Digital pathology, what is the future?

Digital pathology (DP) is based on converting stained tissue sections, laid onto a glass slide, into a digital image through a scanner. It allows the pathologist to assess a histological sample using a computer workstation instead of a conventional microscope. The pathologist can navigate across the virtual slide at any chosen magnification. The quality of the DP images has improved considerably in the last few years and their resolution is now very close to that obtained by routine diagnostic microscopes at standard magnifications. Advantages of DP include full section low magnification “bird’s-eye” view, comparison of different tissue sections on the same screen (particularly helpful in evaluating interval changes in samples taken at different time, or different stains from the same sample), on-screen measurement tools for tumour size and clearance measurements and direct connectivity to image analysis software.1Bueno G. Fernández-Carrobles M.M. Deniz O. García-Rojo M. New trends of emerging technologies in digital pathology.Pathobiol J Immunopathol Mol Cell Biol. 2016; 83: 61-69https://doi.org/10.1159/000443482Crossref Scopus (48) Google Scholar, 2Saco A. Ramírez J. Rakislova N. Mira A. Ordi J. Validation of whole-slide imaging for histolopathogical diagnosis: current state.Pathobiol J Immunopathol Mol Cell Biol. 2016; 83: 89-98https://doi.org/10.1159/000442823Crossref Scopus (31) Google Scholar The recent review by Williams and colleagues makes the case for implementing DP for clinical diagnostic use in response to the continuous increase in histopathology workload, both with respect to volume and complexity, allowing off-site diagnosis for primary interpretation, second opinion, and intra-operative frozen sections.[3]Williams B.J. Bottoms D. Treanor D. Future-proofing pathology: the case for clinical adoption of digital pathology.J Clin Pathol. 2017; https://doi.org/10.1136/jclinpath-2017-204644Crossref Scopus (68) Google Scholar Incorporating DP into clinical practice may be a way to standardize histological diagnosis by reducing interobserver subjectivity, and to provide population-based repositories including annotated histological images along with clinical, molecular and radiologic data, which will facilitate multidisciplinary team meetings. Accordingly, clinical applications have been implemented in various fields including breast, skin, and gastro-intestinal histopathology.[2]Saco A. Ramírez J. Rakislova N. Mira A. Ordi J. Validation of whole-slide imaging for histolopathogical diagnosis: current state.Pathobiol J Immunopathol Mol Cell Biol. 2016; 83: 89-98https://doi.org/10.1159/000442823Crossref Scopus (31) Google Scholar Lastly, DP is a powerful teaching tool allowing simultaneous viewing and discussion of the same image by multiple students using conventional electronic devices and a standard internet access.[4]Saco A. Bombi J.A. Garcia A. Ramírez J. Ordi J. Current status of whole-slide imaging in education.Pathobiology. 2016; 83: 79-88https://doi.org/10.1159/000442391Crossref PubMed Scopus (46) Google Scholar DP offers the opportunity to apply image analysis to whole tissue sections, a major advance from the rather cumbersome and limited single field image analysis of conventional microscopy. This is of particular value when using image analysis to assess liver fibrosis, a key element for staging chronic liver diseases. The measurement of the area occupied by collagen (stained with the Picrosirius red method) as a proportion of the liver biopsy core section surface area (Collagen Proportionate Area, CPA), has been shown to correlate with semi-quantitative fibrosis scores, and predict outcomes in patients with chronic hepatitis and cirrhosis.5Calvaruso V. Burroughs A.K. Standish R. Manousou P. Grillo F. Leandro G. et al.Computer-assisted image analysis of liver collagen: relationship to Ishak scoring and hepatic venous pressure gradient.Hepatol Baltim Md. 2009; 49: 1236-1244https://doi.org/10.1002/hep.22745Crossref PubMed Scopus (217) Google Scholar, 6Tsochatzis E. Bruno S. Isgro G. Hall A. Theocharidou E. Manousou P. et al.Collagen proportionate area is superior to other histological methods for sub-classifying cirrhosis and determining prognosis.J Hepatol. 2014; 60: 948-954https://doi.org/10.1016/j.jhep.2013.12.023Abstract Full Text Full Text PDF PubMed Scopus (101) Google Scholar However, CPA measurement does not take into account the lobular architectural changes related to vascular compromise and structural remodelling which accompany fibrosis and require the interpretation of a pathologist.[7]Stueck A.E. Wanless I.R. Hepatocyte buds derived from progenitor cells repopulate regions of parenchymal extinction in human cirrhosis: clinical observations in hepatology.Hepatology. 2015; 61: 1696-1707https://doi.org/10.1002/hep.27706Crossref PubMed Scopus (69) Google Scholar Future developments in DP based liver fibrosis image analysis include the application of techniques such as second harmonic generation/two photon excitation fluorescence (SHG/TPEF). This method provides a qFibrosis value based on identification and quantification of main collagen patterns (portal, septal, and fibrillary collagen), and is based on a staining-free approach obviating the variability related to the staining process. Collagen quantification using SHG/TPEF in experimental models of liver fibrosis and human liver samples from patients with chronic hepatitis B infection showed excellent correlations with Metavir and Ishak scores, and demonstrated superior performance to CPA measurement.8Wang T.-H. Chen T.-C. Teng X. Liang K.-H. Yeh C.-T. Automated biphasic morphological assessment of hepatitis B-related liver fibrosis using second harmonic generation microscopy.Sci Rep. 2015; 5https://doi.org/10.1038/srep12962Crossref Scopus (29) Google Scholar, 9Xu S. Wang Y. Tai D.C.S. Wang S. Cheng C.L. Peng Q. et al.qFibrosis: a fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients.J Hepatol. 2014; 61: 260-269https://doi.org/10.1016/j.jhep.2014.02.015Abstract Full Text Full Text PDF PubMed Scopus (104) Google Scholar Interestingly, further development of this technology may allow the quantification of additional histological features such as steatosis, apoptosis, and hepatocyte ballooning, which may be of potential significance in non-alcoholic fatty liver diseases. The combination of DP with techniques such as multiplex quantum dot staining and image analysis allows the evaluation of multiple cell populations on the same section, a major step forward from conventional single stain methods on sequential tissue sections.[10]Isse K. Lesniak A. Grama K. Maier J. Specht S. Castillo-Rama M. et al.Preexisting epithelial diversity in normal human livers: a tissue-tethered cytometric analysis in portal/periportal epithelial cells.Hepatology. 2013; 57: 1632-1643https://doi.org/10.1002/hep.26131Crossref PubMed Scopus (36) Google Scholar This applies particularly well to the investigation of lymphocytic subpopulations in the context of liver transplantation. The authors declare no conflicts of interest that pertain to this work. Please refer to the accompanying [10]Isse K. Lesniak A. Grama K. Maier J. Specht S. Castillo-Rama M. et al.Preexisting epithelial diversity in normal human livers: a tissue-tethered cytometric analysis in portal/periportal epithelial cells.Hepatology. 2013; 57: 1632-1643https://doi.org/10.1002/hep.26131Crossref PubMed Scopus (36) Google Scholar forms for further details. The following are the Supplementary data to this article: Download .pdf (.09 MB) Help with pdf files Supplementary Data