Automated image analysis in histopathology: a valuable tool in medical diagnostics

Abstract

Virtual pathology, the process of assessing digital images of histological slides, is gaining momentum in today’s laboratory environment. Indeed, digital image acquisition systems are becoming commonplace, and associated image analysis solutions are viewed by most as the next critical step in automated histological analysis. Here, we document the advances in the technology, with reference to past and current techniques in histological assessment. In addition, the demand for these technologies is analyzed with major players profiled. As there are several image analysis software programs focusing on the quantification of immunohistochemical staining, particular attention is paid to this application in this review. Oncology has been a primary target area for these approaches, with example studies in this therapeutic area being covered here. Toxicology-based image analysis solutions are also profiled as these are steadily increasing in popularity, especially within the pharmaceutical industry. Reinforced by the phenomenal growth of the virtual pathology field, it is envisioned that the market for automated image analysis tools will greatly expand over the next 10 years.

Keywords::

• algorithm
• histology
• histopathology
• image analysis
• immunohistochemistry
• oncology
• slide scanning
• toxicology
• virtual pathology

Acknowledgements

We would like to thank all other members of the PredTox group (www.innomed-predtox.com). We would also like to acknowledge those companies who contributed figures for this article. All companies mentioned were contacted for feedback regarding their individual sections.

Financial & competing interests disclosure

WM Gallagher is on the Scientific Advisory Board of SlidePath and holds shares in this company. WM Gallagher and S Penney are co-directors of OncoMark (www.oncomark.com), an emerging enterprise which offers services in digital slide scanning and tissue microarray construction, as well as carrying out product development in automated image analysis approaches. Funding is acknowledged from the EU FP6 Integrated Project, InnoMed, as well as Enterprise Ireland and the Health Research Board of Ireland. The UCD Conway Institute and the Proteome Research Centre is funded by the Programme for Research in Third Level Institutions (PRTLI), as administered by the Higher Education Authority (HEA) of Ireland. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.