ray after tracheostomy tube placement did not significantly impact clinical decision making. It may be worth reconsidering the value in routine chest x-rays after tracheostomy tube placement in pediatric patients.

Role of expiratory chest X-ray in pediatric foreign body aspiration.

PURPOSE: Tracheobronchial foreign body aspiration is a common pediatric emergency and a leading cause of accidental deaths in children. The diagnosis remains sometimes difficult even with physical examination, medical history, and basic X-rays. This challenge necessitates the performance of endoscopy under general anesthesia, regardless of the potential for serious complications. The benefit of strategies like expiratory chest X-rays to reduce unnecessary endoscopies remains uncertain. We evaluated the effectiveness of expiratory chest X-rays in detecting airway foreign bodies to potentially reduce the need for endoscopies. METHODS: We retrospectively studied children with suspected foreign body aspiration who had X-ray and endoscopy. RESULTS: A total of 70 children were included in the study. Out of these, 19 cases (27.1 %) showed pathological findings on standard chest X-rays. However, when expiratory chest X-rays were added, the number of pathological radiographies increased to 37 cases (52.9 %). Out of the 36 foreign bodies that were present, only 2 were not detected. Furthermore, 3 chest X-rays displayed pathological results, while the endoscopies indicated normal findings. Consequently, the overall sensitivity, specificity, positive predictive value, and negative predictive value stood at 94.4 %, 91.1 %, 91.9 %, and 93.9 % respectively. CONCLUSION: The remarkable sensitivity of expiratory chest radiography can eliminate the need for unnecessary endoscopy, but it should be limited to centers lacking access to MDCT. The performance of endoscopy should only be considered when persistent clinical symptoms are observed during auscultation.

Estimation of threshold thickness of residual normal tissue in lung dysfunction detectable by dynamic chest radiography: A virtual imaging trial.

BACKGROUND: Dynamic chest radiography (DCR) is a recently developed functional x-ray imaging technique that detects pulmonary ventilation impairment as a decrease in changes in lung density during respiration. However, the diagnostic performance of DCR is uncertain owing to an insufficient number of clinical cases. One solution is virtual imaging trials (VITs), which is an emerging alternative method for efficiently evaluating medical imaging technology via computer simulation techniques. PURPOSE: This study aimed to estimate the typical threshold thickness of residual normal tissue below which the presence of emphysema may be detected by DCR via VITs using virtual patients with different physiques and a user-defined ground truth. METHODS: Twenty extended cardiac-torso (XCAT) phantoms that exhibited changes in lung density during respiration were generated to simulate virtual patients. To simulate a locally collapsed lung, an air sphere was inserted into each lung regions in the phantom. The XCAT phantom was virtually projected using an x-ray simulator. The respiratory changes in pixel value (ΔPV) were measured on the projected air spheres (simulated lesions) to calculate the percentage of decrease (ΔPV%) relative to ΔPVexp-ins in the absence of an air sphere. The relationship between the amount of residual normal tissue and ΔPV% was fitted to a cubic approximation curve (hereafter, performance curve), and the threshold at which the ΔPV% began to decrease (normal-tissuethre) was determined. The goodness of fit for each performance curve was evaluated according to the coefficient of determination (R2) and the 95% confidence interval derived from the standard errors between the measured and theoretical values corresponding to each performance curve. The ΔPV% was also visualized as a color scaling to validate the results of the VITs in both virtual and clinical patients. RESULTS: For each lung region in all body sizes, the ΔPV% decreased as the amount of residual normal tissue decreased and could be defined as a function of the amount of residual normal tissue in front of and behind the simulated lesions with high R2 values. Meanwhile, the difference between the measured and theoretical values corresponding to each performance curve was only partially included in the 95% confidence interval. The normal-tissuethre values were 146.0, 179.5, and 170.9 mm for the upper, middle, and lower lungs, respectively, which were demonstrated in virtual patients and one real patient, where the value of the residual normal tissue was less than that of normal-tissuethre; any reduction in the residual normal tissue was reflected as a reduced ΔPV and depicted as a reduced color intensity. CONCLUSIONS: The performance of DCR-based pulmonary impairment assessment depends on the amount of residual normal tissue in front of and behind the lesion rather than on the lesion size. The performance curve can be defined as a function of the amount of residual normal tissue in each lung region with a specific threshold of normal tissue remaining where lesions become detectable, shown as a decrease in ΔPV. The results of VITs are expected to accelerate future clinical trials for DCR-based pulmonary function assessment.

Understanding the Added Value of High-Resolution CT Beyond Chest X-ray in Determining Extent of Physiologic Impairment.

BACKGROUND: Sarcoidosis staging primarily has relied on the Scadding chest radiographic system, although chest CT imaging is finding increased clinical use. RESEARCH QUESTION: Whether standardized chest CT scan assessment provides additional understanding of lung function beyond Scadding stage and demographics is unknown and the focus of this study. STUDY DESIGN AND METHODS: We used National Heart, Lung, and Blood Institute study Genomics Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) cases of sarcoidosis (n = 351) with Scadding stage and chest CT scans obtained in a standardized manner. One chest radiologist scored all CT scans with a visual scoring system, with a subset read by another chest radiologist. We compared demographic features, Scadding stage and CT scan findings, and the correlation between these measures. Associations between spirometry and diffusing capacity of the lungs for carbon monoxide (Dlco) results and CT scan findings and Scadding stage were determined using regression analysis (n = 318). Agreement between readers was evaluated using Cohen's κ value. RESULTS: CT scan features were inconsistent with Scadding stage in approximately 40% of cases. Most CT scan features assessed on visual scoring were associated negatively with lung function. Associations persisted for FEV1 and Dlco when adjusting for Scadding stage, although some CT scan feature associations with FVC became insignificant. Scadding stage was associated primarily with FEV1, and inclusion of CT scan features reduced significance in association between Scadding stage and lung function. Multivariable regression modeling to identify radiologic measures explaining lung function included Scadding stage for FEV1 and FEV1 to FVC ratio (P < .05) and marginally for Dlco (P < .15). Combinations of CT scan measures accounted for Scadding stage for FVC. Correlations among Scadding stage and CT scan features were noted. Agreement between readers was poor to moderate for presence or absence of CT scan features and poor for degree and location of abnormality. INTERPRETATION: In this study, CT scan features explained additional variability in lung function beyond Scadding stage, with some CT scan features obviating the associations between lung function and Scadding stage. Whether CT scan features, phenotypes, or endotypes could be useful for treating patients with sarcoidosis needs more study.

Chest Radiograph Screening for Detecting Subclinical Tuberculosis in Asymptomatic Household Contacts, Peru.

The World Health Organization's end TB strategy promotes the use of symptom and chest radiograph screening for tuberculosis (TB) disease. However, asymptomatic early states of TB beyond latent TB infection and active disease can go unrecognized using current screening criteria. We conducted a longitudinal cohort study enrolling household contacts initially free of TB disease and followed them for the occurrence of incident TB over 1 year. Among 1,747 screened contacts, 27 (52%) of the 52 persons in whom TB subsequently developed during follow-up had a baseline abnormal radiograph. Of contacts without TB symptoms, persons with an abnormal radiograph were at higher risk for subsequent TB than persons with an unremarkable radiograph (adjusted hazard ratio 15.62 [95% CI 7.74-31.54]). In young adults, we found a strong linear relationship between radiograph severity and time to TB diagnosis. Our findings suggest chest radiograph screening can extend to detecting early TB states, thereby enabling timely intervention.

A mediastinum-tumour-like pulmonary arteriovenous malformation with association to the pulmonary artery treated with surgical resection.

Despite embolization being now considered the preferred treatment for PAVM, surgical intervention may be considered if the malformation involves large vessels.

Thoracic Ultrasound Utility in Pulmonary Pathologies Following Blunt Chest Trauma: A Cross-Sectional Study From Barcelona, Venezuela.

Background The thoracic ultrasound (TUS) is a monitoring tool that has gained worldwide popularity in various scenarios, offering the opportunity for dynamic, bedside evaluations. Recent studies indicate that the use of TUS enables the diagnosis of pathologies resulting from blunt chest trauma (BCT), yielding favorable outcomes. This study aimed to compare the utility of TUS versus chest radiography (CXR) in diagnosing pulmonary pathologies resulting from closed-chest traumas. Methodology A prospective cross-sectional study was conducted with a sample of 58 patients diagnosed with BCT who sought emergency care at the "Dr. Luis Razetti" University Hospital in Barcelona, Venezuela, from November 2023 to January 2024. Results Of the patients, 75.9% (n = 44) were male, with an average age of 37.8 years (standard deviation = 18.4 years). Injuries were reported in 8.6% (n = 5) of the patients, including 60% (n = 3) pneumothorax and 40% (n = 2) hemothorax. Ultrasound results coincided with CXR in 94.8% (n = 55) of the cases, with a Cohen's kappa coefficient of 0.9 (95% confidence interval (CI) = 0.642-1.0). TUS demonstrated higher sensitivity than CXR (100% vs. 60%) for detecting hemothorax and pneumothorax in patients with BCT, with an area under the receiver operating characteristic curve of 0.991 (95% CI = 0.968-1.013). Conclusions BCT predominantly occurred in young males, resulting primarily in pneumothorax and hemothorax lesions, detectable with higher sensitivity through TUS compared to CXR. The use of TUS should be considered an essential component of the initial assessment for individuals with BCT.