gilbertson--20100428 Activegolbert-- Overview of ...€¦ · Sony, Olympus, NEC, 3D Histech,...

Overview of Changes in HistologyTechniques, Tools, & Workflow

John Gilbertson MD

Associate Chief of PathologyDirector of Pathology InformaticsMassachusetts General Hospital

Associate ProfessorHarvard Medical School

HARVARDMEDICAL SCHOOL

The Executive War CollegeApril 29, 2010

New Orleans, Louisiana

Disruptive Technologies in Histology & Digital Pathology

John Gilbertson: Thursday, April 29, 2010 Executive War College, New Olreans LA

• John Gilbertson– Massachusetts General Hospital

• Roberta Provencal– Catholic Medical Center,

Manchester, NA

• Mary Anne Haynes– Children’s National Medical

Center, Washington, DC

• Lu Anne Lupfer– Leica Microsystems

• Katja Lehmann– Sakura Finetek

• Theresa Ford– Milestone Medical

• Marco Bellini– Ventana Medical Systems

• Kelsi Currier– Tucson, Az

Conflicts

• 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

• The Laboratory for Pathology Imaging Research and The Laboratory for Pathology Operations Research

• All are disclosed and compliant with Partners and Harvard ethics rules

• Names that we work with and I might mention today include Kurabo, Sony, Olympus, NEC, 3D Histech, Corista, Barco, Bioimagene, Philips, Hamamatsu and Sunquest*

*see next slide

MGH & Sunquest

• On August 24, 2009 the Massachusetts General Hospital, Partners Healthcare System and Sunquest Information Systems Corporation signed a ten year collaboration agreement to co-create modules of a next generation AP LIS as part of an modular AP CP LIS to be marketed and commercialized by Sunquest

• As part of this agreement, both MGH and Sunquest are committing resources to the co-development. MGH will receive a royalty streamback from Sunquest. The size of which will depending on the commercial success of each module and the amount of MGH resources used in its creation

• I am Sunquest advisory boards (unpaid)

MGH PathologyInformatics

Gudewicz Dighe Yagi Wilbur Happel Lewandrowski

• Le• Garniss• Badizadegan• Flood• Higgins• Michaelson

• Misdraji• Tearney• Beckwith*• Kim*• Kuo*

Pathology Informatics 2010Westin Hotel, Copley PlaceBoston, MassachusettsSeptember 19-22, 2010

• I am a pathologist

• The stained slide is the best, most powerful way medicine has to interrogate the nature of disease in tissue

Histopathology

Foundation of knowledge

Histopathology

How histology labs will save the world

This is not an implemented system!

Staining Optics &Digitization

Workflow and Dataflow Infrastructure (LIS)

Cutting &Adhesion

Processing& Embedding

ImageAnalysisossing Interpreta

Pathology Imaging Engine

• Imaging begins in Histology• WSI digitizes it• WSI is one of many AH robots

Histology and imaging are one…

Staining &Drying

Optics &Digitization

Cutting &Adhesion

Pathology Imaging Engine

Whole Slide Imaging

• If we could digitize all of our slides, rapidly, easily and at high resolution, then we could apply computational power and network connectivity – the drivers of efficiency, communication and discovery in the modern world - to the study of morphologic biology and practice of anatomic pathology

We took the Slide (histology) for granted: Skill and Variance

Things that were never a problem for the human hand and pathologist’s eye were problems for the robotic actuator and the digital camera

Upstream and Downstream

We found that some of the most important problems/failures of WSI devices (tissue finding, focusing, etc), had root causes in

histology

Accessioning Grossing Histology Sign out

Surgery Report

5um3um

Upstream and Downstream

Accessioning Grossing Histology Sign out

Surgery Report

WSI developers spend a lot of effort compensating for upstream variations (technical problems in slides). Upstream variation caused trouble in Slide Handling, Tissue Finding and Focus whichlimited Capture Speed, Image Quality and Device Throughput

• A robot for every step – could we minimize the variance at the source?• Better slides better images with less effort…

Better, faster, cheaper imagers?

Cutting &Adhesion

High slide quality, low variance

Yagi et al

Higher Quality Images

• Better images Better Slides• Quantitative QA

Cutting &Adhesion

Bautista PA, Yagi YDetection of tissue folds in whole slide images.Conf Proc IEEE Eng Med Biol Soc. 2009:3669-72.

Quantitative QA

• Lower Variance, Quantitative QA• Better slides Images• Faster image capture speed

Cutting &Adhesion

• Lower variances – faster focus• Lower variance – fewer failures

(unacceptable focus, tissue finding or mechanical failure)

Throughput

Continuous Flow

5:00 AM 4:00 PM

2400 Slides / Day

Sign out

3 Devices1 Minute / Slide / Device

Batch Mode(then image)

Cases are collectedthe day before

4:00 PM

2400 slides / day

Sign out

WSI3 Devices

1 Slide / Minute / Device

Histology3 Lines

1 Slide / Minute / Line

~ 13 hours ~ 1 Additional Minute

Cases are collectedand entered in the process

Pathology on the right side of Moore’s Law…

• Lower Variance, Quantitative QA• Better Slides Better Images • Minimal Impact on Throughput

Cutting &Adhesion

• Ubiquitous, high quality digital slides on which we can apply growing computational power and network connectivity

Conclusions

• For most people histology is about getting slides to pathologists and automated histology is about containing or decreasing cost

• But there is more, it as also a area though which we can change the dynamic of the field (pathology)

Conclusions

• Without digitization, what pathology can do will be limited by our ability to physically manipulate and distribute slides and the time (and eyes) of our pathologist

• Molecular Medicine• Personalized Medicine• Baby Boomers• Global Opportunities

• 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

• Imaging is part of histology• Better Slides Better digitization

Cutting &Adhesion

• Ubiquitous digital slides• A new dynamic in pathology

Conclusions

Cutting &Adhesion

Surgery Collection Transport AccessioningArchive Research

Intel 1965

• The goal this morning was to connect automated histology to digital pathology

• To give a prediction of how histopathology might look in 5 – 10 years

• We are thinking about this…

• We are stable, strong…• We are not “agile”• We are worried about disruptive

technologies…

“Ether Dome”, MGH

Will we be displaced?

Will we have the cycles totake advantage?

• We are stable, strong…• We are not “agile”• We are worried about disruptive

technologies…

“Ether Dome”, MGH

Will we be displaced?

Will we have the cycles totake advantage?

Cutting &Adhesion

ImageAnalysisrossing Interpreta

Surgery Collection Transport Accessioning

Archive Research

Clinic

Specially Clinics

RoboticGrossing

AutomatedHistology

ColorNumberShapeSize

CameraDocumentation

MGH Laboratory forPathology Operations

Cutting &Adhesion

This is not “real”

We have an R&D facility that examines the technology,but this is not in our clinical lab

gilbertson--20100428 Activegolbert-- Overview of ...€¦ · Sony, Olympus, NEC, 3D Histech,...

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