[18F]fluorodeoxyglucose positron emission tomography/computed tomography in combination with clinical data in predicting overall survival in non-small-cell lung cancer patients: A retrospective study.

INTRODUCTION: Positron emission tomography/computed tomography (PET/CT) has an established role in evaluating patients with lung cancer. The aim of this work was to assess the predictive capability of [18F]Fluorodeoxyglucose ([18F]FDG) PET/CT parameters on overall survival (OS) in lung cancer patients using an artificial neural network (ANN) in parallel with conventional statistical analysis. METHODS: Retrospective analysis was performed on a group of 165 lung cancer patients (98M, 67F). PET features associated with the primary tumor: maximum and mean standardized uptake value (SUVmax, SUVmean), total lesion glycolysis (TLG) metabolic tumor volume (MTV) and area under the curve-cumulative SUV histogram (AUC-CSH) and metastatic lesions (SUVmaxtotal, SUVmeantotal, TLGtotal, and MTVtotal) were evaluated. In parallel with conventional statistical analysis (Chi-Square analysis for nominal data, Student's t test for continuous data), the data was evaluated using an ANN. There were 97 input variables in 165 patients using a binary classification of either below, or greater than/equal to median survival post primary diagnosis. Additionally, phantom study was performed to assess the most optimal contouring method. RESULTS: Males had statistically higher SUVmax (mean: 10.7 vs 8.9; p = 0.020), MTV (mean: 66.5 cm3 vs. 21.5 cm3; p = 0.001), TLG (mean 404.7 vs. 115.0; p = 0.003), TLGtotal (mean: 946.7 vs. 433.3; p = 0.014) and MTVtotal (mean: 242.0 cm3 vs. 103.7 cm3; p = 0.027) than females. The ANN after training and validation was optimised with a final architecture of 4 scaling layer inputs (TLGtotal, SUVmaxtotal, SUVmeantotal and disease stage) and receiving operator characteristic (ROC) analysis demonstrated an AUC of 0.764 (sensitivity of 92.3%, specificity of 57.1%). CONCLUSION: Conventional statistical analysis and the ANN provided concordant findings in relation to variables that predict decreased survival. The ANN provided a weighted algorithm of the 4 key features to predict decreased survival. IMPLICATION FOR PRACTICE: Identification of parameters which can predict survival in lung cancer patients might be helpful in choosing the group of patients who require closer look during the follow-up.

[Carrier status of Staphylococcus aureus among students of different courses]. / Nosicielstwo Staphylococcus aureus wsród studentów roznych Kierunków nauczania.

Staphylococcus aureus is a frequent pathogen of nosocomial infections. The main part in the spread of these microorganisms take symptomless carriers. The aim the research was defining the carrierstate of S. aureus among students of Medical Academy and University. The investigation showed a greater carrierstate in the group of Medical students (33%) than in the group of University students. Strains isolated from the Medical students were more differentiated in biochemical tests and they were more drug-resistant mainly to Augmentin (51.5% resistant strains) and doxycycline (24% resistant strains). A great percentage of ampicillin-resistant strains (94%) was found among the strains isolated from both groups. Results of the research showed greater carrierstate among people who had direct contact with patients and infectious materials and proved a wide range of drug-resistance among hospital strains. Carriers of S. aureus among medical personnel could influence the spreading of nosocomial infections mainly on ICU and Newborn Wards.