Related Experiment Video
Updated: May 9, 2025

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
Breast Pathology Through the Digital Lens
Alexis Heller1, Lakshmi Kowtha1, Kriti Tiwari1
1Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
Abstract:
Digital pathology (DP) has significantly transformed breast pathology at Mount Sinai Hospital by enhancing diagnostic accuracy, collaboration, and education. The institution has integrated the Philips IntelliSite Pathology Solution (PIPS) for primary diagnostic use, which allows for high-resolution whole slide imaging (WSI) of surgical pathology slides. The workflow involves the scanning of glass slides to create digital images, which are then reviewed and annotated by pathologists. Key benefits of this workflow include immediate slide sharing with colleagues, efficient sign-outs, improved detection of low-positive immunohistochemical staining, and detailed measurements of tumors and margins. The ability to access a digital archive for retrospective case reviews further enhances diagnostic capabilities. However, limitations persist, including challenges in visualizing small calcium oxalate crystals and the need for manual interpretation of certain stains. Although the process of digitizing slides initially increased turnaround times, this has been mitigated by increased staffing and scanner availability. Additionally, the transition to DP has already paved the way for artificial intelligence, serving as a benchmark to develop algorithms for prognostic and predictive biomarkers, predict immunotherapy response, and thus transform cancer care. The overall impact of DP on breast pathology is overwhelmingly positive, with continued efforts to address its limitations.
More Related Videos
07:41Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
15:48Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014