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Computer-aided diagnosis of pulmonary diseases using x-ray darkfield radiography.

In this work we develop a computer-aided diagnosis (CAD) scheme for classification of pulmonary disease for grating-based x-ray radiography. In addition to conventional transmission radiography, the grating-based technique provides a dark-field imaging modality, which utilizes the scattering properties of the x-rays. This modality has shown great potential for diagnosing early stage emphysema and fibrosis in mouse lungs in vivo. The CAD scheme is developed to assist radiologists and other medical experts to develop new diagnostic methods when evaluating grating-based images.

The scheme consists of three stages: (i) automatic lung segmentation; (ii) feature extraction from lung shape and dark-field image intensities; (iii) classification between healthy, emphysema and fibrosis lungs. A study of 102 mice was conducted with 34 healthy, 52 emphysema and 16 fibrosis subjects. Each image was manually annotated to build an experimental dataset. System performance was assessed by: (i) determining the quality of the segmentations; (ii) validating emphysema and fibrosis recognition by a linear support vector machine using leave-one-out cross-validation. In terms of segmentation quality, we obtained an overlap percentage (Ω) 92.63  ±  3.65%, Dice Similarity Coefficient (DSC) 89.74  ±  8.84% and Jaccard Similarity Coefficient 82.39  ±  12.62%. For classification, the accuracy, sensitivity and specificity of diseased lung recognition was 100%.

Classification between emphysema and fibrosis resulted in an accuracy of 93%, whilst the sensitivity was 94% and specificity 88%. In addition to the automatic classification of lungs, deviation maps created by the CAD scheme provide a visual aid for medical experts to further assess the severity of pulmonary disease in the lung, and highlights regions affected.

Study of inhaler technique in asthma patients: differences between pediatric and adult patients.

OBJECTIVE: Inhaler technique comprises a set of procedures for drug delivery to the respiratory system. The oral inhalation of medications is the first-line treatment for lung diseases. Using the proper inhaler technique ensures sufficient drug deposition in the distal airways, optimizing therapeutic effects and reducing side effects. The purposes of this study were to assess inhaler technique in pediatric and adult patients with asthma; to determine the most common errors in each group of patients; and to compare the results between the two groups.

METHODS: This was a descriptive cross-sectional study. Using a ten-step protocol, we assessed inhaler technique in 135 pediatric asthma patients and 128 adult asthma patients.

RESULTS: The most common error among the pediatric patients was failing to execute a 10-s breath-hold after inhalation, whereas the most common error among the adult patients was failing to exhale fully before using the inhaler.

CONCLUSIONS: Pediatric asthma patients appear to perform most of the inhaler technique steps correctly. However, the same does not seem to be true for adult patients.

Diagnostic value of endobronchial ultrasound-guided transbronchial needle aspiration in various lung diseases.

 OBJECTIVE: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a new method for the diagnosis and staging of lung disease, and its use is increasing worldwide. It has been used as a means of diagnosing lung cancer in its initial stages, and there are data supporting its use for the diagnosis of benign lung disease. The aim of this study was to share our experience with EBUS-TBNA and discuss its diagnostic value.

METHODS: We retrospectively analyzed the results related to 159 patients who underwent EBUS-TBNA at our pulmonary medicine clinic between 2010 and 2013. We recorded the location and size of lymph nodes seen during EBUS. Lymph nodes that appeared to be affected on EBUS were sampled at least twice. We recorded the diagnostic results of EBUS-TBNA and (for cases in which EBUS-TBNA yielded an inconclusive diagnosis) the final diagnoses after further investigation and follow-up.

RESULTS: We evaluated 159 patients, of whom 89 (56%) were male and 70 (44%) were female. The mean age was 54.6 ± 14.2 years among the male patients and 51.9 ± 11.3 years among the female patients. Of the 159 patients evaluated, 115 (84%) were correctly diagnosed by EBUS. The diagnostic accuracy of EBUS-TBNA was 83% for benign granulomatous diseases and 77% for malignant diseases.

CONCLUSIONS: The diagnostic value of EBUS-TBNA is also high for benign pathologies, such as sarcoidosis and tuberculosis. In patients with mediastinal disorders, the use of EBUS-TBNA should be encouraged, primarily because it markedly reduces the need for mediastinoscopy.

Chemotherapeutic Response and Prognosis among Lung Cancer Patients with and without Depression.

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The current study examined quality of life, progression of disease, and survival rate during chemotherapy in newly diagnosed non-small cell lung cancer (NSCLC) patients with depression (n=48) and without depression (n=78). Further, the study explored the hypothesis that the survival benefit resulted from the chemotherapy of docetaxel and cisplatin (the DC regimen). PATIENTS AND METHODS: In total, 126 patients with newly diagnosed NSCLC participated in a cross-sectional study of DC chemotherapy integrated with standard oncology care in depression and non-depression groups. The health-related quality of life (HR-QOL) was assessed using the quality of life questionnaire for Chinese cancer patients receiving chemobiotherapy (QLQ-CCC). Depression was self-rated using the Zung Self-Rating Depression Scale (Z-SDS). Both HR-QOL and Z-SDS were completed before the first and after the last cycle of chemotherapy. Association between depression and quality of life, treatment responses, adverse effects and survival rate was considered positive at the significance level of p<0.05. Pearson and Spearman correlation coefficient, t-test and other statistical analysis were performed using the SPSS software version 13.0 for Windows. RESULTS: In total, 126 lung cancer patients were evaluated, 38% had a diagnosis of depression. The presence of depression was associated with reduced quality of life, increased progression of disease, nausea and fatigue and reduced survival rate by nearly 90 days on follow-up. Therefore, depression significantly predicted worse survival (P=0.009).In addition, the chemotherapy DC regimen did not appear to improve the quality of life in depressed patients (SDS 94.96±18.14 before chemotherapy vs. SDS 100.04±16.61 after therapy, P=0.155). In a secondary analysis, there was a positive relationship between depression and nausea and fatigue but there was no significant difference in hematologic toxicities between the depression and non-depression groups. CONCLUSION: Depression was associated with worse survival in patients with newly diagnosed NSCLC. Also, the chemotherapy DC regimen did not improve quality of life in depressed patients and the data do not support the hypothesis that treatment responses of NSCLC patients with depression mediated the observed survival benefit from the DC regimen. There were more cases of progressed disease in the depressed group. Findings suggest that NSCLC patients with depression are at increased risk for decline in HR-QOL and survival rate during chemotherapy than patients without depression.

Identification of gene markers in the development of smoking-induced lung cancer.

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Lung cancer is a malignant tumor with high mortality in both women and men.
To study the mechanisms of smoking-induced lung cancer, we analyzed microarray of GSE4115. GSE4115 was downloaded from Gene Expression Omnibus including 78 and 85 bronchial epithelium tissue samples separately from smokers with and without lung cancer. Limma package in R was used to screen differentially expressed genes (DEGs). Hierarchical cluster analysis for DEGs was conducted using orange software and visualized by distance map. Using DAVID software, functional and pathway enrichment analyses separately were conducted for the DEGs. And protein-protein interaction (PPI) network was constructed using Cytoscape software. Then, the pathscores of enriched pathways were calculated. Besides, functional features were screened and optimized using the recursive feature elimination (RFE) method. Additionally, the support vector machine (SVM) method was used to train model.
Total 1923 DEGs were identified between the two groups. Hierarchical cluster analysis indicated that there were differences in gene level between the two groups. And SVM analysis indicated that the five features had potential diagnostic value. Importantly, MAPK1 (degree=30), SRC (degree=29), SMAD4 (degree=23), EEF1A1 (degree=21), TRAF2 (degree=21) and PLCG1 (degree=20) had higher degrees in the PPI network of the DEGs. They might be involved in smoking-induced lung cancer by interacting with each other (e.g. MAPK1-SMAD4, SMAD4-EEF1A1 and SRC-PLCG1). MAPK1, SRC, SMAD4, EEF1A1, TRAF2 and PLCG1 might be responsible for the development of smoking-induced lung cancer.

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