title: A robust automated measure of average antibody staining in immunohistochemistry images.
abstract: Identifying and scoring cancer markers plays a key role in oncology, helping to characterize the tumor and predict the clinical course of the disease. The current method for scoring immunohistochemistry (IHC) slides is labor intensive and has inherent issues of quantitation. Although multiple attempts have been made to automate IHC scoring in the past decade, a major limitation in these efforts has been the setting of the threshold for positive staining. In this report, we propose the use of an averaged threshold measure (ATM) score that allows for automatic threshold setting. The ATM is a single multiplicative measure that includes both the proportion and intensity scores. It can be readily automated to allow for large-scale processing, and it is applicable in situations in which individual cells are hard to distinguish. The ATM scoring method was validated by applying it to simulated images, to a sequence of images from the same tumor, and to tumors from different patient biopsies that showed a broad range of staining patterns. Comparison between the ATM score and manual scoring by an expert pathologist showed that both methods resulted in essentially identical scores when applied to these patient biopsies. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials.
authors.affiliation: Department of Statistics, University College Cork, Cork, Ireland. kingshuk@ucc.ie
authors.forename: Kingshuk Roy
authors.initials: KR
authors.lastname: Choudhury
authors.forename: Kevin J
authors.initials: KJ
authors.lastname: Yagle
authors.forename: Paul E
authors.initials: PE
authors.lastname: Swanson
authors.forename: Kenneth A
authors.initials: KA
authors.lastname: Krohn
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Rajendran
mesh_terms: D000906:Antibodies / Q000276:immunology / Q000378:metabolism*; D001331:Automation; D014408:Biomarkers, Tumor / Q000276:immunology / Q000378:metabolism; D006801:Humans; D051793:Hypoxia-Inducible Factor 1 / Q000276:immunology / Q000378:metabolism; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry / Q000379:methods*; D057054:Molecular Imaging / Q000379:methods*; D013194:Staining and Labeling
chemical_list: D000906:Antibodies; D014408:Biomarkers, Tumor; D051793:Hypoxia-Inducible Factor 1
references.citation: Pathology. 2007 Feb;39(1):97-111
references.pmid: 17365826
references.citation: Nat Med. 1998 Jul;4(7):844-7
references.pmid: 9662379
references.citation: J Clin Oncol. 2006 Feb 20;24(6):995-1007
references.pmid: 16418498
references.citation: Breast Cancer. 2004;11(4):334-8
references.pmid: 15604987
references.citation: J Natl Cancer Inst. 1994 Jun 1;86(11):829-35
references.pmid: 8182763
references.citation: J Histochem Cytochem. 1981 Apr;29(4):577-80
references.pmid: 6166661
references.citation: Clin Cancer Res. 2006 Sep 1;12(17):5005-6
references.pmid: 16951212
references.citation: Oncology. 2001;61 Suppl 2:22-30
references.pmid: 11694784
references.citation: World J Urol. 2007 Dec;25(6):557-62
references.pmid: 17690889
references.citation: Pathol Int. 2003 Oct;53(10):693-9
references.pmid: 14516320
references.citation: IEEE Trans Med Imaging. 1982;1(2):113-22
references.pmid: 18238264
references.citation: Mod Pathol. 1998 Feb;11(2):155-68
references.pmid: 9504686
references.citation: J Clin Oncol. 1998 Feb;16(2):793-5
references.pmid: 9469371
references.citation: J Clin Oncol. 1999 May;17(5):1474-81
references.pmid: 10334533