RT Journal Article
SR Electronic
T1 Integration of computer-aided automated analysis algorithms in the development and validation of immunohistochemistry biomarkers in ovarian cancer
JF Journal of Clinical Pathology
JO J Clin Pathol
FD BMJ Publishing Group Ltd and Association of Clinical Pathologists
SP 469
OP 474
DO 10.1136/jclinpath-2020-207081
VO 74
IS 7
A1 Gentles, Lucy
A1 Howarth, Rachel
A1 Lee, Won Ji
A1 Sharma-Saha, Sweta
A1 Ralte, Angela
A1 Curtin, Nicola
A1 Drew, Yvette
A1 O'Donnell, Rachel Louise
YR 2021
UL http://jcp.bmj.com/content/74/7/469.abstract
AB In an era when immunohistochemistry (IHC) is increasingly depended on for histological subtyping, and IHC-determined biomarker informing rapid treatment choices is on the horizon; reproducible, quantifiable techniques are required. This study aimed to compare automated IHC scoring to quantify 6 DNA damage response protein markers using a tissue microarray of 66 ovarian cancer samples. Accuracy of quantification was compared between manual H-score and computer-aided quantification using Aperio ImageScope with and without a tissue classification algorithm. High levels of interobserver variation was seen with manual scoring. With automated methods, inclusion of the tissue classifier mask resulted in greater accuracy within carcinomatous areas and an overall increase in H-score of a median of 11.5% (0%–18%). Without the classifier, the score was underestimated by a median of 10.5 (5.2–25.6). Automated methods are reliable and superior to manual scoring. Fixed algorithms offer the reproducibility needed for high-throughout clinical applications.