Digital Pathology: the Dutch Perspective

Digital pathology: The Dutch perspective

Paul J van Diest, MD, PhD Professor and Head, Department of Pathology University Medical Center Utrecht PO Box 85500, 3508 GA Utrecht The Netherlands [email protected] Professor of Oncology Johns Hopkins Oncology Center Baltimore, MD, USA Notice of Faculty Disclosure

In accordance with ACCME guidelines, any individual in a position to influence and/or control the content of this ASCP CME activity has disclosed all relevant financial relationships within the past 12 months with commercial interests that provide products and/or services related to the content of this CME activity.

The individual below has responded that he/she has no relevant financial relationship(s) with commercial interest(s) to disclose:

Paul J. van Diest, MD, PhD

Disclosures

• member of advisory boards of Roche, Sectra, Philips (unpaid) • client of Hamamatsu, Sectra, Visiopharm, Leica, Aurora, Philips (paying heavily) • test scanners from Philips and Roche (no contract, no fee) • joint research projects with Philips

UMCU Why The Netherlands?

• “bunch-a-crazy dudes”

• innovation is our middle name

• not bound by too many rules and EU-FDA

• strong believe in advantages in digital pathology Advantages of digital pathology

• no more case assembly in the lab efficacy • quicker diagnostics efficacy • easy and more accurate measurements and counting patient safety/efficacy • better overview of tissue present patient safety • flagging missing slides patient safety • tracking viewing patient safety • automatic linking of images/reporting/LMS patient safety • MDM: quicker preparation, anywhere, show images efficacy • easier making annotations efficacy • easier taking snapshots efficacy • no more slide searching efficacy • no more archive digging efficacy • multiple observer viewing efficacy • quicker and easier consultation patient safety/efficacy • quicker revision efficacy • integration of image analysis patient safety • remote digital diagnostics (including consultation) patient safety/efficacy • integration with radiology patient safety • integration of images in EPF clinician satisfaction • allows working paperless environmental • better ergonomics pathologist satisfaction • teaching is easier and better appreciated student satisfaction Workspace flexibility

• Diagnostics at home, on the beach, at conferences • Less office space needed • Remote frozen section diagnostics Pittsburg UPMC

Positions open for residents in pathology:

The medical specialty where you no longer need to get out of bed The Dutch digital pathology landscape Leiden Hengelo

Rotterdam Nijmegen

Heerlen The Dutch perspective

• 2 labs with full digital diagnostics workflow – UMC Utrecht – Labpon Hengelo • 1 lab with partial digital diagnostics workflow – Heerlen • 1 rogue pathologist working digitally • 2 consortia with a digital network – Den Bosch/Nieuwegein/Arnhem – Alkmaar/Zaandam/Hoorn • 7 academic centers with scanners

 16 labs with digital pathology infrastructure  and a lot more working on it! The Dutch perspective

Vendors

• Philips

• Sectra/Hamamatsu

• 3-D Histech

Can we just do this?

• No FDA in Europe

• CE-IVD suffices

• Internal validation required

• No professional guidelines (CAP)

UMCU digital diagnostics validation

1. Mitosis Counting in Breast Cancer: Object-Level Interobserver Agreement and Comparison to an Automatic Method. PLoS One. 2016 Aug 16;11(8):e0161286. 2. Validity of whole slide images for scoring HER2 chromogenic in situ hybridisation in breast cancer. J Clin Pathol. 2016 May 9. 3. Improved quality of patient care through routine second review of histopathology specimens prior to multidisciplinary meetings. J Clin Pathol. 2016 Oct;69(10):866-71. 4. Whole slide images for primary diagnostics of urinary system pathology: a feasibility study. J Renal Inj Prev. 2014 Dec 1;3(4):91-6. 5. Evaluation of mitotic activity index in breast cancer using whole slide digital images. PLoS One. 2013 Dec 30;8(12):e82576. 6. Whole slide images for primary diagnostics of paediatric pathology specimens: a feasibility study. J Clin Pathol. 2013 Mar;66(3):218-23. 7. Whole slide images as a platform for initial diagnostics in histopathology in a medium-sized routine laboratory. J Clin Pathol. 2012 Dec;65(12):1107-11. 8. Digital slide images for primary diagnostics in breast pathology: a feasibility study. Hum Pathol. 2012 Dec;43(12):2318-25. 9. Whole slide images for primary diagnostics in dermatopathology: a feasibility study. J Clin Pathol. 2012 Feb;65(2):152-8. 10. Whole slide images for primary diagnostics of gastrointestinal tract pathology: a feasibility study. Hum Pathol. 2012 May;43(5):702-7.

• double workflow for 2 years Digital diagnostics validation

Digital pathology diagnostics

YES WE CAN!!!!!!!!!!!! Pathology Image Exchange (PIE)

 Growing digital pathology landscape

 Increasing need of digital lab2lab communication

– Subspecialization within regional networks – Covering superspecialties between academic centers – Revisions – Consultations – Expert panels – Research – Teaching Subspecialization between regional labs

• Hematopathology, soft tissue pathology, cytology

Lab A

Lab B Lab E

Lab C Lab D Top expertise Dutch academic centers Covering areas between academic labs

Academic A

Academic Academic D B

Academic C Revision

When referring patient, reassess pathology material

• Quality control • Reformulate results in local and up to date jargon • Compare to new material • Material for demo at multidisciplinary meetings • Further testing

• Volume ~ 27.000 per year in The Netherlands

Consultation

Second opinion from collaegue in a difficult case

• Patient stays at original hospital

• Volume ~ 10.000 per year in The Netherlands

Consultation by regional labs

Lab A

Lab H Lab B

Lab G academic Lab C

Lab F Lab D

Lab E regional Consultation by regional labs

Academic A

Academic Academic D Lab A B

Academic C national Consultation by regional clusters

Lab A

Lab B Lab E

Lab C Lab D

academic regional Consultation by regional clusters

academic Lab A academic A B

Lab B Lab E

Lab C Lab D

academic academic C national D Logistics revisions and consultations

• Dig up slides from archive or desk pathologist • To administrative office Lab A • Print report • Wrap • To post office

• From post office to department • Unwrap Lab B • Register • Assess • Make report Logistics revisions and consultations

• Print report Lab B • Wrap report and slides • To post office

• From post office to department • Unwrap • Report to pathologist Lab A • Append to report • Slides back to the archive Logistics revisions and consultations

• Process takes 3-14 days (50% > 4 days) • Patient has to wait for definitive result and treatment • Stress, loss of productivity and quality of life

• Optimal mail logistics: process  2 days

• Digitally: same day?

Logistics digital revisions and consultations

• Scan slides • Upload to server Lab A • Message through PALGA to other lab

• Log into server • Assess Lab B • Make report • Report to requesting pathologist through PALGA

 Done on the same day Panels

• 6-15 pathologist and residents

• Travel for many kilometers

• Often during rush hour/traffic jams

• Hugh loss of productivity

• Frequency 1/month Research

• Unlock biobanks

• Revisions for clinical trials

Teaching

• Case mix differs

• Sharing wiki of rare cases

• Sharing wiki of classic cases

Patient safety

• Dutch national pathology archive • All labs connected since 1990 • Unique infrastructure for national pathology initiatives Revisions and consultations central solution

message message

Lab A Lab B

image Log in upload Panels central solution

message message Pathologists

Pathologist A B Lab A C D image log in E upload F ….. Revisions and consultations decentral solution

message message

Lab A Lab B

message message Pathologists

Pathologist A B Lab A C D E Log in Log in F portal ….. Professional architecture

Lab A Lab B

IMS 17. Request images 18 Image Repository . View (Key /Recieve Images )

1 . 2 (Repository / Source) Request images . Images

4. Upload images to PIE Consumer 12 . Show Images and Data 6. Done (Key) Uploader 5. Register image in PIE Index 13. Retrieve locations + Data Location (Key 3. Upload images ) 14. Image Done 15 7. 16 . Retrieve Medical Data . PIE Revieve Medical Data Medical

Data (Index)

8 LIS . Instruct Kern U 10 . Register data in PIE Index LIS ( Key

Medical )

Data

- DPS 11. Send Request

Lab2Lab 9. Send Request (End-To-End Encrypted) (Secured Network) Medical Kern U-DPS Data Kern U-DPS (+ Data Repository) Central vs. decentral solution

Central Decentral Security difficult very difficult Storage capacity low? none Upload time high none Development tough very tough Initial costs high very high Running costs ?? >?? Hybrid solution?

• Temporary?

Central  decentral

• Permanent? Tender issues

• Must haves

– Speed – DICOM – Security – Uptime – Connections PALGA, LMS, UDPS/Sympathy etc – Storage Tender issues

• Assets

– Video? – Sound? – Image analysis? – Speech recognition? – MDM tool? – Mobile device functionality? Finances

• One off costs

– NVVP – PALGA – IKNL – SKMS

• Running costs

– IKNL – Pathology labs (savings!!!!) Future

• Upscale to international?

• Central storage? The Dutch image analysis landscape Leiden Hengelo

Rotterdam Nijmegen

Eindhoven

Heerlen Dutch image analysis consortia

• UMC Utrecht/Technical University Eindhoven

– Nicholas Stathonikos/Paul van Diest – Mitko Veta/Josien Pluim

 Breast cancer grading

• UMC Radboud/UMC Utrecht/Hengelo

– Jeroen van der Laak – Quirine Manson/Paul van Diest – Alexi Baidoshvili

 Metastases finding/immune infiltrate quantification Mitoses detection in breast cancer Nuclear segmentation in breast cancer Nuclear segmentation in breast cancer ER/PR HER2 Image analysis on whole slide images Detecting lymph node metastases in breast cancer Borderlands of digital and molecular pathology Integration of image analysis

Example of fully integrated mitoses recognition algorithm

• Automatic kick in based on data mining of LMS and PALGA • Runs in the background • Finds the slides containing tumor • Segments the tumor • Finds possible mitoses • Shows heat map of possible mitoses • Visually confirm most mitoses rich area • Visual check or count in defined area The Dutch perspective?

Digital Pathology for all by the year 2025! Acknowledgements

Marina Tri Nguyen Nicholas Jeroen van Josien Pluim Mitko Veta Verdaasdonk Stathonikos der Laak Digital pathology UMCU 2016

The next step

• new bulk storage (EMC, hospital wide, incremental) • new faster scanners (Hamamatsu) – fluorescence – big slides – z-stacks for cytology – quality control of scans, automatic rescan • upfront scanning in the lab – all slides digitally available – all MDMs digital – no more slide searching – allows digital diagnostics • worfklow platform (Sectra) • implement image analysis (Sectra/Visiopharm) Digital pathology: the UMC Utrecht 2016 solution

scanning macro imager

order form scanner

database LIS VNX Image/data server HIS

U-DPS

PATHOLOGY

storage

RADIOLOGY pathology users clinical users Scanners

140 slides per hour during peak production

~1400 slides per day

cytology big slides fluorescence frozen sections/priority System design

Saltro PACS worklist and desktop sync with UDPS PALGA VPN

U-DPS PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

ORM exam info and Sectra Core LIMS status updates ImageServer/s Finalist Image import NAS/SAN Analysis performed and show result? request ID, block & stain Import Service(SPIS) Technician prepares and stores results for pathologist

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides System design: connections

Saltro PACS worklist and desktop sync with UDPS PALGA VPN Sectra core U-DPS PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides System design: connections

Saltro PACS worklist and desktop sync with UDPS PALGA VPN slide

U-DPS archive PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides System design: connections

Saltro PACS worklist and desktop sync with UDPS PALGA VPN pathology

U-DPS reporting PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides System design: connections

Saltro PACS worklist and desktop sync with UDPS PALGA lab VPN management U-DPS system PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides System design: connections

Saltro PACS worklist and desktop sync with UDPS PALGA VPN scanners U-DPS PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides System design: connections

Saltro PACS worklist and desktop sync with UDPS PALGA VPN hospital information U-DPS system PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides System design: connections

Saltro PACS worklist and desktop sync with UDPS PALGA VPN image

U-DPS analysis PACS worklist

ChipSoft HiX and ImageServer/fs ILM Cloverleaf ORM status update EMC iSilon Rules

Aperio Archive Image analysis

Launch from viewer

Slide Scanners

Slides Sectra is watching you….. Sectra is watching you…..

Uptime > 99.9% Implementation process

• Hardware

• Software

• Lab issues

• Workspace

• Change management Implementation: hardware

• VNX server cluster hosting the workflow – Stand alone – Integration with Radiology later

• Network connections and switches

• Computers – Graphics cards – CPU speed – Big screens

• Climate control – Temperature, noise, ozon

• 2-D barcodes Implementation: software

• Connections

– Integration with PALGA – Integration with G2 speech recognition – Integration with LMS – Integration with bulk storage – Integration with Radiology PACS

• Smart storage

– 40x  20x

• Conversion of old Aperio images to DICOM Implementation: lab issues

• Slide production

– Perfect central mounting – Restrictive mounting – No glue remnants (Neoclear  xylene) – Quick slide drying

• Workflow

– Quality control – Develop various scan protocols • single layer vs Z-stacks • HE vs. special stains/IHC/defatted • big slides • fluorescence – Lean Implementation: lab issues

• Case assembly and release

– Filling folders – Incomplete cases

• Double workflow (temporary)

• Adapt LMS

– “Wanna see the slides” button – “Rescan slide” button Implementation: workspace

• Screens

• Gizmos Storage

• Short term storage on the scanner

• Mid-term storage on the image server

• Long term storage

– UMCU: EMC Isilon solution (hard disk based, backup) – 800 TB of image data – seven years archive – scalable – permanent

Change management

• Clear mission and vision – Explain the why • Regular plenary meeting and email updates • Dealing with dinos – Big bang vs. smooth transition – Convince yourself – Incentives – Residents • Training – Pathologists – Residents – Technicians – Secretaries • Working groups – involvement! – influence Project management structure

End responsibility project Steering Allocation resources committee Final decisions Escalation channel Control Project organization Monitoring planning and deliverables Decisions Project group Planning, coordination, communication Create training plan Safeguard issues and risks Working Rapport to steering committee Define acceptance criteria group Create test plans quality Coordination SOPs Coordination acceptance tests

Working group Working group Working group Working group digital workspace image analyse workflow technology

Ergonomics workstation Architecture and integration Test image analysis software Workspace design Processes Hardware Advise on changes PACS Workflow, worklist, viewer Rearrange lab to house scanners Storage (archive) Integration LMS Storage Perform acceptation tests Installation PACS & Scanners Perform acceptation tests Roll out clients Emergency procedures 2D Barcodes Define acceptation criteria Perform acceptation tests Roll out clients, install workspace Backup, Recovery & Monitoring Migration Aperio images Perform acceptation tests Functional PACS maintenance Chat Our new workflow

Thumbnails of slides associated to Worklist current case folders Reporting Very fast module viewer

List of current & Overview of prior submissions Request slide form Thumbnails Annotations and measurements Changing slides Viewing slides side by side Our new workflow Our new workflow Our new workflow Ki67 counting Ki67 counting Is it working?

• we have gotten used to it

• we are addicted to it!

Advantages of digital pathology

• no more case assembly in the lab • quicker diagnostics √ • easy and more accurate measurements and counting √ • better overview of tissue present √ • flagging missing slides • tracking viewing • automatic linking of images/reporting/LMS √ • MDM: quicker preparation, anywhere, show images √ • easier making annotations √ • easier taking snapshots √ • no more slide searching √ • no more archive digging √ • multiple observer viewing √ • quicker and easier consultation √ • quicker revision √ • integration of image analysis • remote digital diagnostics (including consultation) √ • integration with radiology • integration of images in EPF • allows working paperless √ • better ergonomics √ • teaching is easier and better appreciated √ Issues to solve

• cytology implementation • (birefringence) • optimize viewer (tracking viewing) • sweep • teaching new residents to use the microscope • keeping storage affordable

• nationwide consultation and revision • full integration of image analysis • integration with radiology • remote digital diagnostics business Business development Better demo gizmos The business case

A business case

A lot of words…. A lot of numbers…. To convince somebody else…. That in the end you will pay everything yourself!

The business case

So how much do we spend?

About…………….

The brave new digital pathology world?

Business case?

• efficacy in pathology labs goes up – no more slide searching – no more slide sorting – no more sending slides around – quicker diagnostics – quicker consultation – quicker MDMs – flexibility in diagnostic work • less budget needed for microscopes and maintenance

 will that save enough to pay for digitization????? The brave new digital pathology world?

The greater good?

• quality of pathology diagnoses ↑  patient safety ↑ • quality of pathology diagnoses ↑  health care costs ↓

– will save money on ineffective treatment – will save money on complications

 reallocation of budgets  enable investments in digitization of pathology labs

PATHOLOGY IS WORTH IT!!! Shifting budgets is the way to go! Forget about the business case!

• efficiency goes up • quality and patient safety goes up • flexibility goes up • employee satisfaction goes up • business will increase • teaching is more and better appreciated • not that much money (3% of our budget, including storage)

DON’T THINK TOO MUCH Digital pathology UMCU 2015

• Scanners written off • Tape archive full and written off • No cytology • No fluorescence • Hardly telerevision/teleconsultation • Not all MDMs done digitally • Still slide searching, which could be in the scanner! • No quality controls of scans, error rate 2-4%

 Time for the next step!!!!!!!!!!!

Consultations, revisions: PIE

message message

Lab A Pathology Image Lab B Exchange

images Log in Slide panels: PIE

message message Pathologists

Pathologist A B Lab A C D beelden inloggen E F …..

Optimal, future proof platform for safe exchange of digital images between Dutch pathology labs

 Rapid, low threshold revision, consultation, panels  Increase quality of diagnostics

Mitoses detection in breast cancer Integration of image analysis

Wish list

• Nuclear area • Metastases finder • Immune infiltrate quantification • Tumor vs. stroma quantification • IHC membrane scoring • IHC % positive nuclei scoring • etc