Abstract
Immunohistochemistry (IHC) assays play a central role in evaluating biomarker expression in tissue sections for diagnostic and research applications. Manual scoring of IHC images, which is the current standard of practice, is known to have several shortcomings in terms of reproducibility and scalability to large scale studies. Here, by using a digital image analysis-based approach, we introduce a new metric called the pixelwise H-score (pix H-score) that quantifies biomarker expression from whole-slide scanned IHC images. The pix H-score is an unsupervised algorithm that only requires the specification of intensity thresholds for the biomarker and the nuclear-counterstain channels. We present the detailed implementation of the pix H-score in two different whole-slide image analysis software packages Visiopharm and HALO. We consider three biomarkers P-cadherin, PD-L1, and 5T4, and show how the pix H-score exhibits tight concordance to multiple orthogonal measurements of biomarker abundance such as the biomarker mRNA transcript and the pathologist H-score. We also compare the pix H-score to existing automated image analysis algorithms and demonstrate that the pix H-score provides either comparable or significantly better performance over these methodologies. We also present results of an empirical resampling approach to assess the performance of the pix H-score in estimating biomarker abundance from select regions within the tumor tissue relative to the whole tumor resection. We anticipate that the new metric will be broadly applicable to quantify biomarker expression from a wide variety of IHC images. Moreover, these results underscore the benefit of digital image analysis-based approaches which offer an objective, reproducible, and highly scalable strategy to quantitatively analyze IHC images.
Highlights
Immunohistochemistry (IHC) is a core technology that is used to evaluate the spatial distribution and abundance of biomarkers at the protein level in tissue samples
(measured using qRT-PCR or NanoString analysis of Messenger RNA (mRNA) in adjacent serial sections) as orthogonal measurements of biomarker abundance, we demonstrate that the pix H-score is either comparable or superior to other Digital image analysis (DIA) endpoints in quantifying biomarker abundance in IHC images
Our analysis shows that the correlation coefficient between the pix H-score and either of the biomarker abundance endpoints is significantly higher than the correlation coefficient between DIA based H-scores and biomarker abundance endpoints
Summary
Immunohistochemistry (IHC) is a core technology that is used to evaluate the spatial distribution and abundance of biomarkers at the protein level in tissue samples. Visual quantitative scoring of IHC images is not routinely performed due to several shortcomings. Visual quantitative scores are subjective and often have a limited dynamic range due to their categorical nature (e.g. manual scores of 0, 1+, 2+, and 3+). They may not have the granularity to adequately capture biomarker expression from an IHC slide [2, 3]. While concordance in visual quantitative scoring can be improved by the development of standardized scoring guidelines and extensive training [9, 10], the labor-intensive aspect and the limited dynamic range still remain as major impediments to the widespread use of visual quantitative scoring of IHC images
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