Tissue microarray Immuno-histochemistry (IHC) data can be accurately assessed using digital pathology. However, it is still essential to validate the data against pathologist manual interpretation and evaluate the comparability of the data obtained by various software applications. In this study, we benchmarked the results against pathologist manual scores by comparing the IHC quantification of five clinical breast cancer biomarkers—Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2, Epidermal Growth Factor Receptor, and Cytokeratin 5/6 (CK5/6). In diagnostic pathology, the study of whole cells is called cytotology. Cytologic preparations, in contrast to standard histologic thinly sliced specimens, are prepared from whole cells where cells typically cluster and aggregate. As a result, when viewed through a microscope, cytology preparations typically exhibit large areas of defocus because they are significantly thicker than histologic slides. Pathologists must constantly manipulate the focal plane to view a diagnostic aggregate of cells in focus together, which makes it difficult to accurately assess the entire cellular aggregate and, consequently, to make a diagnosis. In addition, it is extremely challenging to acquire digital images of cytology preparations that are uniformly focused and useful for applications like artificial intelligence models and remote diagnostic evaluations. Acquiring digital images at multiple focal planes across the slide is currently the most common approach to this problem. However, this method necessitates a significant amount of storage space, complex and expensive scanning systems, and a lengthy scanning time. Standard microscopes can use this technology, which we believe can improve diagnostic accuracy as well as the ease and speed with which difficult specimens can be diagnosed. While cytology slides are the focus of this article, we anticipate that applications in histology will benefit greatly from this technology. The issue of remote rapid evaluation of cytology preparations is also addressed by this method. Lastly, we believe that this method is an important step forward in the application of machine learning to cytology specimens because it resolves the focus heterogeneity issues in standard digital images. Digital pathology represents a brand-new development phase in the field of pathomorphological diagnostics. During the COVID-19 pandemic, this issue received the most attention. The upsides of digitization of diagnostics incorporate the chance of remote work of a pathologist, distant nonconcurrent counsel, and mechanization of business processes. They speed up the diagnosis process and improve diagnostic quality. Digital cancer diagnostics can offer a lot more than just these advantages. Our personal experiences working at Russia's first digital pathomorphological laboratory, UNIM, are the basis for this article. The economics of the process, the importance of integration with LIS and MIS, errors and the principles of their solution, payback, and every stage of laboratory work will be considered in detail. Additionally, all advantages and disadvantages of digitization, peculiarities of using technology, differences from the conventional approach to diagnostics, and differences from the conventional approach will be discussed. from diagnosis and archiving to logistics and registration. We will present a comprehensive analysis of statistics and observations on how to organize processes in a fully digital laboratory because all data has been digitized over several years. The high cost-effectiveness of the platform and approach, which enabled us to compete successfully in the market, is an important aspect of our experience. The survey of physicians' attitudes toward digital pathology's findings will also be presented. The uPath HER2 Dual ISH Image Analysis for Breast algorithm was developed to assist pathologists in determining the HER2 gene status of breast cancer specimens. This study sought to contrast manual read scoring with uPath HER2 DISH image analysis for VENTANA HER2 DISH-stained breast carcinoma specimens using the Ground Truth (GT) gene status as a reference. 220 Formalin-Fixed, Paraffin-Embedded (FFPE) breast cancer cases were examined by three reader pathologists using both manual and uPath HER2 DISH IA techniques. The GT gene status determined by a panel of pathologists was compared to the scoring results from computer-assisted scores (IA) and manual read scores (MR). The distinctions in understanding paces of HER2 quality status between manual, PC helped, and GT quality not set in stone. Overall, our data support the uPath HER2 DISH IA's use as an aid for pathologists in routine breast cancer diagnosis because it is comparable to manual scoring.

With Regards,
Sara Giselle
Associate Managing Editor
Journal of Stroke Research & Therapy