The combination of tissue samples and online digital histopathology images can be a major asset in the valorisation of tissue collections. At Brussels Free University (VUB), our biobank data consists of three different datasets: clinical data, brightfield whole slide images, and fluorescence snapshots. A single whole slide imaging (WSI) repository of microscopy slides was set up that could contain all material. The flexibility of modern digital pathology hardware and software solutions allows bespoke solutions to meet individual biobanking needs. A combination of commercial hardware, commercial software, and open source software was used to get this accomplished. Custom coding to connect interfaces was used where needed. Potential users of the tissue bank material can now choose and inspect the tissue and patient characteristics before entering into a collaborative agreement. Researchers can visually inspect a sample first and find out for themselves if the sample really contains the material that they are looking for. Pathologists can gather customised collections of virtual slide material for studying specific phenotypes. Computationally oriented scientists can bypass the (physical) retrieval of material from the biobank, as the digital data by their very nature is reusable by many groups around the world. Whole slide image database repositories add value to legacy biobank and we can see that these “virtual” biorepositories will quickly spread and have the potential to become a new ‘standard of care’ for biobanks.

1. 15-9-2016 pag. 1
Using digital pathology to
enhance a biobank portal
Yves Sucaet, PhD
Diabetes Research Center

2. 15-9-2016 pag. 2
Financial disclosure
• I’m a co-founder and shareholder of Pathomation, one of the
companies mentioned in this presentation

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Presentation outline
• Introduction: Whole Slide Imaging (WSI)
• Current status of WSI at VUB
– Educational tools medical school
– Biobank: retrospective histopathology collections
– Biobank: prospective histopathology collections
• Future plans
– Slide / Data Exchange Research and Clinics
– Image analysis
– Scaling

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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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Once you’re happy…

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VUB result (january 2015)

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Different imaging platforms
• BD Pathway
– TIFF images, 12-or 16-bit per pixel, grayscale, non-pyramidical
– Attovision software
• Zeiss
– ZVI / CZI Images, multiple (fluorescent) channels
– AxioVision Software / ZEN Studio
• Nikon
– ND2 / TIFF images, multiple (fluorescent) channels
– NIS Elements
• Leica / Aperio
– SVS images, brightfield
– Aperio eSlide Manager (formerly Spectrum)
– Aperio ImageScope
• 3DHistech (UZBrussel)
– MRXS, brightfield
– Pannoramic Viewer

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Connecting equipment

9. Innoviris portal introductie
• Taking our first steps
– Trying it out on volunteers (aka students)

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Use case 1: Education

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Use case 1: The first course
• Histology education at http://histology.vub.ac.be (GK, BMW)

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Use case 1: Additional course
• Pathology education at http://pathology.vub.ac.be (GK, BMW)

13. Innoviris portal introductie
• Scaling up
– Doing more than “just” education

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Use case 2: Retrospective collections
Pathologic Anatomy of the Pancreas in Juvenile
Diabetes Mellitus (Diabetes 14:619, 1965).
Willy Gepts (1922-1991)

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Use case 2: archival slides and clinical data

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Use case 2: Retrospective collections
• Currently available: http://gepts.vub.ac.be

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Use case 2: International Collaboration
• http://foulis.vub.ac.be

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Use case 2: slide organization

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Use case 2: meta-data capturing

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Demo
• http://gepts.vub.ac.be
• http://foulis.vub.ac.be

21. Innoviris portal introductie
• Putting our experience to good use
– Digital pathology for the valorisation of a “live”
biobank

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Use case 3: Biobank
– Show-case for
patients and samples.
– Facilitates patient
selection for studies.
– Permanent record of
cases allows
retrospective
validation of studies.

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Vlaamse Biobank (CMI – BBMRI. vl)
• Minimal clinical data (OECD)
• Extended epidemiological dataset
• HLA, auto-immune data
• Images

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Biobank problems
• 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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Use case 3: Biobank (valorization)

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Use case 3: Biobank (inspiration)

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Use case 3: Our own biobank site
http://histosrv.vub.ac.be/dbb

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Use case 3: Biobank “behind the scenes”

29. Innoviris portal introduc
tie
• The VUB digital histopathology ecosystem
– Multiple imaging platforms, multiple users, multiple
applications, multiple portal websites

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The future: Hospital and clinical
• Ongoing evaluation of scanner equipment
– Currently 3DHistech on site
• Case presentation
– “Easy” cases for medical school students (rotations)
– Special cases (multidisciplinary oncology consults)
– Residents in the pathology department
• Collection hosting
– Historical (restrospective) collections
• Students, residents, hospital staff members (don’t need to be
pathologists!)
– Thesis support: collect data, evaluate
• in a uniform, centralized manner
• Fielt study
– 200 cases, to be evaluated by different pathologists for tumor
infiltrating immune cells, tumor cell %, PDL1 IHC staining
evaluation in tumor and micro-environment

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The future: image analysis
Step 1: find tissue
Step 2: locate the islets
Step 3: quantitate insulin

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The future: 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

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A grassroot initiative
• Computational Pathology Workshop – CPW 2016
http://cpw.pathomation.com

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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