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Background: Adenosine deaminase (ADA) is a commonly used marker in the diagnosis of tuberculous effusion and there is evidence that its production is linked to T cells and monocytes. Data on the correlation between ADA and T cells or macrophages in tuberculous effusions are conflicting. Furthermore, no studies have examined a possible correlation between pleural tissue infiltration and ADA. Objectives: We undertook this study to examine cell subsets in the fluid and the pleura in tuberculous effusion and their correlation to ADA. The use of cell subsets as a marker in the differential diagnosis was also examined. Methods: Pleural fluid from 36 patients with tuberculous and 34 patients with malignant effusion as well as pleural tissue biopsies from 16 patients with tuberculous pleurisy were examined. The APAAP and the avidin-biotin complex immunocytochemical methods were used to examine CD4+ T cells and macrophages (CD68+), while ADA activity was measured by the Giusti colorimetric method. Results: Our results showed that, in pleural fluid, CD4+ cells and ADA were significantly higher in tuberculous compared to malignant effusion (p < 0.001 for all measurements). In pleural tissue biopsies, macrophages were the predominant cells but CD4+ T cells were also abundant. A significant correlation was found between ADA and CD4+ numbers in pleural fluid and tissue (r = 0.45, p < 0.01; r = 0.75, p < 0.001, respectively). ADA had high sensitivity and specificity for differential diagnosis while cell subsets did not. Conclusions: These results indicate that ADA activity correlates to CD4+ T cell infiltration in the pleura and the fluid. Moreover, ADA but no cell subsets may be used as markers of tuberculous effusion.

Portable chest radiography is a valuable tool for screening patients hospitalized in intensive care, providing visual cues for diagnosis and physiological measurements. However, its practicality comes at the cost of quality, which is mainly affected by misaligned body positioning, thus increasing x-ray misinterpretation rates. This paper presents a novel methodology for the detection of the lung field boundaries in portable chest radiographs of patients with bacterial pulmonary infections. Such infections are radiographically manifested as foci of consolidations which can lead to vague or invisible lung field boundaries, difficult to distinguish even by experienced physicians. Conventional and state-of-the-art approaches address mainly stationary radiographs, whereas only a few of them cope with pulmonary infections. The proposed methodology is based on an active shape model incorporating shape prior information about the lung fields. The model is initialized by a novel technique utilizing a set of salient points detected on the peripheral anatomic structures of the lungs. A selective thresholding algorithm based on a spinal cord sampling process supports both the initialization and the evolution of the model for the detection of the lung field boundaries. The experiments show that the proposed methodology outperforms state-of-the-art approaches.

The cytologic results of lavage were positive for malignant cells in eight of 85 patients (9.4%). The existence of cancer cells in the pleural cavity can be the result of their exfoliation or surgical manipulations. The mechanical irrigation subdivides the percentage of positive samples. Our study supports that the positive findings on pleural lavage cytology is an essential prognostic factor.

We examined p53, p21WAF-1, and Bcl-2 protein expression in malignant and nonmalignant bronchial specimens obtained during bronchoscopy from 60 lung cancer patients. Twenty-six (43.3%), 36 (60%), and 20 (33.3%) of the tumors were p53, p21WAF-1, and Bcl-2 positive, respectively. High-level p53 and Bcl-2 expression characterized advanced preneoplastic lesions, while hyperplasias, squamous metaplasias, and mild dysplasias exhibited low levels of expression. There was no difference between early and advanced preneoplastic lesions in the level of p21WAF-1, expression. A history of heavy smoking was associated with p21WAF-1, expression in preneoplastic lesions (p = 0.022) and tumors (p = 0.032). p53(-)/p21WAF-1(++)/bcl-2(-) was the only significant independent predictor of lower clinical stage (OR: 0.88, p = 0.038). In univariate analysis, survival of NSCLC patients was affected by disease stage (p <0.001) and tumor histology (p = 0.018). While single-protein expression was not associated with prognosis, the combined immunophenotype p53(-)/p21WAF-1(++)/bcl-2(-) predicted longer survival (p = 0.03). In multivariate analysis, only the TNM stage was found to be a prognostic factor for NSCLC. We conclude that p53 and Bcl-2 alterations may happen early in bronchial carcinogenesis and that absence of these alterations in combination with p21WAF-1, overexpression may be associated with a less aggressive tumor behavior.

Loss of function of the p53 tumor supressor gene is involved in nearly all human cancer. Recently a cellular oncogene product, mdm2, has been shown to bind to p53 and eliminate its ability to function as a transcription factor. mdm2 and p53 immunohistochemical protein expression was studied in tumor tissues, preneoplastic lesions, and normal bronchial mucosa. The specimens were obtained during diagnostic bronchoscopy from 53 patients with lung cancer. In the tumor specimens, p53 nuclear staining was detected in 26 (49%) cases, mdm2 in 11 (20.7%), and simultaneous expression of both proteins in 6 (11.3%) cases. Thirty-five sections with preneoplastic lesions were found in 21 patients. p53 nuclear staining was found in 11 of 35 and mdm2 in 6 of 35 sections. In normal cells, mdm2 positive staining was found in 18 and p53 in 12 specimens. Simultaneous p53 and mdm2 expression was found in 4 specimens. Our results indicate that p53 expression is more frequent than mdm2 expression in lung cancer tissues. Alterations in these proteins are early events and may represent alternative pathways in carcinogenesis.

We present a novel framework for automatic extraction of the progress of an infection from time-series medical images, with application to pneumonia monitoring. In each image of a series, the lungs, which are the body components of interest in our study, are detected and delineated by a modified active shape model-based algorithm that is constrained by binary approximation masks. This algorithm offers resistance in the presence of infection manifestations that may distort the typical appearance of the body components of interest. The relative extent of the infection manifestations is assessed by supervised classification of samples acquired from the respective image regions. The samples are represented by multiple dissimilarity features fused according to a novel entropy-based weighted voting scheme offering nonparametric operation and robustness to outliers. The output of the proposed framework is a time series of structured data quantifying the relative extent of infection manifestations at the body components of interest over time. The results obtained indicate an improved performance over relevant state-of-the-art methods. The overall accuracy quantified by the area under receiver operating characteristic reaches 90.0 ± 2.1%. The effectiveness of the proposed framework to pneumonia monitoring, the generality, and the adaptivity of its methods open perspectives for application to other medical imaging domains.

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