ArticleHistochemistry and cell biology2015
Image analysis of immunohistochemistry is superior to visual scoring as shown for patient outcome of esophageal adenocarcinoma.
Article in Histochemistry and cell biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.
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- Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma.NPJ precision oncology · 2023Article
- Machine Learning for Digital Scoring of PRMT6 in Immunohistochemical Labeled Lung Cancer.Cancers · 2023Article
- Patterns of Carbon-Bound Exogenous Compounds Impact Disease Pathophysiology in Lung Cancer Subtypes in Different Ways.ACS nano · 2023Article
- Hypoxic pre-conditioned adipose-derived stem/progenitor cells embedded in fibrin conduits promote peripheral nerve regeneration in a sciatic nerve graft model.Neural regeneration research · 2023Article
- In Situ Metabolomics of Cortisol-Producing Adenomas.Clinical chemistry · 2023Article
- TSC22D4 interacts with Akt1 to regulate glucose metabolism.Science advances · 2022Article
- Comparison of manual and automated digital image analysis systems for quantification of cellular protein expression.Histology and histopathology · 2022Article
- Reliability of CD44, CD24, and ALDH1A1 immunohistochemical staining: Pathologist assessment compared to quantitative image analysis.Frontiers in medicine · 2022Article
- Article
- Reliability of a computational platform as a surrogate for manually interpreted immunohistochemical markers in breast tumor tissue microarrays.Cancer epidemiology · 2021Article
- Digital scoring of EpCAM and slug expression as prognostic markers in head and neck squamous cell carcinomas.Molecular oncology · 2021Article
- Lipocalin 13 enhances insulin secretion but is dispensable for systemic metabolic control.Life science alliance · 2021Article
- Identification and characterization of distinct brown adipocyte subtypes in C57BL/6J mice.Life science alliance · 2021Article
- De novo discovery of metabolic heterogeneity with immunophenotype-guided imaging mass spectrometry.Molecular metabolism · 2020Article
- Digital image analysis of multiplex fluorescence IHC in colorectal cancer recognizes the prognostic value of CDX2 and its negative correlation with SOX2.Laboratory investigation; a journal of technical methods and pathology · 2020Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantification of protein expression based on immunohistochemistry (IHC) is an important step in clinical diagnoses and translational tissue-based research. Manual scoring systems are used in order to evaluate protein expression based on staining intensities and distribution patterns. However, visual scoring remains an inherently subjective approach. The aim of our study was to explore whether digital image analysis proves to be an alternative or even superior tool to quantify expression of membrane-bound proteins. We analyzed five membrane-binding biomarkers (HER2, EGFR, pEGFR, β-catenin, and E-cadherin) and performed IHC on tumor tissue microarrays from 153 esophageal adenocarcinomas patients from a single center study. The tissue cores were scored visually applying an established routine scoring system as well as by using digital image analysis obtaining a continuous spectrum of average staining intensity. Subsequently, we compared both assessments by survival analysis as an end point. There were no significant correlations with patient survival using visual scoring of β-catenin, E-cadherin, pEGFR, or HER2. In contrast, the results for digital image analysis approach indicated that there were significant associations with disease-free survival for β-catenin, E-cadherin, pEGFR, and HER2 (P = 0.0125, P = 0.0014, P = 0.0299, and P = 0.0096, respectively). For EGFR, there was a greater association with patient survival when digital image analysis was used compared to when visual scoring was (visual: P = 0.0045, image analysis: P < 0.0001). The results of this study indicated that digital image analysis was superior to visual scoring. Digital image analysis is more sensitive and, therefore, better able to detect biological differences within the tissues with greater accuracy. This increased sensitivity improves the quality of quantification.
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