Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association

Abstract

The advent of whole-slide imaging in digital pathology has brought about the advancement of computer-aided examination of tissue via digital image analysis. Digitized slides can now be easily annotated and analyzed via a variety of algorithms. This study reviews the fundamentals of tissue image analysis and aims to provide pathologists with basic information regarding the features, applications, and general workflow of these new tools. The review gives an overview of the basic categories of software solutions available, potential analysis strategies, technical considerations, and general algorithm readouts. Advantages and limitations of tissue image analysis are discussed, and emerging concepts, such as artificial intelligence and machine learning, are introduced. Finally, examples of how digital image analysis tools are currently being used in diagnostic laboratories, translational research, and drug development are discussed.

Procedural Requirements and Recommendations for Multiplex Immunofluorescence Tyramide Signal Amplification Assays to Support Translational Oncology Studies

“…Using these scanners, we can analyze whole-slide images or specific ROIs. Confining the image analysis region to one or more smaller ROIs is often necessary to create an accurate and computationally viable method for tissue image analysis (Figure 4) [40]. Because the strategy of the analysis must be specified according to the aims of the study, the ROIs must be selected at the beginning of the project.…”

“…The algorithm then analyzes all tissues included in the inclusion annotation of the ROIs. Areas of disinterest, such as necrosis, tissue artifacts, and staining artifacts, must be excluded with the disinterest tool [40].…”

Online narrative guides for illuminating tissue atlas data and digital pathology images

“…Genome browsers are similar: they do not perform alignment and data analysis, but they make it possible to interact with data effectively. OpenSeadragon has been used previously for displaying H&E images 37 , but in Minerva it is paired with narrative features, a lightweight implementation, the ability to accommodate both bright-field and multiplexed immunofluorescence images, and easy deployment.…”

“…A range of other software is available for static or partially interactive visualization of H&E and IHC images in a Web browser, including caMicroscope 55 which is used to organize IHC and H&E images for The Cancer Genome Atlas (TCGA) 22 , the Cancer Imaging Archive (TCIA), 56 Digital Slide Archive 32 , PathPresenter 57 , and Aperio 58 (Figure 2b). Interested readers are referred to a recent White Paper from the Digital Pathology Association that discusses tools being developed to view bright-field digital pathology data 37 . However, such H&E-IHC viewers are not generally designed to display multichannel images and integrate different types of omic data.…”

Introduction to digital pathology and computer-aided pathology

“…However, manual annotation is costly and timeconsuming because it must be performed by skilled technicians with confirmation and approval by a pathologist. Various tools have been developed to overcome the shortcomings of manual annotations, including automated image annotation and predeveloped commercial software packages [42]. Because these tools may compromise accuracy, a pathologist must confirm the accuracy of automated annotations.…”