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

Quantitative Digital Pathology resources

 
GenASIs HiPath as a recommended, cost-effective replacement product to the ACIS III imaging system, for HER2/neu IHC scoring in breast cancer

GenASIs HiPath as a recommended, cost-effective replacement product to the ACIS III imaging system, for HER2/neu IHC scoring in breast cancer

This white paper summarizes the results of scoring reproducibility of HER2/neu IHC expression, by two digital imaging platforms: (1) GenASIs HiPath (Applied Spectral Imaging – ASI); and (2) ACIS III (Dako-Agilent)
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QUANTITATIVE IMAGE ANALYSIS OF KI-67 IMMUNOHISTOCHEMISTRY COMPARED WITH MANUAL PATHOLOGIST ANALYSIS IN BREAST CANCER

QUANTITATIVE IMAGE ANALYSIS OF KI-67 IMMUNOHISTOCHEMISTRY COMPARED WITH MANUAL PATHOLOGIST ANALYSIS IN BREAST CANCER

Determining Ki-67 percentage in a nuclear IHC quantitative sample is complicated by tumor type, observer variability, staining intensity, bias and workload.
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HER2 M-Scores in Gastric/Gastroesophageal Junction Adenocarcinomas: Comparison of Digital Image Analysis and Pathologist Interpretation

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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AUTOMATED FISH - CLINICAL STUDY

AUTOMATED FISH – CLINICAL STUDY

A comparative study conducted at an independent clinical laboratory to evaluate the performance of ASI’s automated FISH scanning and analysis solution, GenASIsTM SpotScan, compared to unassisted manual analysis. The purpose of the study was to determine whether GenASIs SpotScan yields time saving benefits, while still maintaining concordance with manual analysis.
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Endometrial Endometrioid Carcinoma Metastases Show Decreased ER-Alpha and PR-A Expression Compared to Matched Primary Tumors

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

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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Quantitative Image Analysis of Ki-67 Immunohistochemistry
Compared with Manual Pathologist Analysis in Breast Cancer - POSTER

Quantitative Image Analysis of Ki-67 Immunohistochemistry
Compared with Manual Pathologist Analysis in Breast Cancer – POSTER

Quantitative Image Analysis of Ki-67 Immunohistochemistry
Compared with Manual Pathologist Analysis in Breast Cancer – POSTER
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