1. The Pathology Imaging Engine Histology Workflow with WSI John Gilbertson MD Associate Chief of Pathology Director of Pathology Informatics Massachusetts General Hospital Associate Professor of Pathology Harvard Medical School HARVARD MEDICAL SCHOOL Pathology Visions 2010 October 25, 2010 San Diego, CA

2. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 I have no personal financial relationship with any company* However, I am Associated Chief of Pathology and Director of Pathology Informatics in a Department that does significant research and co-development with industry Names that we work with and I might mention today include Kurabo, Sony, Olympus, 3D Histech, Corista, Bioimagene, Hamamatsu and Sunquest* I am overall PI on a collaboration agreement with Philips All conflicts are disclosed and compliant with Partners and Harvard ethics rules

3. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 The Massachusetts General Hospital and Sunquest Information Systems, Inc. have a long term collaboration agreement to co-create new modules of Sunquest’s AP LIS product (Sunquest Copath) MGH and Sunquest are committing resources to the co-development It is done under Sunquest’s Software Development Environment The products of the collaboration will be commercialized by Sunquest and made generally available to Sunquest clients in future versions of Sunquest Copath MGH will receive a royalty stream back from Sunquest depending on the commercial success of the software and the amount of MGH resources used in its creation I am Sunquest advisory boards

4. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Today’s Talk: The potential of WSI and Digital Pathology The importance of histology (slide quality and variance) in WSI The importance of maintaining histology throughput when implementing large scale, clinical WSI The use of process mapping, modeling and computer simulation in the planning for WSI in the histology lab

5. John Gilbertson: Monday July 25, 2010Pathology Visions 2010

6. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Computational power and network connectivity are the driving forces of change in the modern world They have changed every industry they have touched: they should change pathology When pathology is able to digitize all of its slides, automatically, rapidly and with high fidelity, it will be able to apply computational power and network connectivity to study of microscopic morphology and the practice of anatomic pathology

7. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 WSI is an enabling technology for “putting Pathology on the right side of Moore’s Law” Exponential decrease in computational cost – for decades

8. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 What if the rest of the medicine is taking advantage of growing computational power and network connectivity and pathology isn’t? … It will not end well Not going “digital” is not an option

9. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 But

10. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Digital pathology isn’t really digital… There still is the slide … …and the stain Stained slides are the subject of the WSI process… …but they have been an unwilling subject

11. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 They are designed to be looked at by eye under the microscope They were never designed to be imaged

12. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Slides: for your eyes only Many of them Rapidly By hand

13. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 In most laboratories, the glass slide has vary high variance

14. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Machines hate this Things that were never a problem for the human hand and pathologist’s eye were problems for the robotic actuator and the digital camera

15. John Gilbertson: Monday July 25, 2010Pathology Visions 2010

16. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Slides are active participants in the digitization process

17. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Slide variance is a major factor in imaging failures and imaging speed

18. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 When robots work with robots… Better slides  Images Faster image capture speed Staining Optics & Digitization Workflow and Dataflow Infrastructure (LIS) Cutting & Adhesion Processing & Embedding Image Analysis Grossing Archive Interpretation Lower variances – faster focus Lower variance – fewer failures (unacceptable focus, tissue finding or mechanical failure) Pathology Imaging Engine

19. John Gilbertson: Monday July 25, 2010Pathology Visions 2010

20. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 High slide quality, low variance Yagi et al

21. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Yagi et al

22. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Yagi et al

23. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Quantitative QA: Better images  Better Slides Staining Optics & Digitization Workflow and Dataflow Infrastructure (LIS) Cutting & Adhesion Processing & Embedding Image Analysis Grossing Archive Interpretation Bautista PA, Yagi Y Detection of tissue folds in whole slide images. Conf Proc IEEE Eng Med Biol Soc. 2009:3669-72. Pathology Imaging Engine

24. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 There is a trend to incorporate robots and quantitative, Imaging- based QA at every step of the histology process This is great for imaging, histology and anatomic pathology

25. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Throughput

26. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Digitization adds steps (image, check, redo) We still have to push a lot of slide through histology – fast Digitization might make the entire process (gross – histology – signout) faster…. … large scale WSI will not be implemented if it significantly slows histology throughput

27. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Anatomic Pathology Workflow We have a real interest in AP productivity –Our pathologist’s time is the more valuable resource we have –This is true world wide –Potential Market is increasing… –Case complexity is increasing… –Need for documentation is increasing… –Research opportunities are increasing… –Pathology satisfaction is declining… –High turnover in Histology Labs –Aging infrastructure

28. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Anatomic Pathology Workflow We have a specific interest in AP productivity –Sunquest collaboration requires the implementation of a new AP LIS –Axiom: Bad workflow eats good software for lunch –Axiom: Don’t prop up bad workflow with new software All these things give us a very good excuse to examine our workflow (and infrastructure)

29. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Infrastructure to study/improve productivity Green belts, analysts, techs and engineers (Lean, six sigma, FMEA) Mapping: What is our baseline workflow’ Modeling: Include rates, numbers, times (manually initially) Populated Models: Asset tracking (2011), routing and station protocols (process steps) (2012) Process Laboratory: “A laboratory to study the laboratory” Simulation Software: “What if we make a change” Clinical Laboratory: “Beta Testing” Compare: Scientifically compare the pre- and post states

30. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Current findings Mapping and manual modeling ………………….! 29 major workflows 1000+ hand offs Major Variation (interruptions, etc) Cultural issues

31. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Simulation We began computer simulation of workflow about 5 months ago Commercial simulation software developed for production lines (Lean, Six Sigma and FMEA analysis) We will eventually use of asset tracking data (2011) Decided to began using our current process maps and observations (time studies, red card studies, etc) Our first “test” example, was what would happen if we decided to image all of slides prior to sending the slides to the pathologist

32. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Simulation A story: ~ 4.5 months ago… ~ 3 weeks… ~ 2.5 weeks ago… Developing a simulation of laboratory that does 300 cases and 2500 slides a day, 1200 part types, 29 major processes (and wide variations in each process), 40+ people… is hard ~ 1.5 weeks ago… ~ 4 days ago…

33. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Simulation Data was not bad, it was impossible to understand on PPT Data was not perfect: a lot of excessive waiting time because of steps were modeled. Key points: –Our normal case mix –Begin in the processor (grossing room is a black box) –One input of cases (there is nothing in the lab except this one surge of cases) –Keep our normal number of processing, imbedding, cutting, drying, staining, drying, reconciliation stations –Keep our normal time (and variances) at each station –This was not reality

34. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Simulation Changed size of batches between stations and redo rate. Run the simulation for 0, 1, 2, 3 scanners Scanners imaged at 1-3 minute per slide rtr, Image QA time 0 – 10 minutes Image redo rate 0 – 10%

35. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 3 6 2 2 1 1

36. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Simulation Results - Not based in reality, but useful… Tidal Effect” (traffic jams) but the simulation did not “stop” Batching drives throughput rate – especially in staining/drying –Batches of five slides each, allowed two scanners to image 400 slides (~ 600 – 800 minutes of work) while only adding 19 minutes to the run (redo rate = 0, QA time = 0) Case size drives throughput rate Imaging QA time is a major impact throughput rate (scan time + QA time = ) Imaging redo kills throughput rate especially at rates above 5% or with large cases Elimination of batching, case reconciliation, low QA time and minimum imaging failures are key

37. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Conclusions Digital slides are potentially powerful tools for pathology. Its gets us on the right side of Moore’s Law Pathology imaging begins in Histology, it requires a stained slide Slide quality impacts image quality and scanner specification: High quality, low variance slide result in high quality, high speed images For large scale clinical WSI to be implemented, WSI must not significantly impact the distribution of slides to the pathologist Preliminary simulations at MGH indicate that both workflow changes (especially minimizing batches) and improved image quality (decreased QA time and redos) are important parameters in maintaining high histology throughput with WSI Computer simulations seems useful in evaluating a large number of process in pathology – especially in conjunction with asset tracking

38. John Gilbertson: Monday July 25, 2010Pathology Visions 2010 Conclusions We will be publishing our data so that you can make your own decisions…