Commentary

Abstract

Historically, pathologists perform manual evaluation of H&E-or immunohistochemically-stained slides, which can be subjective, inconsistent, and, at best, semiquantitative. As the complexity of staining and demand for increased precision of manual evaluation increase, the pathologist's assessment will include automated analyses (i.e., ''digital pathology'') to increase the accuracy, efficiency, and speed of diagnosis and hypothesis testing and as an important biomedical research and diagnostic tool. This commentary introduces the many roles for pathologists in designing and conducting high-throughput digital image analysis. Pathology review is central to the entire course of a digital pathology study, including experimental design, sample quality verification, specimen annotation, analytical algorithm development, and report preparation. The pathologist performs these roles by reviewing work undertaken by technicians and scientists with training and expertise in image analysis instruments and software. These roles require regular, face-to-face interactions between team members and the lead pathologist. Traditional pathology training is suitable preparation for entry-level participation on image analysis teams. The future of pathology is very exciting, with the expanding utilization of digital image analysis set to expand pathology roles in research and drug development with increasing and new career opportunities for pathologists.

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

“…[3] However, there are multiple advantages of transitioning to a digital workflow, including ease of slides and cases sharing (consulting with other pathologists, or collaborating within interdisciplinary research teams), standardization of teaching, organization of archived digitized slides, and extraction of complex data in a highly reproducible fashion via specialized software. [4] The pathologist plays a key role both in the process of slide digitization and in the subsequent data generation via the use of appropriate image analysis algorithms.…”

“…Utilizing digital image analysis tools, the most commonly used categories of measurements that can be extracted from digitized tissue slides are area based, cell based, and measurements pertaining to objects in the tissue aside from cells. [4]…”

An Image Analysis Solution For Quantification and Determination of Immunohistochemistry Staining Reproducibility

“…In addition, automated analysis diminished (though did not fully replace) the need for skilled histopathology support to provide QA for IHC staining runs. 22 , 23 Finally, automated image analysis afforded a more sensitive means for detecting nuanced changes in IHC staining, especially at low staining levels at which the human eye tends to have difficulty in discriminating subtle variations in color intensity. 24 , 25 …”

Quantitative analysis of histopathological findings using image processing software

“…The convenience of automated quantification of a pathological tissue image is currently under discussion 5 , 17 , 18 . A means of automated clinical diagnosis of cancer has been developed 19 , 20 .…”