Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control

Abstract

BackgroundDigital image analysis (DIA) enables better reproducibility of immunohistochemistry (IHC) studies. Nevertheless, accuracy of the DIA methods needs to be ensured, demanding production of reference data sets. We have reported on methodology to calibrate DIA for Ki67 IHC in breast cancer tissue based on reference data obtained by stereology grid count. To produce the reference data more efficiently, we propose digital IHC wizard generating initial cell marks to be verified by experts.MethodsDigital images of proliferation marker Ki67 IHC from 158 patients (one tissue microarray spot per patient) with an invasive ductal carcinoma of the breast were used. Manual data (mD) were obtained by marking Ki67-positive and negative tumour cells, using a stereological method for 2D object enumeration. DIA was used as an initial step in stereology grid count to generate the digital data (dD) marks by Aperio Genie and Nuclear algorithms. The dD were collected into XML files from the DIA markup images and overlaid on the original spots along with the stereology grid. The expert correction of the dD marks resulted in corrected data (cD). The percentages of Ki67 positive tumour cells per spot in the mD, dD, and cD sets were compared by single linear regression analysis. Efficiency of cD production was estimated based on manual editing effort.ResultsThe percentage of Ki67-positive tumor cells was in very good agreement in the mD, dD, and cD sets: regression of cD from dD (R2=0.92) reflects the impact of the expert editing the dD as well as accuracy of the DIA used; regression of the cD from the mD (R2=0.94) represents the consistency of the DIA-assisted ground truth (cD) with the manual procedure. Nevertheless, the accuracy of detection of individual tumour cells was much lower: in average, 18 and 219 marks per spot were edited due to the Genie and Nuclear algorithm errors, respectively. The DIA-assisted cD production in our experiment saved approximately 2/3 of manual marking.ConclusionsDigital IHC wizard enabled DIA-assisted stereology to produce reference data in a consistent and efficient way. It can provide quality control measure for appraising accuracy of the DIA steps.

Construction and analysis of tissue microarrays in the era of digital pathology: a pilot study targeting CDX1 and CDX2 in a colon cancer cohort of 612 patients

“…The main limitation of this study is a lack of information regarding the method of DIA in the literature. Even amongst recent studies [10,14,15,24,[28][29][30][31][32][33][34][35][36] using this technique, only a few report details regarding settings and scientific troubleshooting [10,32,33]. Additionally, many studies condense the detailed data to again simplified values, which could have been gathered with eye-balling, or are partially hidden for license/patent processes of industrial-academic collaboration [15,30].…”

“…Evaluation of immunohistochemistry by digital image analysis (DIA) would further help to fast‐track the discovery of potential prognostic and predictive biomarkers, in addition to help streamline workflows and produce objective and reproducible biomarker data . The combined value of a DIA approach to TMAs has been underlined by works of many authors .…”

“…As of yet, there are few if any standards for the reporting of algorithms and settings, which may hinder cross‐comparison of results from different studies . The added value of DIA with regard to the objective quantification of the number of positive cells across various staining intensity ranges (and what defines these ranges), and the detection of intra‐tumoural heterogeneity in the context of a large prognostic TMA cohort, has not been explored.…”

Immediate post-interventional contrast-enhanced computed tomography overestimates hepatic microwave ablation – an in vivo animal study

“…A quantitative analysis was performed with an analysis software for histopathological images (Aperio GENIE Image Analysis Tool, Leica Biosystems Imaging Inc, DB Maarn, Netherlands). The software was trained to identify areas with similar histological patterns with respect to predefined cellular properties [15]. Results are presented as color-coded maps of each histological section (Figure 2(c)).…”

Comprehensive Immunohistochemistry: Digital, Analytical and Integrated

“…The amount of manual expert work needed on large images with a huge number of cells is a critical bottleneck in the adoption of editing-based approaches [24]. Several approaches have been proposed to decrease the expert workload [25,26,27]; however, the efficiency and integration of the tools requires further sophistication.…”