Investigation of fluorescence lifetime imaging for quantitative cervical cancer screening and diagnosis - Gu, Jun (2015)
To supplement the traditional histopathological examination of early cervical cancer, fluorescence lifetime imaging microscopy (FLIM) of H&E stained cervical tissue sections was investigated. Categories comprising normal, cervical intraepithelial neoplasia (CIN1, CIN2, CIN3), squamous cell carcinoma (SCC) and microinvasive were imaged and analyzed. Lifetime calculated from fluorescence emission decay in cervical epithelium region was used to correlate with tissue pathology. Mean and standard deviation of the characteristic fluorescence lifetime were used as feature vectors to feed into a neural network extreme learning machine (ELM) classifier for discrimination. An averaged sensitivity and specificity of 92.8% and 80.2%, respectively, were achieved when differentiating normal from precancerous (CIN1, CIN2, CIN3) samples. Discriminations between low-risk group (normal, CIN1) and high-risk group (CIN2, CIN3) were also conducted due to the clinical importance for treatment and a sensitivity of 85.0% and specificity of 87.6% were obtained. The results suggest that the proposed fluorescence lifetime imaging of H&E stained cervical tissue sections with the quantitative neural network ELM could be used to aid and supplement the traditional histopathological examinations.