Discrimination of lung cancer and adjacent normal tissues based on permittivity by optimized probabilistic neural network / 南方医科大学学报

OBJECTIVE@#To propose a probabilistic neural network classification method optimized by simulated annealing algorithm (SA-PNN) to discriminate lung cancer and adjacent normal tissues based on permittivity.@*METHODS@#The permittivity of lung tumors and the adjacent normal tissues was measured by an open-ended coaxial probe, and the statistical dependency (SD) algorithm was used for frequency screening.The permittivity associated with the selected frequency points was taken as the characteristic variable, and SA-PNN was used to discriminate lung cancer and the adjacent normal tissues.@*RESULTS@#Three frequency points, namely 984 MHz, 2724 MHz and 2723 MHz, were selected by SD algorithm.SA-PNN was used to discriminate 200 samples with the permittivity at the 3 frequency points as the characteristic variable.After 10-fold cross-validation, the final discrimination accuracy was 92.50%, the sensitivity was 90.65%, and the specificity was 94.62%.@*CONCLUSIONS@#Compared with the traditional probabilistic neural network, BP neural network, RBF neural network and the classification discriminant analysis function (Classify) in MATLAB, the proposed SA-PNN has higher accuracy, sensitivity and specificity for discriminating lung cancer and the adjacent normal tissues based on permittivity.

Correlation of caveolin-1 expression with microlymphatic vessel density in colorectal adenocarcinoma tissues and its correlation with prognosis

Objective:To study the expression of caveolin-1 in colorectal adenocarcinoma tissues and its correlation with microlymphatic vessel density (LMVD), and to investigate the clinical pathological prognostic significance of caveolin-1 and LMVD in patients with colorectal cancer.Methods:The expression of caveolin-1 and LMVD in 45 specimens of normal colorectal tissues, and 90 specimens of colorectal adenocarcinoma tissues were detected by immunohistochemistry technique. The correlation between their expression and the clinicopathologic features was analyzed. Muhivariable Cox regression was used to analyze the association between the laboratory indices and overall survival time.Results:The positive rates of caveolin-1 in colorectal adenocarcinoma tissues were significantly higher than those in normal colorectal tissues (P<0.01). LMVD in colorectal adenocarcinoma tissues were significantly higher than those in normal colorectal tissues (P<0.01). Mean LMVD in group with caveolin-1 positive was significantly higher than in that with caveolin-1 negative. The median survival time was 26.7 months. Cox regression analysis showed that the caveolin-1 expression, invation depth, lymph nodemetastasis, TNM stage, liver metastasis and LMVD were independent risk factors of overall survival time of patients with colorectal carcinoma. Conclusions:Caveolin-1 may contribute to the lymphangiogenesis in the tumor. During the occurrence and development of colorectal adenocarcinoma, there is a close relationship between the expression of caveolin-1 and lymphatic microvessel of tumor. Caveolin-1 expression and microlymphatic vessel density are significant prognostic value of colorectal carcinoma.