Jake Eden
Global Product Manager,
Digital Pathology, Denmark
Agilent Technologies, Inc

Robert D Goldin
Professor, Imperial College London,
UK

Biography:

I am Professor of Gastro-intestinal and Liver Pathology at Imperial College and Clinical Lead for Gastro-intestinal Pathology in the North-West London Pathology Trust. I also work at the Ludwig Institute for Cancer Research in the University of Oxford. My interests are in clinical and experimental aspects hepato-biliary and gastro-intestinal disease. I am, especially, focused on liver cancer, steatohepatitis and gastro-intestinal malignancy. I am particularly interested in developing new approaches to obtaining information from tissue using computational pathology, metabonomic and other imaging techniques.

Abstract:

The digitisation of pathology promises to deliver improved workflows and allow for the application to Artificial Intelligence (AI) to challenging areas. Medical liver biopsies are an exemplar of this. Although these biopsies are relatively low volume, they require a high level of specialist reporting of a kind available only in regional centres. Digitisation expedites the transfer of biopsies to these centres and allows for clinical decisions to be made in a time frame that improves patient outcome. We have experience in setting up such a network in NW London.

The commonest indication for medical liver biopsy is metabolic dysfunction associated liver disease (MALD). Patients with this condition are increasingly being recruited into clinical trials. Entry is based on semi-quantitative assessment of key histological features. Unfortunately, this assessment has been shown to be very subjective and AI based approaches, in which we are actively involved, have been applied to address the problems posed by MALD.

Teemu Tolonen, MD, PhD
Project manager, Digital Pathology
Head of Department, Fimlab Laboratories,
Finland

Biography:

Teemu Tolonen graduated from the University of Tampere with a Doctorate of Medicine and Doctorate of Philosophy with a focus in cancer genetics. He became an adjunct professor of pathology in 2019. In 2010 he began his residency at Fimlab Laboratories, one of the leading laboratory companies in Finland, providing laboratory services, education, and research in Pirkanmaa, Central Finland, Kanta-Häme, Ostrobothnia and Paijät-Hame regions. In 2017 Dr. Tolonen became the Head of the department of pathology at Fimlab Laboratories. Over the course of his career, Dr. Tolonen has served key roles for the Finnish Division of the International Academy of Pathology (IAP), as a board member (2014-2015) and President (2016-2017/2018-2019). Dr. Tolonen has 62 publications that include scientific publications on genitourinary lab cancers and digital image analysis.

Abstract:

The integration of digital pathology image management systems (IMS) with embedded multi-AI workflows represents a transformative advancement in the field of histopathology. This presentation will explore the significant value these technologies bring to clinical practice, using IHC quantification as an example, and when deployed at scale in a full software-as-a-service (SaaS) solution across multiple sites and with multiple applications. The session will focus on practical considerations for system requirements, implementation, and future direction of a true multi-site, multi-AI workflow in pathology.

Bert van der Vegt, MD, PhD
Consultant Histopathologist
University Medical Center Groningen,
The Netherlands

Biography:

Dr. Bert van der Vegt has been working as a consultant breast and head & neck pathologist at the department of Pathology and Medical Biology of the University Medical Center Groningen, The Netherlands since 2012. His research focuses on the discovery, validation and clinical implementation of biomarkers in cancer (breast and head & neck cancer) and auto-immune disorders (Sjögren’s syndrome). In particular the use of digital- and computational pathology (DCP) in this field has his interest. He is leading the DCP unit of the department of Pathology, which focuses on bringing Digital Image Analysis algorithms to routine clinical pathology practice.

Abstract:

To really benefit from the advantages of computational pathology these techniques need to be seamlessly integrated in the routine digital pathology practice. This talk will focus on current challenges and possible solutions and opportunities in optimizing the digital pathology workflow from the perspective of a pathology department that has been working fully digital for over 5 years.

Holger Moch, Professor, MD
Director of Institute of Pathology and Molecular Pathology Laboratories
Universitätsspital Zürich,
Switzerland

Biography:

Dr. Holger Moch is a Professor of Pathology at the University Zurich, Switzerland. He is the Chairman of the Institute for Surgical Pathology as well as Clinical Co‐Director in the Department Pathology of the University Hospital Zurich. Dr. Moch is a graduate of the Humboldt University Berlin (Charité), Germany and completed his residency training at the Institute for Pathology, University Basel, Switzerland. Dr Moch is a member of the United States and Canadian Academy of Pathology, the editorial board of various journals and boards of several cancer research foundations. He is member of the Executive Committee of the Swiss Group for Clinical Cancer Research (SAKK), the Cancer Network Zurich (CNZ), and the Competence Center for Systems Physiology and Metabolic Diseases (CC‐SPMD) of the University Zurich and the Swiss Federal Institute for Technology Zurich (ETH). His work is described in more than 200 per reviewed papers. In 2007, he was elected as a member of the German National Academy of Science Leopoldina. 
 
Abstract:  

Evolving Role of Digital Pathology in Anatomic and Molecular Pathology Laboratories
Comprehensive targeted parallel sequencing, whole-genome copy number variation (CNV) analysis, determination of microsatellite instability (MSI) and tumor mutational burden (TMB) testing for personalized therapies require an exact estimation of tumor cell content. In parallel, exact quantification of tumor infiltrating lymphocytes may support selection of patients for immunotherapy. The use of digital pathology (DP) has a great impact for both, research and clinical workflows. Once slides are in a digital format, they become amenable to digital transfer and computational analysis. DP images can be analyzed by machine learning (ML) algorithms to enable more precise characterization of disease presentation features, and data mining of these features for discovery of clinically relevant biomarkers. 
In this presentation, we describe examples for the relevance of DP in diagnostic molecular pathology workflows and in research questions. Estimation of tumor cell content can be performed by pathologist, by molecular methods or DP. Comparison of these three different estimates of tumor cell content in our cohort of more than 1000 solid tumors reveals strengths and weaknesses of each method. Exact quantification of the spatial distribution of tumor-infiltrating T cells and of tertiary lymphoid structures is possible by digital immunoprofiling and allows to identify different prognosis of pathologically “cold” and “hot” tumors. Integrative analysis of molecular and immune phenotypes identified an association of an inflamed microenvironment with specific genomic alterations. These image-based approaches benefit from being orders of magnitude faster and more cost-effective than their genetic assay-based counterparts, potentially enabling a more complete characterization of tumor heterogeneity. Our results obtained from DP also suggest that clinically relevant tumor subtypes can be extracted directly from H&E-stained whole slide images and may complement gene expression-based patient stratification. Thus, DP will facilitate the development and implementation of tools for increased diagnostic efficiency, quality and patient safety.  
 
Holger Moch1, 2, Tobias Krull 1 Jan Rüschoff 1, Bettina Sobottka 1 
 
1 Department of Pathology and Molecular Pathology, University Hospital Zurich  
2 Medical Faculty, University Zurich, Zurich, Switzerland