Longitudinal long term follow up investigation on the carcinogenic impact of polyhexamethylene guanidine phosphate in rat models.

Polyhexamethylene guanidine phosphate (PHMG-p) is a major component in humidifier disinfectants, which cause life-threatening lung injuries. However, to our knowledge, no published studies have investigated associations between PHMG-p dose and lung damage severity with long-term follow-up. Therefore, we evaluated longitudinal dose-dependent changes in lung injuries using repeated chest computed tomography (CT). Rats were exposed to low (0.2 mg/kg, n = 10), intermediate (1.0 mg/kg, n = 10), and high (5.0 mg/kg, n = 10) doses of PHMG-p. All rats underwent repeated CT scans after 10 and 40 weeks following the first exposure. All CT images were quantitatively analyzed using commercial software. Inflammation/fibrosis and tumor counts underwent histopathological evaluation. In both radiological and histopathologic results, the lung damage severity increased as the PHMG-p dose increased. Moreover, the number, size, and malignancy of the lung tumors increased as the dose increased. Bronchiolar-alveolar hyperplasia developed in all groups. During follow-up, there was intergroup variation in bronchiolar-alveolar hyperplasia progression, although bronchiolar-alveolar adenomas or carcinomas usually increase in size over time. Thirty-three carcinomas were detected in the high-dose group in two rats. Overall, lung damage from PHMG-p and the number and malignancy of lung tumors were shown to be dose-dependent in a rat model using repeated chest CT scans during a long-term follow-up.

Time-Sequential Monitoring of the Early Mesothelial Reaction in the Pleura after Cryoinjury.

(1) Background: An early mesothelial reaction of the pleura, leading to fibrosis, has been reported in animals after chemical or heavy metal exposure. However, the visual monitoring of early time-sequential mesothelial reaction-associated cryoinjury has not been fully investigated. Therefore, this study aimed to evaluate and visualize the early mesothelial reactions seen following cryoinjury using rabbit pleura. (2) Methods: We monitored the early mesothelial reaction in rabbit pleurae after cryoinjury using optical coherence tomography (OCT), in real-time, which was then compared with pathological images. Due to the penetration limit of OCT, we made a thoracic window to image the parietal and visceral pleurae in vivo. We also used an innovative technique for capturing the microstructure in vivo, employing a computer-controlled intermittent iso-pressure breath hold to reduce respiratory motion, increasing the resolution of OCT. We organized three sample groups: the normal group, the sham group with just a thoracic window, and the experimental group with a thoracic window and cryotherapy. In the experimental group, localized cryoinjury was performed. The mesothelial cells at the level of pleura of the cryotherapy-injured site were visualized by OCT within the first 30 min and then again after 2 days at the same site. (3) Results: In the experimental group, focal thickening of the parietal pleura was observed at the site of cryoinjury using OCT after the first injury, and it was then confirmed pathologically as focal mesothelial cell proliferation. Two days after cryoinjury, diffuse mesothelial cell proliferation in the parietal pleura was noted on the reverse side around the cryoinjured site in the same rabbit. In the sham group, no pleural reaction was found. The OCT and pathological examinations revealed different patterns of mesothelial cell reactions between the parietal and visceral pleurae: the focal proliferation of mesothelial cells was found in the parietal pleura, while only a morphological change from flat cells to cuboidal cells and a thickened monolayer without proliferation of mesothelial cells were found in the visceral pleural. (4) Conclusions: An early mesothelial reaction occurs following cryoinjury to the parietal and visceral pleurae.

Computed tomography-based imaging biomarker identifies coal workers' pneumoconiosis.

Rationale: The increase in the incidence and the diagnostic limitations of pneumoconiosis have emerged as a public health concern. This study aimed to conduct a computed tomography (CT)- based quantitative analysis to understand differences in imaging results of pneumoconiosis according to disease severity. Methods: According to the International Labor Organization (ILO) guidelines, coal workers' pneumoconiosis (CWP) are classified into five categories. CT images were obtained only at full inspiration and were quantitatively evaluated for airway structural variables such as bifurcation angle (θ), hydraulic diameter (Dh), wall thickness (WT), and circularity (Cr). Parenchymal functional variables include abnormal regions (emphysema, ground-glass opacities, consolidation, semi consolidation, and fibrosis) and blood vessel volume. Through the propensity score matching method, the confounding effects were decreased. Results: Category 4 demonstrated a reduced θ in TriLUL, a thicker airway wall in both the Trachea and Bronint compared to Category 0, and a decreased Cr in Bronint. Category 4 presented with higher abnormal regions except for ground-glass opacity and a narrower pulmonary blood vessel volume. A negative correlation was found between abnormal areas with lower Hounsfield units (HU) than the normal lung and the ratio of forced expiratory volume in 1 s/forced vital capacity, with narrowed pulmonary blood vessel volume which is positively correlated with abnormal areas with upper HU than the normal lung. Conclusion: This study provided valuable insight into pneumoconiosis progression through a comparison of quantitative CT images based on severity. Furthermore, as there has been paucity of studies on the pulmonary blood vessel volume of the CWP, in this study, a correlation between reduced pulmonary blood vessel volume and regions with low HU values holds significant importance.

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with HDLI but still felt discomfort, possibly due to the unknown effects of HD. Therefore, this study examined HD-exposed subjects with normal-appearing lungs, as well as unexposed subjects, in clusters (subgroups) with distinct characteristics, classified by deep-learning-derived computed-tomography (CT)-based tissue pattern latent traits. Among the major clusters, cluster 0 (C0) and cluster 5 (C5) were dominated by HD-exposed and unexposed subjects, respectively. C0 was characterized by features attributable to lung inflammation or fibrosis in contrast with C5. The computational fluid and particle dynamics (CFPD) analysis suggested that the smaller airway sizes observed in the C0 subjects led to greater airway resistance and particle deposition in the airways. Accordingly, women appeared more vulnerable to HD-associated lung abnormalities than men.

Structural and functional alterations of subjects with cement dust exposure: A longitudinal quantitative computed tomography-based study.

Cement dust exposure (CDE) can be a risk factor for pulmonary disease, causing changes in segmental airways and parenchymal lungs. This study investigates longitudinal alterations in quantitative computed tomography (CT)-based metrics due to CDE. We obtained CT-based airway structural and lung functional metrics from CDE subjects with baseline CT and follow-up CT scans performed three years later. From the CT, we extracted wall thickness (WT) and bifurcation angle (θ) at total lung capacity (TLC) and functional residual capacity (FRC), respectively. We also computed air volume (Vair), tissue volume (Vtissue), global lung shape, percentage of emphysema (Emph%), and more. Clinical measures were used to associate with CT-based metrics. Three years after their baseline, the pulmonary function tests of CDE subjects were similar or improved, but there were significant alterations in the CT-based structural and functional metrics. The follow-up CT scans showed changes in θ at most of the central airways; increased WT at the subgroup bronchi; smaller Vair at TLC at all except the right upper and lower lobes; smaller Vtissue at all lobes in TLC and FRC except for the upper lobes in FRC; smaller global lung shape; and greater Emph% at the right upper and lower lobes. CT-based structural and functional variables are more sensitive to the early identification of CDE subjects, while most clinical lung function changes were not noticeable. We speculate that the significant long-term changes in CT are uniquely observed in CDE subjects, different from smoking-induced structural changes.

Pulmonary fibrosis model using micro-CT analyzable human PSC-derived alveolar organoids containing alveolar macrophage-like cells.

Human lung organoids (hLOs) are useful for disease modelling and drug screening. However, a lack of immune cells in hLOs limits the recapitulation of in vivo cellular physiology. Here, we generated hLOs containing alveolar macrophage (AMφ)-like cells derived from pluripotent stem cells (PSC). To bridge hLOs with advanced human lung high-resolution X-ray computed tomography (CT), we acquired quantitative micro-CT images. Three hLO types were observed during differentiation. Among them, alveolar hLOs highly expressed not only lung epithelial cell markers but also AMφ-specific markers. Furthermore, CD68+ AMφ-like cells were spatially organized on the luminal epithelial surface of alveolar hLOs. Bleomycin-treated alveolar hLOs showed upregulated expression of fibrosis-related markers and extracellular matrix deposits in the alveolar sacs. Alveolar hLOs also showed structural alterations such as excessive tissue fraction under bleomycin treatment. Therefore, we suggest that micro-CT analyzable PSC-derived alveolar hLOs are a promising in vitro model to predict lung toxicity manifestations, including fibrosis.

Analysis of lung cancer-related genetic changes in long-term and low-dose polyhexamethylene guanidine phosphate (PHMG-p) treated human pulmonary alveolar epithelial cells.

BACKGROUND: Lung injury elicited by respiratory exposure to humidifier disinfectants (HDs) is known as HD-associated lung injury (HDLI). Current elucidation of the molecular mechanisms related to HDLI is mostly restricted to fibrotic and inflammatory lung diseases. In our previous report, we found that lung tumors were caused by intratracheal instillation of polyhexamethylene guanidine phosphate (PHMG-p) in a rat model. However, the lung cancer-related genetic changes concomitant with the development of these lung tumors have not yet been fully defined. We aimed to discover the effect of long-term exposure of PHMG-p on normal human lung alveolar cells. METHODS: We investigated whether PHMG-p could increase distorted homeostasis of oncogenes and tumor-suppressor genes, with long-term and low-dose treatment, in human pulmonary alveolar epithelial cells (HPAEpiCs). Total RNA sequencing was performed with cells continuously treated with PHMG-p and harvested after 35 days. RESULTS: After PHMG-p treatment, genes with transcriptional expression changes of more than 2.0-fold or less than 0.5-fold were identified. Within 10 days of exposure, 2 protein-coding and 5 non-coding genes were selected, whereas in the group treated for 27-35 days, 24 protein-coding and 5 non-coding genes were identified. Furthermore, in the long-term treatment group, 11 of the 15 upregulated genes and 9 of the 14 downregulated genes were reported as oncogenes and tumor suppressor genes in lung cancer, respectively. We also found that 10 genes of the selected 24 protein-coding genes were clinically significant in lung adenocarcinoma patients. CONCLUSIONS: Our findings demonstrate that long-term exposure of human pulmonary normal alveolar cells to low-dose PHMG-p caused genetic changes, mainly in lung cancer-associated genes, in a time-dependent manner.

Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique.

BACKGROUND AND OBJECTIVE: Cement dust exposure is likely to affect the structural and functional alterations in segmental airways and parenchymal lungs. This study develops an artificial neural network (ANN) model for identifying cement dust-exposed (CDE) subjects using quantitative computed tomography-based airway structural and functional features. METHODS: We obtained the airway features in five central and five sub-grouped segmental regions and the lung features in five lobar regions and one total lung region from 311 CDE and 298 non-CDE (NCDE) subjects. The five-fold cross-validation method was adopted to train the following classification models:ANN, support vector machine (SVM), logistic regression (LR), and decision tree (DT). For all the classification models, linear discriminant analysis (LDA) and genetic algorithm (GA) were applied for dimensional reduction and hyperparameterization, respectively. The ANN model without LDA was also optimized by the GA method to observe the effect of the dimensional reduction. RESULTS: The genetically optimized ANN model without the LDA method was the best in terms of the classification accuracy. The accuracy, sensitivity, and specificity of the GA-ANN model with four layers were greater than those of the other classification models (i.e., ANN, SVM, LR, and DT using LDA and GA methods) in the five-fold cross-validation. The average values of accuracy, sensitivity, and specificity for the five-fold cross-validation were 97.0%, 98.7%, and 98.6%, respectively. CONCLUSIONS: We demonstrated herein that a quantitative computed tomography-based ANN model could more effectively detect CDE subjects when compared to their counterpart models. By employing the model, the CDE subjects may be identified early for therapeutic intervention.

Classification of rotator cuff tears in ultrasound images using deep learning models.

Rotator cuff tears (RCTs) are one of the most common shoulder injuries, which are typically diagnosed using relatively expensive and time-consuming diagnostic imaging tests such as magnetic resonance imaging or computed tomography. Deep learning algorithms are increasingly used to analyze medical images, but they have not been used to identify RCTs with ultrasound images. The aim of this study is to develop an approach to automatically classify RCTs and provide visualization of tear location using ultrasound images and convolutional neural networks (CNNs). The proposed method was developed using transfer learning and fine-tuning with five pre-trained deep models (VGG19, InceptionV3, Xception, ResNet50, and DenseNet121). The Bayesian optimization method was also used to optimize hyperparameters of the CNN models. A total of 194 ultrasound images from Kosin University Gospel Hospital were used to train and test the CNN models by five-fold cross-validation. Among the five models, DenseNet121 demonstrated the best classification performance with 88.2% accuracy, 93.8% sensitivity, 83.6% specificity, and AUC score of 0.832. A gradient-weighted class activation mapping (Grad-CAM) highlighted the sensitive features in the learning process on ultrasound images. The proposed approach demonstrates the feasibility of using deep learning and ultrasound images to assist RCTs' diagnosis.

Evaluation of the effect of filtered ultrafine particulate matter on bleomycin-induced lung fibrosis in a rat model using computed tomography, histopathologic analysis, and RNA sequencing.

We aimed to investigate the effect of chronic particulate matter (PM) exposure on bleomycin-induced lung fibrosis in a rat model using chest CT, histopathologic evaluation, and RNA-sequencing. A bleomycin solution was intratracheally administrated to 20 male rats. For chronic PM exposure, after four weeks of bleomycin treatment to induce lung fibrosis, PM suspension (experimental group) or normal saline (control group) was intratracheally administrated for 10 weeks. Chest CT was carried out in all rats, and then both lungs were extracted for histopathologic evaluation. One lobe from three rats in each group underwent RNA sequencing, and one lobe from five rats in each group was evaluated by western blotting. Inflammation and fibrosis scores in both chest CT and pathologic analysis were significantly more aggravated in rats with chronic PM exposure than in the control group. Several genes associated with inflammation and immunity were also upregulated with chronic PM exposure. Our study revealed that chronic PM exposure in a bleomycin-induced lung fibrosis rat model aggravated pulmonary fibrosis and inflammation, proven by chest CT, pathologic analysis, and RNA sequencing.

Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study.

BACKGROUND: Fat fraction values obtained from magnetic resonance imaging (MRI) can be used to obtain an accurate diagnosis of fatty liver diseases. However, MRI is expensive and cannot be performed for everyone. OBJECTIVE: In this study, we aim to develop multi-view ultrasound image-based convolutional deep learning models to detect fatty liver disease and yield fat fraction values. METHODS: We extracted 90 ultrasound images of the right intercostal view and 90 ultrasound images of the right intercostal view containing the right renal cortex from 39 cases of fatty liver (MRI-proton density fat fraction [MRI-PDFF] ≥ 5%) and 51 normal subjects (MRI-PDFF < 5%), with MRI-PDFF values obtained from Good Gang-An Hospital. We obtained combined liver and kidney-liver (CLKL) images to train the deep learning models and developed classification and regression models based on the VGG19 model to classify fatty liver disease and yield fat fraction values. We employed the data augmentation techniques such as flip and rotation to prevent the deep learning model from overfitting. We determined the deep learning model with performance metrics such as accuracy, sensitivity, specificity, and coefficient of determination (R2). RESULTS: In demographic information, all metrics such as age and sex were similar between the two groups-fatty liver disease and normal subjects. In classification, the model trained on CLKL images achieved 80.1% accuracy, 86.2% precision, and 80.5% specificity to detect fatty liver disease. In regression, the predicted fat fraction values of the regression model trained on CLKL images correlated with MRI-PDFF values (R2=0.633), indicating that the predicted fat fraction values were moderately estimated. CONCLUSIONS: With deep learning techniques and multi-view ultrasound images, it is potentially possible to replace MRI-PDFF values with deep learning predictions for detecting fatty liver disease and estimating fat fraction values.

Evaluation of the long-term effect of polyhexamethylene guanidine phosphate in a rat lung model using conventional chest computed tomography with histopathologic analysis.

There have been no studies on the effects of polyhexamethylene guanidine phosphate (PHMG) after a long period of exposure in the rodent model. We aimed to evaluate long-term lung damage after PHMG exposure using conventional chest computed tomography (CT) and histopathologic analysis in a rat model. A PHMG solution was intratracheally administrated to 24 male rats. At 8, 26, and 52 weeks after PHMG instillation, conventional chest CT was performed in all rats and both lungs were extracted for histopathologic evaluation. At 52 weeks after PHMG instillation, four carcinomas had developed in three of the eight rats (37.5%). Bronchiolo-alveolar hyperplasia and adenoma were found in rats at 8, 26, and 52 weeks post-instillation. The number of bronchiolo-alveolar hyperplasia significantly increased over time (P-value for trend< 0.001). The severity of lung fibrosis and fibrosis scores significantly increased over time (P-values for trend = 0.002 and 0.023, respectively). Conventional chest CT analysis showed that bronchiectasis and linear density scores suggestive of fibrosis significantly increased over time (P-value for trend < 0.001). Our study revealed that one instillation of PHMG in a rat model resulted in lung carcinomas and progressive and irreversible fibrosis one year later based on conventional chest CT and histopathologic analysis. PHMG may be a lung carcinogen in the rat model.

MTF1 Is Essential for the Expression of MT1B, MT1F, MT1G, and MT1H Induced by PHMG, but Not CMIT, in the Human Pulmonary Alveolar Epithelial Cells.

The inhalation of humidifier disinfectants (HDs) is linked to HD-associated lung injury (HDLI). Polyhexamethylene guanidine (PHMG) is significantly involved in HDLI, but the correlation between chloromethylisothiazolinone (CMIT) and HDLI remains ambiguous. Additionally, the differences in the molecular responses to PHMG and CMIT are poorly understood. In this study, RNA sequencing (RNA-seq) data showed that the expression levels of metallothionein-1 (MT1) isoforms, including MT1B, MT1E, MT1F, MT1G, MT1H, MT1M, and MT1X, were increased in human pulmonary alveolar epithelial cells (HPAEpiCs) that were treated with PHMG but not in those treated with CMIT. Moreover, upregulation of MT1B, MT1F, MT1G, and MT1H was observed only in PHMG-treated HPAEpiCs. The protein expression level of metal regulatory transcription factor 1 (MTF1), which binds to the promoters of MT1 isoforms, was increased in PHMG-treated HPAEpiCs but not in CMIT-treated HPAEpiCs. However, the expression of early growth response 1 (EGR1) and nuclear receptor superfamily 3, group C, member 1 (NR3C1), other transcriptional regulators involved in MT1 isomers, were increased regardless of treatment with PHMG or CMIT. These results suggest that MTF1 is an essential transcription factor for the induction of MT1B, MT1F, MT1G, and MT1H by PHMG but not by CMIT.

Evaluation of polyhexamethylene guanidine-induced lung injuries by chest CT, pathologic examination, and RNA sequencing in a rat model.

Our aim was to correlate chest CT and pathologic findings of polyhexamethylene guanidine phosphate (PHMG)-induced lung injuries in a rat model, to determine whether PHMG exposure causes lung tumors, and to explore genetic alterations according to PHMG exposure under the guidance of CT. A PHMG solution was intratracheally administrated to 40 male rats. Chest CT was carried out in all rats and both lungs were collected for histopathologic evaluation. At 4- and 8-weeks post-instillation, one lobe of the right lung from 3 rats was subjected to RNA sequencing. At least one abnormal CT finding was found in all rats at all weeks. The major CT findings were inflammation, fibrosis, and tumors in the pathologic analysis, where significant changes were observed over time. The lung lesions remained persistent after 8 weeks of PHMG exposure. In the pathologic analysis, the extent/severity of inflammation did not show statistically significant changes over time, whereas the extent/severity of fibrosis increased continuously up to 6 weeks after PHMG exposure and then decreased significantly at 8 weeks. Bronchiolar-alveolar adenomas which have malignant potential were found in 50% of rats at 6 and 8 weeks after PHMG exposure. Also, several genes associated with lung cancer, acute lung injury, and pulmonary fibrosis were detected. Our study revealed that PHMG-induced lung injury and its changes according to the number of weeks after exposure were demonstrated using chest CT and pathologic evaluation. In addition, we showed that PHMG exposure caused lung tumors and genetic alterations according to PHMG exposure under the guidance of CT.

Changes in concentrations and characteristics of asbestos fibers dispersed from corrugated asbestos cement sheets due to stabilizer treatment.

Asbestos management in Korea has, to date, focused exclusively on dismantlement and removal; however, the effective management of asbestos in public facilities and rural dwellings is also critical. This study compares eight different asbestos stabilization treatments and their effectiveness in reducing asbestos fiber dispersion from weathered corrugated asbestos cement sheets (CACS) under different wind conditions. The effectiveness of the different asbestos stabilizers was assessed in order to identify the characteristics of fibers dispersed from treated CACS samples. The impact of wind speed on the concentration and composition of the dispersed fibers was also evaluated. For all wind speeds, the concentration of the fibers dispersed from the CACS samples that were treated with stabilizers decreased relative to the untreated CACS. These results show that asbestos concentrations were considerably reduced following stabilizer treatment and that treated CACS dispersed fewer asbestos fibers relative to untreated CACS. The results of this study will be useful for the development of strategies regarding the appropriate management of asbestos in public buildings.

A 3D-CNN model with CT-based parametric response mapping for classifying COPD subjects.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder involving abnormalities of lung parenchymal morphology with different severities. COPD is assessed by pulmonary-function tests and computed tomography-based approaches. We introduce a new classification method for COPD grouping based on deep learning and a parametric-response mapping (PRM) method. We extracted parenchymal functional variables of functional small airway disease percentage (fSAD%) and emphysema percentage (Emph%) with an image registration technique, being provided as input parameters of 3D convolutional neural network (CNN). The integrated 3D-CNN and PRM (3D-cPRM) achieved a classification accuracy of 89.3% and a sensitivity of 88.3% in five-fold cross-validation. The prediction accuracy of the proposed 3D-cPRM exceeded those of the 2D model and traditional 3D CNNs with the same neural network, and was comparable to that of 2D pretrained PRM models. We then applied a gradient-weighted class activation mapping (Grad-CAM) that highlights the key features in the CNN learning process. Most of the class-discriminative regions appeared in the upper and middle lobes of the lung, consistent with the regions of elevated fSAD% and Emph% in COPD subjects. The 3D-cPRM successfully represented the parenchymal abnormalities in COPD and matched the CT-based diagnosis of COPD.

Follow-up of Soluble Mesothelin-Related Protein Levels in Participants With Asbestos-Related Disorders.

BACKGROUND: Asbestos exposure is associated with the development of the cancer malignant mesothelioma (MM). Measurement of soluble mesothelin-related protein (SMRP) has been suggested as a method for detection of MM in its early stages. We prospectively examined SMRP levels in participants with asbestos exposure who are a group at a high risk of development of MM. METHODS: This study was a follow-up of our cohort of 322 asbestos-exposed participants. No further participants developed MM or malignancy over the study period. Mean follow-up time was 22.9 months. RESULTS: Mean (standard deviation) SMRP levels at baseline and follow-up were 0.94 (0.79) and 0.91 (0.86) nmol/L (p = 0.1033), respectively. Mean SMRP levels of the healthy individuals exposed to asbestos at baseline was significantly lower than those of participants with asbestosis and pleural plaques alone; similar patterns were found on follow-up measurements. There was a statistically significant effect of age on serial SMRP measurements. Our study confirms higher levels in participants with nonmalignant asbestos-related disorders. Levels decreased in asbestos-related disorders other than asbestosis, where a small increase was observed. We did not detect any further cases of malignancy. CONCLUSION: Monitoring programs for early detection of MM need to take into account increased SMRP levels found in benign asbestos-related diseases.

Characteristics of asbestos fibers in lung tissue from occupational and environmental asbestos exposure of lung cancer patients in Busan, Korea.

The Asbestos Injury Relief Act in Korea requires that asbestos exposure be assessed through clinical examination and chest computed tomography (CT). However, a more specific measurement of asbestos characteristics in the lung tissue may be appropriate. We aimed to investigate the asbestos burden and characterize asbestos fibers in patients with lung cancer and ultimately assess the relationship between occupational and environmental asbestos exposure and lung cancer in Korea. We evaluated 37 lung cancer patients (LCPs) from Busan. The factors affecting asbestos burden in LCPs were analyzed using a multiple regression analysis. History of asbestos exposure (environmental/occupational), male sex, and old age were the main factors affecting asbestos burden in lung tissues of LCPs. These factors had an approximate 37% adjusted coefficient of determination. There was a significant difference in the length of asbestos fibers (4.06-37.6 µm vs. 4.26-91.7 µm) and aspect ratio (4.5-151.9 vs. 5.6-735.6) between those who were occupationally exposed to asbestos and those who were environmentally exposed (P < 0.01). Therefore, both environmental/occupational exposure to asbestos should be strongly managed to reduce the risk of lung cancer, and exposure should be assessed according to the characteristics of asbestos fibers in the lung tissue.

Quantitative CT-based structural alterations of segmental airways in cement dust-exposed subjects.

BACKGROUND: Dust exposure has been reported as a risk factor of pulmonary disease, leading to alterations of segmental airways and parenchymal lungs. This study aims to investigate alterations of quantitative computed tomography (QCT)-based airway structural and functional metrics due to cement-dust exposure. METHODS: To reduce confounding factors, subjects with normal spirometry without fibrosis, asthma and pneumonia histories were only selected, and a propensity score matching was applied to match age, sex, height, smoking status, and pack-years. Thus, from a larger data set (N = 609), only 41 cement dust-exposed subjects were compared with 164 non-cement dust-exposed subjects. QCT imaging metrics of airway hydraulic diameter (Dh), wall thickness (WT), and bifurcation angle (θ) were extracted at total lung capacity (TLC) and functional residual capacity (FRC), along with their deformation ratios between TLC and FRC. RESULTS: In TLC scan, dust-exposed subjects showed a decrease of Dh (airway narrowing) especially at lower-lobes (p < 0.05), an increase of WT (wall thickening) at all segmental airways (p < 0.05), and an alteration of θ at most of the central airways (p < 0.001) compared with non-dust-exposed subjects. Furthermore, dust-exposed subjects had smaller deformation ratios of WT at the segmental airways (p < 0.05) and θ at the right main bronchi and left main bronchi (p < 0.01), indicating airway stiffness. CONCLUSIONS: Dust-exposed subjects with normal spirometry demonstrated airway narrowing at lower-lobes, wall thickening at all segmental airways, a different bifurcation angle at central airways, and a loss of airway wall elasticity at lower-lobes. The airway structural alterations may indicate different airway pathophysiology due to cement dusts.

Prevalence and Risk Factors of Occupational Skin Disease in Korean Workers from the 2014 Korean Working Conditions Survey.

PURPOSE: Occupational skin disease (OSD) is a commonly known occupational disease. However, epidemiological data about this condition in Korea are limited. We aimed to estimate the prevalence and risk factors of OSD using nationally representative data. MATERIALS AND METHODS: We used data from the large-scale, cross-sectional, nationwide 4th Korean Working Conditions Survey conducted in 2014. OSD was defined as skin diseases caused or aggravated by working environments as indicated in a self-reported questionnaire. Factors affecting the occurrences of OSD were investigated using logistic regression analysis. RESULTS: The prevalence rates of OSD were 1.35% in all workers and 62.2% in workers with skin diseases. The workers with OSD were older, had lower educational levels, and had longer working times per week than those without OSD (p<0.001). Furthermore, OSDs occurred more frequently in self-employed workers (p=0.002), those with small-sized businesses (p=0.008), those with longer working durations (p<0.001), and manual and service workers (p<0.001). Although the workers with OSD had greater exposure to various hazardous factors, logistic multivariate analysis showed that high temperatures and skin contact with chemical products were significantly correlated (odds ratios: 2.096 and 2.326, respectively). High prevalence rates of OSD were observed in membership organizations/repair/other personal services (3.2%), agriculture/forestry/fishing (2.7%), manufacturing (2.0%), and construction (1.6%) industries. Additionally, depression/anxiety problems were significantly more prevalent in workers with OSD than in those without (p<0.001). CONCLUSION: This is the first study to present large-scale epidemiological data on OSD prevalence in Korean workers. Our results highlight modifiable factors contributing to the development of OSDs.