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Enabling Path of Digital Pathology to Personalized Medicine

Session #74, February 12, 2019

Matthew G. Hanna, MD, Memorial Sloan Kettering Cancer Center

Rajendra Singh, MD, The Mount Sinai Hospital

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Matthew Hanna, MD

Advisory Board, PathPresenter

Rajendra Singh, MD

Founder, PathPresenter

Conflict of Interest

Have no real or apparent conflicts of interest to report

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Agenda

Intro Ecosystem

Educational

Initiatives

Current

Landscape

endQ/A

Digital

Pathology

PathPresenter

FUTURE

AI/ML

Personalized

medicine

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Learning Objectives

Define what is digital pathology and what is its promise

Design an effective program that will train the pathologists of today and

tomorrow in digital pathology

Practice using digital pathology for educational, research, and clinical

purposes

Outline path of pathology to digital pathology to computational pathology

and finally to personalized medicine for patients

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Film photography isnow a niche field

2001 E-book market jumpstarted in 2009.Did not invest in digital solutions.

2011

Failed to identify digital photography as a disruptive technology, had to sell film, patents, scanners to stay alive

2012

Failed to innovate a digital solution.Netflix added streaming services in 2010.

2010

Years Companies Filed for Chapter 11

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Life of Patients’ Specimens

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Digital Pathology Basics

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THE FIVE RIGHTs OF DIGITAL PATHOLOGY

RIGHT PATIENT

RIGHT SLIDE

RIGHT

PATHOLOGIST

RIGHT TIME

“Telepathology”

RIGHT

DIAGNOSIS

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Digital Pathology Ecosystem

Resource: Hanna, M. G., & Pantanowitz, L. (2019). Digital Pathology. In R. Narayan

(Ed.), Encyclopedia of Biomedical Engineering, vol. 2, pp. 524–532. Elsevier.

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Digital Pathology Subsystems

Software

Hardware

Whole slide image

Slide Scanner

Slide scanning

Robotics/slide handling

Optics/Lighting

Tissue detection

WSI viewer

File format

WSI acquisition

WSI repository

Compression

Image analysis

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Digital Pathology ProcessARMS

Acquisition

Retrieval/Storage

Manipulation

Sharing

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1x magnification

20x magnification

40x magnification

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Digital Pathology Benefits

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On-demand Archive/Case management

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Glass slides storage

Move slides from local

To remote

↓ Costs

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Archival glass slide requisitions had a 93% decrease in requests

47,387

186,607

424,901

19,369 20,745

12,336

1,426 -

5,000

10,000

15,000

20,000

25,000

-

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

2014 2015 2016 2017

Gla

ss S

lid

e R

eq

uests

(n

)

Dig

ita

l S

lid

es

(n

)

Digital slides available Glass slide requests

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Slide storage costs projected savings of $274,000/year

Due to decreased vendor services

(i.e. asset retrieval, storage proximity, labor)

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Image Analysis

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Wang, Khosla, … Beck (2016) https://arxiv.org/abs/1606.05718 Camelyon16 (JAMA, 2017)

Machine Learning

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Big Data meets Pathology

Massive volume of digital data generated from WSI & bioinformatics/molecular data

Critical for personalized medicine, health systems, basic research and “Big data”

Dataset sizes: Computer vision vs. computational pathology

1 whole slide = 100 X 60,000 = 6 billion pixelsFrom Fuchs, 2017

Computational Pathology

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Why is this possible now?

Image datasets

Cognitive algorithms

Fast computing/GPUs

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Challenges

Not always being done with pathologist involvement, mostly being

done in computer science departments

No universal platform to aggregate and share the vast amount of

data generated by pathology across thousands of hospitals, medical

centers and reference laboratories

Available solutions are often scanner specific, lack useful

apps/tools for Pathologists, lack active participation of

pathologists and lack high quality aggregated data

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You would feel comfortable providing primary diagnosis using

digital pathology, with retrieval of glass slides available upon

request

You would feel comfortable providing primary diagnosis using

digital pathology, without availability of glass slides

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What can be accomplished?

• Education

– Trainee/faculty education/CME

• Clinical

– Create efficiencies for pathologists

• Research

– Identify digital prognostic markers

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Education

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Why is there a need?

Lack of open-access to digital slides or are restricted by firewalls to download software

Learning from digital slides is not only having access to digital slides; it should also simulate

current teaching techniques

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CURRENT TEACHING TECHNIQUE

Outdated, Unscalable, Limited

http://www.teachingmicroscopes.com

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Current landscape of Digital Educational Resources

PathXL

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DPA

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CAP Case of the Month

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PathXL

http://www.pathxl.com/pathology-education-tutor

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PathPresenter

• Digital pathology company built by pathologists for pathologists

• Focused on building software to enhance and standardize the learning and teaching experience in pathology

• Provide a multidisciplinary educational environment

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Current PathPresenter Apps for education

• Developed Applications for Public or Institutional Use

MySlideBoxManage your digital slides and

folders.

High YieldLearn and study from hand-picked

cases to prepare for board

examinations, or to brush up on must-

know diagnoses

My PresentationsCreate and manage your presentations

using our extensive Slide library or by

uploading your own slides

QuizSearch, view, or share from thousands

of cases covering all medical

subspecialties

Slide LibrarySearch, view, or share from thousands

of cases covering all medical

subspecialties

Group ChatCreate group with other members and

discuss slides.

AnalysisCreate Analysis and

collaborate to add

annotations and discussions

in Groups

QACross check the Quality of

Diagnosis by assigning to the

expert reviewers

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MySlideBox

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Slide Library

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My Presentations

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High Yield Sections

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Quiz Module

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Steps to Facilitate Education

•Provide an easy to use platform for trainees, faculty, and pathology departments

•Provide high quality content

•Content validated by experts

•Publicized on social media

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Path of Pathology to Personalized Medicine

Bring digital

pathology to

the world

Provide a new

standard medical

presentation

platform

Make

pathologist

comfortable

using digital

pathology

High quality

curated

digital

images

Pathology to

personalized

medicine

Growth in

pCAD

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Use Cases

• PhysiciansReady access to a wealth of data and images, with seamless medical presentations

• InstitutionsBranded platforms with site specific content, monetized to the medical community

• PharmaAgnostic platform coupled with pathology data and AI apps for

real time analysis

LEARN, TEACH, CONSULT, RESEARCH, PUBLISH, CME

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Is it really working?• Usage by country/continent

>162

Countries Users

>62,000

>10,000

Digital Images Apps

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30%

Why this will only increase

Future

PathologistsNumber of

cancer cases 70%

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How will AI affect Pathology Education

De-skilling Access to resources

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Clinical & Research

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Digital Pathology &

Personalized Medicine

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Digital Pathology Slide

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Cancer registrydata

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Clustering corresponded with molecular gene expressions and prognosis

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Survival and Relapse

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https://ai.googleblog.com/2017/03/assisting-pathologists-in-detecting.html

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https://ai.googleblog.com/2018/04/an-augmented-reality-microscope.html

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Assistive screening tools for pathologists

Resource:

https://ai.googleblog.com/2018/04/an-augmented-reality-microscope.html

https://ai.googleblog.com/2018/10/applying-deep-learning-to-metastatic.html

LYNA (LYmph Node Assistant)ARM

(Augmented Reality Microscope)

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Novel Technologies: Multiplex

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(h) autofluorescence

(i) Red = tumor

Green = stroma

(j) Double positivity

yellow = HER2+/Ki-

67+

blue = HER2–/Ki-67–

red = HER2–/Ki-67+

green = HER2+/Ki-67–

Multispectral Imaging. A Review of Its Technical Aspects and

Applications in Anatomic Pathology. J. R. Mansfield

HER2 PR Ki67 ER

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Will AI/New tech Lead to Better Patient Care?

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Digital pathology is increasingly being used and will be a key enabler of personalized medicine.

Many areas of medicine including clinical, education, and research are creating and utilizing digital imaging applications including AI/machine learning.

Pathologists’ current routines is transforming and being impacted by digital pathology.

We need to continue to partner with industry vendors and continue to build applications of WSI for clinical use including primary diagnosis and image analysis to help drive personalized medicine.

Take Home Messages

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The Road to Personalized Medicine

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• Matthew G Hanna, MD

• mghannamd@gmail.com

• Rajendra Singh, MD

• skinpathology@gmail.com

• Please remember to complete online session evaluation

Questions