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Proceedings Paper

Confocal fluorescence microscopy for detection of cervical preneoplastic lesions
Author(s): Fahime Sheikhzadeh; Rabab K. Ward; Anita Carraro; Zhaoyang Chen; Dirk van Niekerk; Calum MacAulay; Michele Follen; Pierre Lane; Martial Guillaud
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Paper Abstract

We examined and established the potential of ex-vivo confocal fluorescence microscopy for differentiating between normal cervical tissue, low grade Cervical Intraepithelial Neoplasia (CIN1), and high grade CIN (CIN2 and CIN3). Our objectives were to i) use Quantitative Tissue Phenotype (QTP) analysis to quantify nuclear and cellular morphology and tissue architecture in confocal microscopic images of fresh cervical biopsies and ii) determine the accuracy of high grade CIN detection via confocal microscopy. Cervical biopsy specimens of colposcopically normal and abnormal tissues obtained from 15 patients were evaluated by confocal fluorescence microscopy. Confocal images were analyzed and about 200 morphological and architectural features were calculated at the nuclear, cellular, and tissue level. For the purpose of this study, we used four features to delineate disease grade including nuclear size, cell density, estimated nuclear-cytoplasmic (ENC) ratio, and the average of three nearest Delaunay neighbors distance (3NDND). Our preliminary results showed ENC ratio and 3NDND correlated well with histopathological diagnosis. The Spearman correlation coefficient between each of these two features and the histopathological diagnosis was higher than the correlation coefficient between colposcopic appearance and histopathological diagnosis. Sensitivity and specificity of ENC ratio for detecting high grade CIN were both equal to 100%. QTP analysis of fluorescence confocal images shows the potential to discriminate high grade CIN from low grade CIN and normal tissues. This approach could be used to help clinicians identify HGSILs in clinical settings.

Paper Details

Date Published: 27 April 2015
PDF: 6 pages
Proc. SPIE 9420, Medical Imaging 2015: Digital Pathology, 942009 (27 April 2015); doi: 10.1117/12.2077268
Show Author Affiliations
Fahime Sheikhzadeh, The BC Cancer Agency Research Ctr. (Canada)
The Univ. of British Columbia (Canada)
Rabab K. Ward, The Univ. of British Columbia (Canada)
Anita Carraro, The BC Cancer Agency Research Ctr. (Canada)
Zhaoyang Chen, The BC Cancer Agency Research Ctr.. (Canada)
Dirk van Niekerk, British Columbia Cancer Agency (Canada)
Calum MacAulay, The BC Cancer Agency Research Ctr. (Canada)
Michele Follen, Texas Tech Univ. Health Sciences Ctr. (United States)
Pierre Lane, The BC Cancer Agency Research Ctr. (Canada)
The Univ. of British Columbia (Canada)
Martial Guillaud, The BC Cancer Agency Research Ctr. (Canada)

Published in SPIE Proceedings Vol. 9420:
Medical Imaging 2015: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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