• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.226-233
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• 2023

Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

• Progress in Medical Physics
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• v.25 no.2
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• pp.100-109
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• 2014

In stereotactic body radiotherapy (SBRT), the accurate location of treatment sites should be guaranteed from the respiratory motions of patients. Lots of studies on this topic have been conducted. In this letter, a new verification method simulating the real respiratory motion of heterogenous treatment regions was proposed to investigate the accuracy of lung SBRT for Volumetric Modulated Arc Therapy. Based on the CT images of lung cancer patients, lung phantoms were fabricated to equip in $QUASAR^{TM}$ respiratory moving phantom using 3D printer. The phantom was bisected in order to measure 2D dose distributions by the insertion of EBT3 film. To ensure the dose calculation accuracy in heterogeneous condition, The homogeneous plastic phantom were also utilized. Two dose algorithms; Analytical Anisotropic Algorithm (AAA) and AcurosXB (AXB) were applied in plan dose calculation processes. In order to evaluate the accuracy of treatments under respiratory motion, we analyzed the gamma index between the plan dose and film dose measured under various moving conditions; static and moving target with or without gating. The CT number of GTV region was 78 HU for real patient and 92 HU for the homemade lung phantom. The gamma pass rates with 3%/3 mm criteria between the plan dose calculated by AAA algorithm and the film doses measured in heterogeneous lung phantom under gated and no gated beam delivery with respiratory motion were 88% and 78%. In static case, 95% of gamma pass rate was presented. In the all cases of homogeneous phantom, the gamma pass rates were more than 99%. Applied AcurosXB algorithm, for heterogeneous phantom, more than 98% and for homogeneous phantom, more than 99% of gamma pass rates were achieved. Since the respiratory amplitude was relatively small and the breath pattern had the longer exhale phase than inhale, the gamma pass rates in 3%/3 mm criteria didn't make any significant difference for various motion conditions. In this study, the new phantom model of 4D dose distribution verification using patient-specific lung phantoms moving in real breathing patterns was successfully implemented. It was also evaluated that the model provides the capability to verify dose distributions delivered in the more realistic condition and also the accuracy of dose calculation.

• Journal of Radiation Protection and Research
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• v.19 no.1
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• pp.69-80
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• 1994

The TCMI(Three-Compartment Model for iodine) computer code has been developed, which is based on the three-compartment model and the respiratory model recommended in ICRP publication 54. This code is able to evaluate the thyroid burden, dose equivalent, committed dose equivalent and urinary excretion rate as time-dependent functions from the input data: working time and the radioiodine concentration in air. Using the TCMI code, the time-dependent thyroid burdens, the thyroid doses and the urinary excretion rates were calculated for three specific exposure patterns : acute, chronic and periodic. Applicability as an internal dose evaluation method has been assessed by comparing the results with some operational experiences. Simple equations and tables are provided to be used in the evaluation of the thyroid burden and the resulting doses for given I-131 concentration in air and the working time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2016-2029
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• 2023

Accurate prediction of critical illness is significant for ensuring the lives and health of patients. The selection of indicators affects the real-time capability and accuracy of the prediction for critical illness. However, the diversity and complexity of these indicators make it difficult to find potential connections between them and critical illnesses. For the first time, this study proposes an indicator analysis model to extract key indicators from the preoperative and intraoperative clinical indicators and laboratory results of critical illnesses. In this study, preoperative and intraoperative data of heart failure and respiratory failure are used to verify the model. The proposed model processes the datum and extracts key indicators through four parts. To test the effectiveness of the proposed model, the key indicators are used to predict the two critical illnesses. The classifiers used in the prediction are light gradient boosting machine (LightGBM) and eXtreme Gradient Boosting (XGBoost). The predictive performance using key indicators is better than that using all indicators. In the prediction of heart failure, LightGBM and XGBoost have sensitivities of 0.889 and 0.892, and specificities of 0.939 and 0.937, respectively. For respiratory failure, LightGBM and XGBoost have sensitivities of 0.709 and 0.689, and specificity of 0.936 and 0.940, respectively. The proposed model can effectively analyze the correlation between indicators and postoperative critical illness. The analytical results make it possible to find the key indicators for postoperative critical illnesses. This model is meaningful to assist doctors in extracting key indicators in time and improving the reliability and efficiency of prediction.

• Tuberculosis and Respiratory Diseases
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• v.46 no.3
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• pp.386-393
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• 1999

Objective : Cardiopulmonary exercise testing in patients with heart and lung problems is used to assess functional capacity, evaluate responses to medical treatment, plan for exercise therapy, assess progression of disease process, and determine prognosis. Particularly in the patients with lung cancer, the exercise pulmonary function test gives significant physiologic assessment of the lung resection candidate. Common exercise modalities are running and cycling. Until now, the comparison of two tests mainly has been done in normal person and patients with cardiac diseases. This study is designed to compare the treadmill and bicycle exercise pulmonary function test in patients with respiratory diseases. Methods : Twenty one patients underwent a progressively incremental exercise test to the symptom-limited stage with the treadmill (Vmax29 Sensor Medics, USA) and the bicycle(model No. 2,900 Sensor Medics, USA) with 7 days apart between the two tests. Measurements were made of the metabolic, cardiorespiratory parameters, blood gases, and symptoms. Results : The results of the treadmill exercise showed significant elevation in the $VO_2$max, VEmax, and anaerobic threshold compared to those of bicycle exercise. In contrast, the results of the breathing and heart rate reserve showed the reverse. Conclusion : These results suggest that the type of exercise should be taken into consideration when interpreting exercise test in patients with respiratory diseases.

• The Journal of Internal Korean Medicine
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• v.45 no.1
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• pp.11-30
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• 2024

Objectives: This study evaluated the effects of Ssanghwa-tang (SHT) on lung injury and muscle loss in a COPD mouse model. Methods: C57BL/6 mice were challenged with cigarette smoke extract and lipopolysaccharide, and then treated with two concentrations of SHT (250 and 500 mg/kg). After sacrifice, the bronchoalveolar lavage fluid (BALF) or lung tissue was analyzed by cytospin, ELISA, real-time PCR, flow cytometry analysis, and H&E and Masson's trichrome staining. The grip strength of COPD mice was measured using a grip strength meter. The running time of COPD mice was measured by a treadmill test. Muscle tissue of the quadriceps was stained with H&E and Masson's trichrome staining. Results: SHT significantly inhibited the increase in neutrophil numbers in BALF and significantly decreased immune cell activity in BALF and lung tissue. It also significantly inhibited the increase in TNF-α, IL-17, and MIP2 in BALF. Real-time PCR analysis revealed that the mRNA expression of TNF-α, IL-17, MIP2, and TRPV1 in lung tissue showed a significant decrease compared with the control group. Lung tissue damage was significantly reduced in the histological analysis. The grip strength and running time of the COPD mice showed a significant decrease compared with the control group. In histological staining, SHT was found to reduce the damage to muscle tissue. Conclusions: This study indicates that SHT can be used as a therapeutic agent for COPD patients by inhibiting lung injury and muscle loss.

• Tuberculosis and Respiratory Diseases
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• v.86 no.4
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• pp.284-293
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• 2023

Background: Attitudes towards smoking, lung cancer screening, and perceived risk of lung cancer have not been widely studied in Malaysia. The primary objective of this study was to describe the factors affecting the willingness of high-risk current smokers and ex-smokers to undergo low-dose computed tomography (LDCT) screening for lung cancer. Methods: A prospective, cross-sectional questionnaire study was conducted in current smokers or ex-smokers aged between 55 and 80 years at three hospitals in Kota Kinabalu, Sabah, Malaysia. The questionnaire recorded the following parameters: perceived lung cancer risk; Prostate Lung Colon Ovarian Cancer 2012 risk prediction model excluding race and ethnicity predictor (PLCO_m2012norace); demographic characteristics; psychosocial characteristics; and attitudes towards lung cancer and lung cancer screening. Results: A vast majority of the 95 respondents (94.7%) indicated their willingness to undergo screening. Stigma of lung cancer, low levels of knowledge about lung cancer symptoms, concerns about financial constraints, and a preference for traditional medication were still prevalent among the respondents, and they may represent potential barriers to lung cancer screening uptake. A desire to have an early diagnosis (odds ratio [OR], 11.33; 95% confidence interval [CI], 1.53 to 84.05; p=0.02), perceived time constraints (OR, 3.94; 95% CI, 1.32 to 11.73; p=0.01), and proximity of LDCT screening facilities (OR, 14.33; 95% CI, 1.84 to 111.4; p=0.01) had significantly higher odds of willingness to undergo screening. Conclusion: Although high-risk current smokers and ex-smokers are likely to undergo screening for lung cancer, several psychosocial barriers persist. The results of this study may guide the policymakers and clinicians regarding the need to improve lung cancer awareness in our population.

• The Journal of Internal Korean Medicine
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• v.32 no.2
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• pp.203-216
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• 2011

Objectives : This study was conducted to evaluate the protective effects of bee venom on lipopolysaccharide (LPS)-induced chronic obstructive pulmonary disease (COPD). Methods : In this study, LPS was administrated to Balb/c mice to induce a disease that resembles COPD. 2 hr prior to LPS administration, mice were treated with bee venom via an intraperitoneal injection. Total cell number and neutrophils number in bronchoalveolar lavage fluid were counted and pro-inflammatory cytokines were also measured. For histologic analysis, periodic acid Schiff (PAS) and hematoxylin and eosin (H&E) stains were evaluated. Proliferating cell nuclear antigens (PCNA) were also assessed by immunohistochemistry. Results : On 7 days after LPS stimulation, influx of neutrophils significantly decreased in the bee venom group, compared with the COPD group. In addition, TNF-a and IL-6 levels decreased in bee venom group. Histological results also demonstrated the attenuation effect of bee venom on LPS-induced lung inflammation. Conclusions : These data suggest that bee venom has protective effects on LPS-induced lung inflammation. Therefore, bee venom may represent a novel therapeutic agent for lung inflammation and in particular for COPD.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.11 s.254
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• pp.1051-1056
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• 2006

The mean and RMS velocity field of the respiratory gas flow in the human airway was studied experimentally by particle image velocimetry (PIV). Some researchers investigated the airflow for the mouth breathing case both experimentally and numerically. But it is very rare to investigate the airflow of nose breathing in a whole airway due to its geometric complexity. We established the procedure to create a transparent rectangular box containing a model of the human airway for PIV measurement by combination of the RP and the curing of clear silicone. We extend this to make a whole airway including nasal cavities, larynx, trachea, and 2 generations of bronchi. The CBC algorithm with window offset (64 $\times$ 64 to 32 $\times$ 32) is used for vector searching in PIV analysis. The phase averaged mean and RMS velocity distributions in Sagittal and coronal planes are obtained for 7 phases in a respiratory period. Some physiologic conjectures are obtained. The main stream went through the backside of larynx and trachea in inspiration and the frontal side in expiration. There exist vortical motions in inspiration, but no prominent one in expiration.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.28 no.2
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• pp.190-199
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• 2018

Objectives: The purpose of this case study is to assess the current airflow and find the ideal ventilation conditions in tank reactors for minimizing the possibility of exposure respiratory dusts(size of $2.5{\mu}m$, $10{\mu}m$) when workers exchange catalysts in the tank reactors. Methods: A Numerical study was performed to determine ideal ventilation conditions, We considered two sizes of airborne respiratory particles($2.5{\mu}m$, $10{\mu}m$) at 12points from the bottom of tank reactor. We changed input & output ventilation conditions and analyzed the particle motion in the tank reactor. The star-ccm+, computational fluid dynamics tool was used to predict air & particle flow patterns in the tank reactor and a numerical simulation was achieved by applying the realized ${\kappa}-{\varepsilon}$ turbulence model and the Lagrangian particle tracking method. Results: From the results, the increase of recirculation air had a significant impact on removing dusts because they are removed by HEPA filter. To the contrary, Increasing the clean air quantity or changing the input position of clean air is not good for workers because it causes the exit of respiratory dusts through workers' entrance or cause it to remail suspended in the air in the workplace tank.