Publication: Multivariate discriminant analysis of normal, intraepithelial neoplasia and human papillomavirus
infection of the uterine cervix samples
Authors
Artacho-Perula, E. ; Roldan-Villalobos, R. ; Salas-Molina, J. ; Vaamonde-Lemos, R.
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Publisher
Murcia : F. Hernández
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DOI
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info:eu-repo/semantics/article
Description
Abstract
The present investigation studies the role of
multivariate statistical methods on quantitative
histopathological features of cells in uterine cervix
epithelium to discriminate between normal and abnormal
uterine cervix samples. 143 histological specimens were
included in the study involving normal cervix, cervical
intraepithelial neoplasia (CIN) lesions and cervical
human papillomavirus (HPV) infection with and without
CIN (condyloma-CIN and condyloma-NCIN
groups, respectively). Deep, middle and superficial
regions of the cervical squamous epithelium were
morphometrically analyzed. Identification of normal
cervix from pathological cases was highly achieved with
a specificity of 100%. The application of discriminant
statistical method within pathological specimens showed
an acceptable percentage of cases correctly classified;
thus, an efficiency of 83.0% and 74.6% was obtained in
order to discriminate within CIN and condyloma-CIN
grades respectively. These percentages increased when
differentiation between each grade of CIN versus
condyloma-CIN were considered, using only 1-3
morphometrical parameters. Our findings indicate that
the combination of nuclear and cytoplasmic quantitative
features, specially size parameters, permit a high correct
percentage classification of cervix samples. The
discrimination process was better when few diagnostic
categories were included; however, 100% specificity for
normal samples was always reached.
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