1. 8-1-2016 pag. 1
How digital pathology can add
value to your biobank
Yves Sucaet, PhD
Diabetes Research Center
CMI
2. 8-1-2016 pag. 2
Who am I?
Education
• 2000: Hogeschool Gent (BE)
– BS Computer Sciences
• 2001-2005: Troy State
University (US)
– Exchange program
– MS Biological Sciences
• 2005-2010: Iowa State
University
– PhD Bioinformatics &
Computational Biology
Professional
• 2000-2001: Becton Dickinson
• 2010-2013: HistoGeneX
• Data Management
• Bioinformatics
• Section head
• 2014-2016: VUB
• Digital Pathology Manager
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Presentation outline
• Background
– What is Whole Slide Imaging (WSI)
– What is Digital Pathology
• What is a biobank?
• Adding value to your biobank
– By adding slide imaging data
– By adding (semi)automated image analysis
• Things to consider
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What is Whole Slide Imaging (WSI)?
• The technique of converting glass-mounted microscopy
material into a digital representation / image.
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Implementing WSI for end-users
Enhanced network
infrastructure
I gave you slides;
how do I get to
see these?
We’ll send you a link
that you can open with
your webbrowser
Cool!
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Am I doing digital pathology yet?
• Whole Slide Imaging
– A technique
– Get a scanner
– Generate LOTS of data
– Easy
• Digital (histo)pathology
– A method,
• a way of thinking
– Workflow management,
integration
– USE the data
• valorization
– Hard
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So you want to do digital pathology?
Education
Biobanking
Second
opinion
Primary
diagnosis
Research
QA
Start small; select one
use case; implement it
RIGHT; scale and build
on your success
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Why do we build biobanks?
– Show-case for
patients and samples.
– Facilitates patient
selection for studies.
– Permanent record of
cases allows
retrospective
validation of studies.
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Opportunities for digital pathology
• Without digital histopathology: • With digital histopathology:
I’m looking for breast
tumor tissue
Does the sample
contain cancer cells
Is it in situ or
invasive?
Is it hormone-
responsive?
I’m looking for breast
tumor tissue
Does the sample
contain cancer cells
Is it in situ or
invasive?
Is it hormone-
responsive?
Sure; glad to help
Just trust us
Just trust us
We don’t have that
information
Sure; glad to help
Have a look at the HE
Have a look at the HE and
the immunostains
(p63 – calponine)
Have a look at the
immunostains and the fluo
data (FISH)
Fidelity increases, confident about
requests, investments pay off
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Valorization through digital pathology
As you add more layers of
data and move further
down the pyramid, the
value of the initial sample
in the biobank increases
and the biobank as a whole
is likely to prove more
useful.
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Step 2: image analysis
Step 1: find tissue
(Based on work by J. Watson, Pathology Visions meeting 2012)
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Step 2: image analysis
Step 1: find tissue
Step 2: locate the islets
(Based on work by J. Watson, Pathology Visions meeting 2012)
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Step 2: image analysis
Step 1: find tissue
Step 2: locate the islets
Step 3: quantitate insulin
(Based on work by J. Watson, Pathology Visions meeting 2012)
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The result: intelligent querying
I’m looking for pancreatic
tissue from a patient with
recent onset diabetes and a
susceptible HLA-DQ
genotype. At least y% of the
islets still have to contain
insulin-producing cells
Here you go
28. Innoviris portal introductie
• Thank you for taking the time to review these
materials
• Contact me at yves.sucaet@usa.net to continue
the conversation
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Acknowledgements
• Diabetes Research Center, VUB
– Yves Sucaet
– Silke Smeets
– Stijn Piessens
– Peter In’t Veld
• Dept of Pathology, UZ Brussel
– Wim Waelput
– Ramses Forsyth
CMI
