Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring

被引:337
作者
Rizzardi, Anthony E. [1 ]
Johnson, Arthur T. [1 ]
Vogel, Rachel Isaksson [2 ]
Pambuccian, Stefan E. [1 ]
Henriksen, Jonathan [1 ,3 ]
Skubitz, Amy P. N. [1 ,3 ]
Metzger, Gregory J. [4 ]
Schmechel, Stephen C. [1 ,3 ]
机构
[1] Univ Minnesota, Dept Lab Med & Pathol, Minneapolis, MN 55455 USA
[2] Univ Minnesota, Masonic Canc Ctr, Biostat & Bioinformat Core, Minneapolis, MN 55455 USA
[3] Univ Minnesota, BioNet, Minneapolis, MN 55455 USA
[4] Univ Minnesota, Dept Radiol, Minneapolis, MN 55455 USA
关键词
Annotation; Color deconvolution; Digital pathology; Immunohistochemistry; Intensity; Quantification; Software; IN-SITU HYBRIDIZATION; CANCER TISSUE MICROARRAYS; B-CELL LYMPHOMA; GENE-EXPRESSION; INTEROBSERVER REPRODUCIBILITY; BREAST; VALIDATION; HER2; ESTROGEN; QUANTIFICATION;
D O I
10.1186/1746-1596-7-42
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
Immunohistochemical (IHC) assays performed on formalin-fixed paraffin-embedded (FFPE) tissue sections traditionally have been semi-quantified by pathologist visual scoring of staining. IHC is useful for validating biomarkers discovered through genomics methods as large clinical repositories of FFPE specimens support the construction of tissue microarrays (TMAs) for high throughput studies. Due to the ubiquitous availability of IHC techniques in clinical laboratories, validated IHC biomarkers may be translated readily into clinical use. However, the method of pathologist semi-quantification is costly, inherently subjective, and produces ordinal rather than continuous variable data. Computer-aided analysis of digitized whole slide images may overcome these limitations. Using TMAs representing 215 ovarian serous carcinoma specimens stained for S100A1, we assessed the degree to which data obtained using computer-aided methods correlated with data obtained by pathologist visual scoring. To evaluate computer-aided image classification, IHC staining within pathologist annotated and software-classified areas of carcinoma were compared for each case. Two metrics for IHC staining were used: the percentage of carcinoma with S100A1 staining (%Pos), and the product of the staining intensity (optical density [ OD] of staining) multiplied by the percentage of carcinoma with S100A1 staining (OD*%Pos). A comparison of the IHC staining data obtained from manual annotations and software-derived annotations showed strong agreement, indicating that software efficiently classifies carcinomatous areas within IHC slide images. Comparisons of IHC intensity data derived using pixel analysis software versus pathologist visual scoring demonstrated high Spearman correlations of 0.88 for %Pos (p < 0.0001) and 0.90 for OD*%Pos (p < 0.0001). This study demonstrated that computer-aided methods to classify image areas of interest (e.g., carcinomatous areas of tissue specimens) and quantify IHC staining intensity within those areas can produce highly similar data to visual evaluation by a pathologist.
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页数:10
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