Title :
Diagnosis of Human Bladder Cancer Cells at Different Stages Using Multispectral Imaging Microscopy
Author :
Chun-Ping Jen ; Ching-Te Huang ; Yung-Sheng Chen ; Chie-Tong Kuo ; Hsiang-Chen Wang
Author_Institution :
Dept. of Mech. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
Abstract :
Bladder cancer presents a spectrum of different diatheses. A precise assessment for individualized treatment depends on the accuracy of the initial diagnosis. Detection relies on comprehensive and accurate white light cystoscopy. White light cystoscopy has limitations in addition to its invasive nature and the potential risks related to the method. These limitations include difficulties in flat lesion detection, precise tumor delineation to enable complete resection, inflammation and malignancy differentiation, and grade and stage determination. The resolution of these problems depends on the surgeon´s ability and experience with available technology for visualization and resection. In this study, we used multispectral imaging technology combined with phase contrast microscopy to analyze bladder cancer cells (BCCs) at various stages using a single-cell array chip. We found from the spectral characteristics of single cell that the cell spectra at the different cancer stages demonstrate a change in the cell´s composition. We cultured 419 normal and diseased bladder cells. We used principal component analysis and a principal component score map to distinguish the different cancer stages. Diagnosis sensitivity and specificity of this method were 85.7% and 90.2% in 119 stage 0 (normal) cells, 84.3% and 90.8% in 79 stage 2 cancer cells, 87.6% and 92.4% in 151 stage 3 BCCs, and 85.3% and 91.2% in 70 stage 4 BCCs, respectively.
Keywords :
biomedical optical imaging; cancer; cellular biophysics; optical microscopy; patient treatment; principal component analysis; tumours; cell composition; diatheses; flat lesion detection; human bladder cancer cell diagnosis; multispectral imaging microscopy; patient treatment; phase contrast microscopy; principal component analysis; principal component score map; single-cell array chip; tumor delineation; white light cystoscopy; Arrays; Bladder; Cancer; Gray-scale; Image color analysis; Microscopy; Principal component analysis; Biomedical optical imaging; Image reconstruction techniques; cancer cell detection; multispectral imaging; multispectral imaging microscopy;
Journal_Title :
Selected Topics in Quantum Electronics, IEEE Journal of
DOI :
10.1109/JSTQE.2013.2279804