St Andrews Research Repository

St Andrews University Home
View Item 
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.

Proliferating cell nuclear antigen (PCNA) allows the automatic identification of follicles in microscopic images of human ovarian tissue

Thumbnail
View/Open
Kelsey_2010_PLMI_Proliferating.pdf (1.513Mb)
Date
24/07/2010
Author
Kelsey, Thomas William
Caserta, B
Castillo, L
Wallace, W H B
Coppola, F
Funder
EPSRC
Grant ID
EP/H004092/1
Keywords
Histology
Biological clock
Ovarian reserve
Immunohistochemistry
Feature detection
R Medicine
Metadata
Show full item record
Altmetrics Handle Statistics
Altmetrics DOI Statistics
Abstract
Background: Human ovarian reserve is defined by the population of nongrowing follicles (NGFs) in the ovary. Direct estimation of ovarian reserve involves the identification of NGFs in prepared ovarian tissue. Previous studies involving human tissue have used hematoxylin and eosin (HE) stain, with NGF populations estimated by human examination either of tissue under a microscope, or of images taken of this tissue. Methods: In this study we replaced HE with proliferating cell nuclear antigen (PCNA), and automated the identification and enumeration of NGFs that appear in the resulting microscopic images. We compared the automated estimates to those obtained by human experts, with the “gold standard” taken to be the average of the conservative and liberal estimates by three human experts. Results: The automated estimates were within 10% of the “gold standard”, for images at both 100× and 200× magnifications. Automated analysis took longer than human analysis for several hundred images, not allowing for breaks from analysis needed by humans. Conclusion: Our results both replicate and improve on those of previous studies involving rodent ovaries, and demonstrate the viability of large-scale studies of human ovarian reserve using a combination of immunohistochemistry and computational image analysis techniques.
Citation
Kelsey , T W , Caserta , B , Castillo , L , Wallace , W H B & Coppola , F 2010 , ' Proliferating cell nuclear antigen (PCNA) allows the automatic identification of follicles in microscopic images of human ovarian tissue ' , Journal of Pathology and Laboratory Medicine International , vol. 2010 , no. 2 , pp. 99-105 . https://doi.org/10.2147/PLMI.S11116
Publication
Journal of Pathology and Laboratory Medicine International
Status
Peer reviewed
DOI
https://doi.org/10.2147/PLMI.S11116
Type
Journal article
Rights
© 2010 Kelsey et al, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution - Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/).
Description
TWK is supported by EPSRC grants EP/CS23229/1 and EP/H004092/1.
Collections
  • University of St Andrews Research
URL
http://www.dovepress.com/articles.php?article_id=4986
URI
http://hdl.handle.net/10023/4961

Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

Advanced Search

Browse

All of RepositoryCommunities & CollectionsBy Issue DateNamesTitlesSubjectsClassificationTypeFunderThis CollectionBy Issue DateNamesTitlesSubjectsClassificationTypeFunder

My Account

Login

Open Access

To find out how you can benefit from open access to research, see our library web pages and Open Access blog. For open access help contact: openaccess@st-andrews.ac.uk.

Accessibility

Read our Accessibility statement.

How to submit research papers

The full text of research papers can be submitted to the repository via Pure, the University's research information system. For help see our guide: How to deposit in Pure.

Electronic thesis deposit

Help with deposit.

Repository help

For repository help contact: Digital-Repository@st-andrews.ac.uk.

Give Feedback

Cookie policy

This site may use cookies. Please see Terms and Conditions.

Usage statistics

COUNTER-compliant statistics on downloads from the repository are available from the IRUS-UK Service. Contact us for information.

© University of St Andrews Library

University of St Andrews is a charity registered in Scotland, No SC013532.

  • Facebook
  • Twitter