Introducing "Vascular Cell", an open access medical journal endorsed by
The Australasian Immunohistochemistry Society.

Quantitative Digital Pathology resources

	HER2 M-Scores in Gastric/Gastroesophageal Junction Adenocarcinomas: Comparison of Digital Image Analysis and Pathologist Interpretation
	Background: Approximately 20% of gastric and gastroesophageal junction (GEJ) adenocarcinomas are HER2 positive (3+ overexpression by immunohistochemistry [IHC] or gene amplification by in situ hybridization [ISH]). In the ToGA trial, the addition of trastuzumab was shown to prolong survival in patients with advanced gastric and GEJ carcinomas. Prior studies have examined HER2 IHC scoring using digital image analysis (DIA) and some have implemented H-scores in their evaluation. The M-score is a quantitative measure of membrane staining with a calculated range of 0 to 50. We investigated the potential utility of a commercially available image analysis platform (IAP) in determining M-scores for HER2 expression in gastric/GEJ adenocarcinomas.
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	Endometrial Endometrioid Carcinoma Metastases Show Decreased ER-Alpha and PR-A Expression Compared to Matched Primary Tumors
	Patients with endometrial endometrioid carcinoma (EEC) that present with advanced pri- mary disease and develop recurrences have a poor outcome. The phenotype of EEC metastases and recurrences is poorly studied. We evaluated the morphological features and ER-alpha/PRA/p53 immunohistochemical expression of a sample of 45 EEC metasta- ses compared to matched primary tumors. Additionally, we studied methylation levels of ER-alpha/PRA gene promoters. The distribution of histological FIGO grade was signifi- cantly different in metastases, which disclosed higher grade than primary tumors (p = 0.005).
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	Quantitative Image Analysis of Ki-67 Immunohistochemistry Compared with Manual Pathologist Analysis in Breast Cancer
	Image analysis (IA) is prevalent in pathology quantification. Determining Ki-67 percentage is complicated by tumor type, observer variability, bias and workload.
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