The process of removing and staining tissue for disease diagnostics, especially in oncology, has been practiced the same way for more than a century. In today’s world of network-based medicine, there are new advancements that enable this field to
detect, visualize and monitor diseases more effectively, which would lead to better diagnosis, treatments
and outcomes. Cambridge Healthtech Institute’s Tissue Diagnostics program is designed to bring together experts in the field to share their latest findings for best practices and global transformation of tissue diagnostics in the age of
digital world and artificial intelligence.
Final Agenda
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Arrive Early for:
MONDAY, MARCH 11, 8:00 - 11:00 AM (MORNING SHORT COURSES)
SC20: Digital Pathology: A-Z for Beginners - Detailed Agenda
Monday, March 11
10:30 am Conference Program Registration Open (South Lobby)
Eric F. Glassy, MD, FCAP, Medical Director, Affiliated Pathologists Medical Group
12:00 pm Advancing Cancer Diagnostics with Artificial Intelligence
Martin Stumpe, PhD, Senior Vice President, Data Science, Tempus
Rendering cancer diagnoses from tissues is a highly complex process that requires many years of expert training. It involves challenging tasks for pathologists, such as identifying rare events in very large images (e.g., micrometastases in lymph nodes), or classifying subtle differences between normal vs. tumor, or amongst similar-looking tumors that have very different treatment plans. These tasks are typically more challenging for human cognition, and, consequently, over- and under-diagnoses are not uncommon, resulting in non-optimal treatment selection. In recent year, deep learning has been successfully applied for several image-based tasks in digital pathology. This talk will discuss the potential of machine learning in cancer diagnostics, as well as the challenges to bring it to practical, and how those challenges can be overcome.
12:30 QuPath: Digital Pathology for Everyone
Peter Bankhead,
PhD, Senior Lecturer, Digital Pathology, University of Edinburgh
QuPath is an open source digital pathology platform that is rapidly becoming established as the software of choice for many researchers worldwide working with whole slide images, both in academia and industry. This talk describes the background to
QuPath, its current applications
and latest developments, and discusses what the software offers pathologists, biologists and algorithm developers looking to apply sophisticated and reproducible analysis and visualization methods to complex tissue images.
1:00 Enjoy Lunch on Your Own
2:30 Chairperson’s Remarks
Richard M. Levenson, MD, Professor and Vice Chair for Strategic Technologies, Department of Pathology
& Laboratory Medicine, UC Davis Medical Center
2:40 Rapid, Automated Brain Tumor Diagnosis Using Stimulated Raman Histology
Daniel A. Orringer, MD, Assistant Professor, Neurosurgery; Member, Cancer Center, University of Michigan
Accurate, diagnostic histologic information is essential for decision making during brain tumor surgery. Conventional histologic techniques complicate and delay the access of clinicians to microscopic data. Stimulated Raman histology (SRH), a label-free
method for generating histologic images of fresh specimens puts microscopic data at the surgeons’ fingertips. Moreover, SRH images are natively digital and well-suited to automated interpretation through emerging artificial intelligence
(AI) methods. SRH and AI can be combined to unlock and annotate histologic information that can be leveraged by surgeons to provide the best possible care to their patients.
3:10 3D Light-Sheet Microscopy for Next Generation Pathology
Nicholas P. Reder, MD, MPH, Genitourinary Pathology Fellow, CAP In-Vivo Microscopy Committee, Junior
Member, Harborview Medical Center, Department of Pathology, University of Washington
Light-sheet microscopy, in combination with optical clearing techniques, enables non-destructive 3D imaging of tissue. These 3D microscopic images yield new biologic insights into prostate carcinoma, kidney vasculature, and other 3D structural
features. In addition, the non-destructive nature of this technique creates laboratory workflow efficiencies and better integration with genetic sequencing assays. I will give an overview of the current state of the technology, future directions,
and potential for clinical adoption.
3:40 Deep Learning-Enabled Computational Imaging in Pathology
Aydogan Ozcan,
PhD, Chancellor’s Professor, Electrical & Computer Engineering Bioengineering, UCLA; HHMI Professor, Howard Hughes Medical Institute; Associate Director, California NanoSystems Institute (CNSI); Founder of Holomic/Cellmic LLC
Deep learning is a class of machine learning techniques that
uses multi-layered artificial neural networks for
automated analysis of signals or data. Beyond its
main stream applications such as the recognition and labeling of specific features in images, deep learning holds numerous opportunities for revolutionizing image formation, reconstruction and sensing fields. In this presentation, I will
provide an overview of some of our recent work on the use of deep neural networks in advancing computational microscopy systems, also covering their applications in pathology.
4:10 Big Picture - Deep Analysis. Cloud Based Active Deep Learning for Computational Pathology
Thomas Westerling-Bui, PhD, Senior Scientist, Aiforia Inc.
Traditionally the use of DeepLearning in image analysis has been the domain of the computer and data scientists. Here we show how you can by simple deployment of Aiforia Cloud Solutions, enable yourself to train, validate, and deploy DeepLearning
algorithms in your own digital pathology workflow.
4:40 Refreshment Break and Transition to Plenary Session
5:00 Plenary Keynote Session (Room Location: 3 & 7)
6:00 Grand Opening Reception in the Exhibit Hall with Poster Viewing
7:30 Close of Day
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Tuesday, March 12
7:30 am Registration Open and Morning Coffee (South Lobby)
8:00 Plenary Keynote Session (Room Location: 3 & 7)
9:15 Refreshment Break in the Exhibit Hall with Poster Viewing
10:15 Chairperson’s Remarks
Karl V. Voelkerding, MD, Professor, Pathology, University of Utah; Medical Director
for Genomics and Bioinformatics, ARUP Laboratories
10:25 Best Practices for Clinical Validation of NGS Bioinformatics Pipeline
Somak Roy, MD, Director, Molecular Informatics, Genetics Services, & MGP fellowship, Molecular and
Genomic Pathology, University of Pittsburgh Medical Center
A joint consensus guideline was developed by the Association of Molecular Pathology (AMP), in conjunction with the College of American Pathologists (CAP), and the American Medical Informatics Association (AMIA) for validation of clinical
NGS bioinformatics pipelines. This talk will discuss these best practice consensus recommendations with emphasis on distributive NGS testing model,
role of in silico datasets, and laboratory accreditation checklist (CAP).
10:55 Improving Clinical Quality with Bioinformatics Automation
Elaine P.S. Gee,
PhD, Founder & President, BigHead Analytics Group; Principal Algorithm Development Engineer, Sensor R&D, Diabetes R&D, Medtronic
Clinical genomic testing relies on complex bioinformatics pipelines to perform a range of genomic profiling functions, from identification of germline and somatic genomic alterations to pathogen detection and identification. Each pipeline
is comprised of complex algorithms carefully parameterized to meet the intended clinical needs. This talk highlights how to improve quality at scale by leveraging automation throughout the bioinformatic product life cycle for actionable
feedback on pipeline performance.
11:25 Current and Future Approaches to Sequence Variant Interpretation
Julie M. Eggington, MS,
PhD, Co-Founder and CEO, Center for Genomic Interpretation (CGI)
The clinical science
speciality of genetic variant classification and reclassification has evolved rapidly in recent years. With a focus on
germ line (aka hereditary) disease variant classification, this presentation will review the current state of the
speciality, including what is working well, and what can and will be improved to ensure better patient care.
11:55 Networking and Q & A with Speakers in the Session
12:25 pm Enjoy Lunch on Your Own
1:35 Refreshment Break in the Exhibit Hall with Poster Viewing
2:05 Chairperson’s Remarks
Jennifer J.D. Morrissette,
PhD, FACMG, Scientific Director, Clinical Cancer Cytogenetics; Clinical Director, Center for Personalized Diagnostics, Department of Pathology, University of Pennsylvania
2:10 NCI Resources to Support Biospecimen-Based Research
Helen M. Moore,
PhD, Branch Chief, Biorepositories and Biospecimen Research Branch, NCI
The U.S. National Cancer Institute offers evidence-based best practice documents,
an online literature and SOPs database, and research programs to support the collection of
high quality research biospecimens. These resources will be discussed as well as new biobanking programs being developed under the Cancer Moonshot initiative.
2:40 A Moving Target: Optimization and Evolution of NGS Testing in Myeloid Malignancies
Jennifer J.D. Morrissette,
PhD, FACMG, Scientific Director, Clinical Cancer Cytogenetics; Clinical Director, Center for Personalized Diagnostics, Department of Pathology, University of Pennsylvania
This talk will discuss how our laboratory incorporated longitudinal testing for our hematological malignancy patients, based on data demonstrating the shift of clones containing variants that respond to targeted therapies, including FLT3,
IDH1
and IDH2. The extremely poor outcome for patients harboring a TP53 mutation and the gene variants known to respond to targeted therapies has highlighted the need to rapidly identify variants. The final section will discuss the
validation of a rapid NGS test in the laboratory.
3:10 A Multi-Institutional Collaborative Approach to Reducing Costs and Driving Standardization of Oncology NGS
Jeremy Segal, MD,
PhD, Assistant Professor; Director, Genomic and Molecular Pathology, University of Chicago
Next-generation sequencing (NGS) oncology diagnostics are continuing to grow in complexity and represent a substantial developmental and validation challenge for clinical laboratories. Academic laboratories are mainly working independently,
creating a variety of different assays on various chemistry platforms with variable gene lists, bioinformatics algorithms and reported features. This assay variability raises questions of cross-site concordance and puts academic labs
at a regulatory disadvantage. To lower NGS-associated laboratory costs and begin to work towards cross-site assay standardization, we assembled a collection of 17 academic laboratories to pursue a novel type of large-scale hybrid capture
reagent purchase capable of supporting standardization efforts while permitting flexible design for site-specific gene content. This talk will address the formation of the Genomic Oncology Academic Laboratory (GOAL) consortium, the
details of the group purchase including design specifications and performance, and future directions related to assay and bioinformatics standardization.
3:40 Tissue Print Technologies for Biopsy-Based Molecular Biomarker Studies
Sandra M. Gaston
PhD, Director, Molecular Biomarkers Analytic Laboratory, Radiation Oncology, University of Miami Miller School of Medicine
Many tissue biomarker tests are designed to use FFPE specimens as a source of RNA and/or DNA, but the allocation of FFPE tissue for pathology and research is becoming increasingly challenging, particularly for biopsy specimens. Tissue
prints provide a practical alternative for obtaining RNA, DNA and protein biomarkers for molecular analyses without compromising the specimen for diagnostic H&E and immunohistochemistry. With biopsies, tissue prints support
molecular biomarker studies of valuable specimens that may otherwise be significantly limited or entirely unavailable for research. Because tissue prints are snap frozen rather than fixed in formalin, the purified tissue print RNA
and DNA is
of high quality and suitable for advanced biomarker analysis. We will review applications of tissue print techniques to biopsy-based studies of RNA, DNA and protein biomarkers, to molecular biomarker mapping and to biorepository
specimen annotation.
4:10 St. Patrick’s Day Celebration in the Exhibit Hall with Poster Viewing
5:00 Breakout Discussions in the Exhibit Hall
6:00 Close of Day
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Wednesday, March 13
7:30 am Registration Open and Morning Coffee (South Lobby)
8:00 Plenary Keynote Session (Room Location: 3 & 7)
10:00 Refreshment Break and Poster Competition Winner Announced in the Exhibit Hall
10:50 Chairperson’s Remarks
Liron Pantanowitz, MD, Professor, Pathology & Biomedical Informatics, University of Pittsburgh Medical Center
11:00 The Application of Pathology-Based Image Analysis and AI to Patient Selection Strategies in Immuno-Oncology Clinical Trials
Michael C. Montalto,
PhD, Head, Translational Pathology and Clinical Biomarker Laboratories, Translational Medicine, Bristol-Myers Squibb
Understanding the role of the tumor
micro environment is paramount to the success of patient selection strategies in immune-oncology drug development. This talk will explore the role of automated image analysis and artificial intelligence for pathology samples in
I-O drug development, and its potential as a platform for patient stratification and companion diagnostics.
11:30 Building the Digital Pathology Cockpit: What Is It Looking Like and Where Does It Need to Go?
Douglas J. Hartman, MD, Associate Professor of Pathology and Director, Division of Pathology
Informatics, University of Pittsburgh Medical Center
Digital pathology is increasing in adoption throughout pathology departments. There is a transition of the working environment from a microscope environment to a computer. This creates the opportunity to augment the tools that are available
for a pathologist in order to support better diagnostics. These additional tools have been described as a diagnostic cockpit. There are lessons that can be learned from our radiology colleagues as the pathology cockpit evolves.
12:00 pm Digital Pathology Applications for Personalized Health Care: An Industrial Perspective on Immunohistochemical Assays
Ehab A. ElGabry, MD, Senior Director, Pathology & Companion Diagnostics, Pharma Services
Medical Director, Ventana Medical Systems, Inc., A Member of the Roche Group
In an era focused on personalized health care (PHC), the use of immunohistochemical assays for targeted immunotherapies (e.g. Programmed death ligand 1) is rapidly expanding. The objective of this presentation is to give a brief overview
of the current and future role of digital pathology in the development process of these assays from early hypothesis to launch. More specifically we will share our experience using image analysis software, digital platforms for
training, artificial intelligence and multiplexing technologies.
12:30 Enjoy Lunch on Your Own
1:10 Refreshment Break in the Exhibit Hall and Last Chance for Poster Viewing
1:50 Chairperson’s Remarks
Emanuel “Chip” Petricoin, CSO, Perthera
2:00 Multi-Omic Network Analysis in Complex Disease
Kimberly Glass,
PhD, Assistant Professor of Medicine, Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School
Networks provide a powerful approach for modeling biological mechanisms. Our group has developed a suite of methods
for: (1) integrating multi-omic data through gene regulatory network reconstruction; (2) analyzing networks to identify changes in disease state; and (3) modeling patient-specific networks to link regulatory alterations with
disease phenotype. We have applied these approaches to discover new disease features and to understand alterations in biological processes across patients with lung disease.
2:30 Dissecting Proteomic Heterogeneity of the Tumor Microenvironment
Thomas P. Conrads,
PhD, Associate Director of Scientific Technologies, Inova Schar Cancer Institute, Inova Center for Personalized Health; Chief Scientific Officer, Gynecologic Cancer Center of Excellence, John P. Murtha Cancer Center, Walter
Reed National Military Medical Center, Uniformed Services University of the Health Sciences
This lecture will highlight cutting edge applications in applying laser microdissection and microscaled quantitative proteomics and phosphoproteomics to uncover exquisite
intra- and inter-tumor heterogeneity. The paradigm-shifting results offer unprecedented opportunities to speed progress in identifying novel molecular sub-types of cancer, therapeutic targets, prognostic signatures, and companion
diagnostics.
3:00 A Cloud-Based Asynchronous Virtual Tumor Board Facilitates Treatment Recommendations for Patients with Advanced Cancers Based on Molecular and Clinical Data
Subha Madhavan,
PhD, Director, Innovation Center for Biomedical Informatics (ICBI); Associate Professor, Oncology, Georgetown University Medical Center
We developed a cloud-based, asynchronous virtual tumor board (VTB) that integrates multi-modal patient data to formulate, discuss, and rank treatments. The VTB utilizes 8 linked databases, a treatment scoring model based on the AMP/ASCO
variant interpretation guidelines and an AI-based treatment
recommender. The VTB provides a scalable platform for integration and asynchronous team communication for facilitating case review with no geographical and time/attendance restrictions. We anticipate that further development
of such clinical decision support tools will be important for widespread adoption of cancer precision medicine.
3:30 Session Break
3:40 Chairperson’s Remarks
Eric F. Glassy, MD, FCAP, Medical Director, Affiliated Pathologists Medical Group
3:45 What is the Future of Pathology?
James M. Crawford, MD,
PhD, Professor
and Chair, Department of Pathology and Laboratory Medicine, Senior Vice President of Laboratory Services, Northwell Health
An article-of-faith for pathologists, and pathology in
general, is that we practice high impact patient-centered healthcare that touches virtually every person in their life journey. But to policy-makers and our stakeholders, including consumers, pathology is a commodity. And in
the transformation of American healthcare to a value-based system, pathology is at risk of being left off the agenda, except perhaps for cancer screening programs. While laboratory medicine and precision medicine are getting a
good run at building their “value-added” evidence base for the future practice of medicine, anatomic pathology has not yet done so. Digital pathology and AI/ML hold promise, but if the only achievement is facilitating
more effective workflow for pathologists, then we will have fallen short. This talk will examine how pathology (as in anatomic pathology) might effectively bring its “value statements” into the future of healthcare
and secure its future position as a valued asset.
4:15 Interoperability Advances in Digital Pathology and Implications for Your Organization’s Imaging Strategy
Raj C. Dash, MD, Professor and Vice-Chair, Pathology IT, Duke University Health System; Medical Director,
Laboratory Information Systems
The Pathology and Lab Medicine (PALM) domain of the Integrating the Healthcare Enterprise (IHE) organization has collaborated with DICOM (Digital Imaging and Communications in Medicine) working group 26 to propose an initial draft
solution supporting an environment of interoperability among
vended digital pathology instrumentation and systems focused on acquisition of digital assets critical for anatomic pathology diagnostics. This solution aims to increase the value of all
vended digital pathology components.
4:45 Artificial Intelligence (AI)/Machine Learning (ML) Expert Systems in Pathology
Hooman H. Rashidi, MD, FASCP, Professor and Vice Chair, GME, Director of Residency Program;
Director, Flow Cytometry & Immunology, Department of Pathology and Laboratory Medicine, University of California, Davis School of Medicine
AI/ML platforms will undoubtedly become an integral part of our future medical practice workflow (such as pathology and radiology). These ML platforms can help the workflow with triage, help formulate a differential diagnosis, help
verify one’s diagnostic impression, and enhance the laboratory workflow as the number of cases per diagnostician increases. The development and validation of such platforms
requires a multidisciplinary team that includes a specialist, machine learning expert(s) and certain digital delivery platform experts.
5:15 Close of Conference Program
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