Anil V Parwani, MD, PhD, MBA

Transcription

1 The Ohio State University Comprehensive Cancer Center Arthur G. James Cancer Hospital and Richard J. Solove Research Institute Using Digital Pathology for Primary Diagnosis: What All Pathology Labs Need to Know about Technology, Workflow Impact, Clinical Quality, and Financial Opportunity Anil V Parwani, MD, PhD, MBA

2 Objectives of today s workshop Introduction to digital pathology and role in clinical diagnostics and personalized medicine Whole slide imaging, applications and challenges Current state of technology and impact on quality and workflow Expanding the Use of Digital Pathology to Drive Revenue Recognize how artificial intelligence/deep learning is an enabling technology for cancer diagnostics and personalized medicine Future Directions

3 8:00 am 8:10 am Introduction and Goals Overview of Digital Pathology s Current State: Technologies, Systems, Capabilities, Limitations, and Opportunities David McClintock 8:50 am 9:20 am Use Case Academic: Ohio State University Wexner Anil Parwani 9:20 am 9:50 am Lessons Learned in the Use of Digital Pathology at Memorial Sloan-Kettering Cancer Center Victor Reuter 9:50 10:10 am Break 10:10 am 10:40 am Expanding the Use of Digital Pathology to Drive Revenue and Create a Competitive Advantage for Your Lab Dan Angress 10:40 am 12:00 pm Digital Pathology Systems & Services Showcase Each company discusses what its systems/products do and what differentiates them Philips Digital Pathology, Brett Kimball Leica, Kevin Whiteley Inspirata, Mark Lloyd Gestalt Diagnostics, Morgan Wright Thermo Fisher Scientific, John Wellbank 3

4 12:00 pm 1:30 pm Lunch 1:30 pm 2:10 pm Future of Digital pathology and Artificial Intelligence Keith Kaplan 2:10 pm 2:50 pm Digital Pathology Beyond Primary Diagnosis: Integrating Pathology into the Care Team A Workflow Solution to Meet Requirements for Quality Reporting and Patient Outcomes Patricia Goede, Conor Ward 2:50 pm 3:30 pm Panel: Moving Forward with Digital Pathology in Daily Practice: What We ve Learned About Acquiring, Implementing, and Using Digital pathology Systems and Whole Slide Imaging Anil Parwani, Chair; Panelists: Keith Kaplan, David McClintock, Patricia Goede

5 INTRODUCTION

6 IMAGING PROCESS CAPTURE SAVE EDIT SHARE MODALITIES DATABASE APPLICATION WORKSTATION

7 Digital Microscopes Whole Slide Imaging: (WSI)

8 Powerful Microscope = Whole Slide Imaging (WSI)

9 APRIL 13 th 2017 Philips Receives FDA Clearance To Market Philips Intellisite Pathology Solution For Primary Diagnostic Use In The US

10 Time Applications to replace of the WSI at microscope? OSU Primary Diagnosis Digital consultation/2 nd opinion Quality assurance Education Clinical conferences Research Image analysis 12 Deep Learning/Artificial Intelligence

11 REASONS FOR IMPLEMENTING DIGITAL PATHOLOGY 1. INCREASED PRODUCTIVITY IMPROVED INFORMATION MANAGEMENT, WORKFLOW DISTRIBUTION, INTEGRATION OF DATA 2. IMPROVED QUALITY/BETTER MEDICINE QUALITY ASSURANCE, RAPID SECOND REVIEWS, EASIER ACCESS TO SUB-SPECIALIST 3. INCREASE REVENUES INSOURICING (Digital Consults), PULL-THROUGH REVENUES, BRAND RECOGNITION 4. COST SAVINGS CONSOLIDATION, REDUCED COSTS WITH MOVING SLIDES AROUND 5. BECOME AN INNOVATION LEADER IMAGE ANALYSIS/WORKFLOW, COMPUTER AIDED DIAGNOSIS

12 14 DAVID McCLINTOCK

13 The Ohio State University Comprehensive Cancer Center Arthur G. James Cancer Hospital and Richard J. Solove Research Institute Implementing Whole Slide Imaging for Clinical Diagnostics: The Good and the Bad Anil V Parwani, MD, PhD, MBA

14 RESEARCH FUNDS AND SUPPORT PROVIDED BY: Stefanie Spielman Fund for Breast Cancer Research The Department of Pathology

15 Vendors involved with this project

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17 Department of Pathology OSUWMC 80 faculty AP, CP, MP Outreach Experimental Nationwide Children s Hospital (NCH) Sites OSUWMC/James CCC Molecular lab OSU East 3 outreach hospitals NCH 19

18 Clinical Volumes Increasing Surgical Pathology cases 80,000 Approximately 600,000 slides including H&E, IHCs and special stains Approximately 3,000 slides 20

19 Objectives of my talk: Key factors to consider in the implementation of whole slide imaging for clinical use Current state of digital pathology at The Ohio State University Implementation challenges and lessons learnt

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21 Emergence of Whole Slide Imaging: Powerful tools Improved Integration Microscopic and gross findings Clinical data Molecular testing Image analysis Patient care Goals/Outcomes Accurate reporting Integrated reporting Timely reporting Efficiency Better medicine 23

22 Value of Digital Pathology to OSU Improved quality Operational efficiency and load balancing Whole slide imaging Information/imaging management and applications Brand enhancement and pull-through revenue Research, education and innovation Increased revenues Tele-consultation/network development Increased referral for low volume specialties Global medicine- new patients Imaging analysis/predictive algorithms/artificial intelligence 24

23 Whole Slide Imaging Why now? Lack of integrated barcoding/tracking system Lack of streamlined, integrated, high scale scanning interface for enabling digitization of images and image analysis for diagnosis and collaboration Desire for specimen library with annotated clinical data Robust sub-specialty model of sign-out but not being leveraged for increasing opportunities for digital consults Outreach growing, need coverage, backup and quality care Primary Diagnosis was on the horizon; technology no longer a barrier 25

24 Institutional Buy in: Key Result Areas Key Result Areas Impact Digital Pathology Metrics Productivity and Efficiency Workload balance, automation, improved workflow Turnaround time Quality QA program, image sharing, remove site barrier to second opinion # Technical errors # Diagnostic errors Innovation and Strategic Growth New consult cases and partners Research opportunities (image analysis and predictive algorithms) # Consult cases # Partner institutions New tools # Patents, grants Service and Reputation 26 Patient satisfaction Leadership in area Branding Satisfaction scorecards # Papers/talks Financial Performance Revenue from new cases/patients Cost savings Pull through revenue

25 Building Institutional Support- Faculty is the Key Early adopters/supporters Low hanging fruit- barcoding Early wins- retrospective cases now available, some frozen sections from home, tumor boards What motivates each of them Efficiency Teaching Research (projects using image analysis) Frozen sections or weekend stat biopsies (home) Financial incentives 27

26 Faculty- Why Should I Learn it? Why not? 28 It is new No RVUs/shifts It will slow me down I will never get to go home! It will lead to decreased academic time Will it take my job/future security?

27 Faculty- Why Should I Learn it? It is innovative and exciting No lost, broken slides- less time wasted organizing, looking for slides I can show a case without leaving my office Multiple faculty can use same case for research/teaching at same time Easy way to photograph and store teaching/research slides Algorithms will help me do my job better/faster Financial incentive- increase salary or research money? Research and collaboration opportunities 29

28 What if pathologists used digital slides instead of glass slides?

29 Digital slides will introduce new costs! New capital equipment Scanners Servers Storage (terabytes per week! But storage is cheap) BARCODES are a MUST

30 Digital slides will IMPROVE my workflow by Direct interface to LIS Sharing cases with consultants, clinicians Tumor conferences Flagging cases Controls instantly available Digital slides will IMPROVE my TAT by automatically distributing workload Glass slides go directly from cover slipper to scanner to proper pathologist Cases are instantly available upon scanning previous cases are instantly available 32

31 VISIO N PLAN BUY- IN FINANCI AL Our Journey to implement digital pathology

32 Preparing for a SLIDELESS Lab

33 Implementation: Key Points Consider Identifying the applications/uses Creating a digital pathology resource center Evaluation and selection of various WSI systems Workflow considerations Adoption of WSI Validation of the WSI systems Training GO LIVE!!!

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35 Many different WSI Imaging Devices

36 els e What do I need? Workflow Design & Planning Systems Integration Faculty & Staff Training Validation Studies Experienced Team

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38 Current state Future state 40

39 Adoption of Digital Pathology Today: What are the barriers? Regualtory Issues FDA, CAP etc. Workflow Issues Lack of automation and technology: Current state Integration with LIS Adoption of technology Financial Issues Cost of Technology Cost of Implementation

40 APRIL 13 th 2017 Philips Receives FDA Clearance To Market Philips Intellisite Pathology Solution For Primary Diagnostic Use In The US

41 What is the difference? REGULATES REGULATES Manufactures of Medical Devices/ *note: FDA may soon regulate laboratories Vendors conducting Lab Developed Tests Laboratories*

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43 WORKFLOW CONSIDERATIONS MULTIPLE INTERACTIONS MAY OCCUR WITH THE WSI SYSTEMS Patient Specimen to Pathology Accession Grossing MAKE THE USERS UNDERSTAND THE SIGNIFICANCE OF THE WSI PROJECT Case assembly & slide delivery Histology Pathologist review

44 COMBINING MORPHOLOGY WITH PATIENT INFORMATION: AP-LIS INTEGRATION IS KEY AP-LIS Pathology Workstation

45 pathology workflows and COCKPIT

46 INTEGRATED WORKFLOW Workflow server APLIS Pathologist Workstation

47 Message out of Copath at Order: Date formatted: 3/14/ :01:13 Status: SEND Date sent: 3/14/ :01:21 Sequential Number: 1975 MSH ^~\& COPATHPLUS IMAGER ORM^O P 2.3 PID ^^^1 TEST^BRUTUS M ORC NW S17-27 ER OBR 1 S17-27 S17-27_1_1_1 Breast, mastectomy, no lymph nodes^^hei OBR 2 S17-27 S17-27_2_2_1 Lymph node, sentinel^^hei OBR 3 S17-27 S17-27_2_3_1 Lymph node, sentinel^^ae1/ae3

48 Messages into LIS from WSI scanner after scanning complete Date In: 3/14/ :01:23 Status: ok Date Processed: 3/14/ :01:34 Sequential Number: MSH ^~\& SQ SQTUCSON COPATH DADD ORR^O P 2.2 PID PV1 ORC NA S17-27^CoPath C/S OBR S17-27^CoPath C/S

49 Digital Pathology moving forward- Primary Diagnosis (GO LIVE MARCH 1st 2018) Telepathology (LIVE) Digital consults (OPEN FOR CONSULTATION) Resident training (digital slide sets) (LIVE) Clinical/Teaching conference (LIVE) Archiving rare slides (cytopathology, frozen sections) (LIVE) Proficiency testing (CAP PIP slides) (LIVE) Image analysis (LIVE) Research- Many pathologists are working on projects (LIVE)

50 52 GO LIVE MARCH 1 st 2018 First case Benign Prostate Biopsy

51 Inspirata Review Workstation and barcode printers HTTPS 1Gb/s Inspira ta Cockp it + Philips IMS OSU Digital Pathology Workflow System 10 Gb/s Tier 1 Online Storage 1 Gb/s Philips UFS OSU Data Center Network NAS storage OSU Datacent 1 Gb/s Scanning Center Philips UFS AP-LIS server Philips UFS 1 Gb/s Philips UFS 1 OSU network Gb/s Philips UFS 1 Gb/s HTTPS 1Gb/s Inspirata Cockpit Workstations (n=55) Philips UFS 1 Gb/s Philips UFS Pathologist Lab & 1 Gb/s 1 Gb/s Huron LE 120. Exter nal Net work Remote Support

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54 SCAN LAB AND INNOVATION LAB

55 Scan Lab The James Cancer Hospital and Solove Research Institute Room Bank of seven (7) highthroughput Philips UFS and one (1) Huron LE 120 slide scanners; Leica LVI (3), Sakura (2), Hamamatsu (1), Aperio XT (2) Fully staffed 3 shifts/day (24hr scanning) ~ Thousands of slides/day capacity; 0.4% rescan rate

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58 Innovation Lab

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60 THE OHIO STATE CONSULTATION PORTAL ENHANCING CLINICAL DIAGNOSTICS

61 Liposarcoma

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67 69 Rescan Rates and Common Errors Evaluated over 350,000 Whole Slide Images Our scan volumes to thousands of retrospective slides per day- averaging over 13,000 per week Studying rescan rates and common errors. Our experiences running multiple slide scanning

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69 WHOLE SLIDE IMAGING PROBLEMS WITH SCANNING 71

70 WHOLE SLIDE IMAGING PROBLEMS WITH SCANNING 72

71 WHOLE SLIDE IMAGING PROBLEMS WITH SCANNING 73

72 WHOLE SLIDE IMAGING PROBLEMS WITH SCANNING 74

73 WHOLE SLIDE IMAGING PROBLEMS WITH SCANNING 75

74 WHOLE SLIDE IMAGING PROBLEMS WITH SCANNING 76

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76 78 Over 400,000 WSIs were acquired and a total of 7,315 errors were recorded representing 1.82% of all scans.

77 Digital Pathology Scanning Center Pilot went live on May 25 th Over 500,000 retrospective slides scanned and associated with LIS Cases: All of 2015, 2016 and 2017 Cancer cases are now online

78 TWO IMPORTANT DEVELOPMENTS SINCE WE WENT LIVE WITH WHOLE SLIDE IMAGING SWITCHING LIS- MOVING TO BEAKER MOVING TO A NEW CENTRAL LAB WHICH WILL BE OFF-CAMPUS 80

79 LIS WSI APPS 81

80 PATHOLOGY : TRANSFORMED Predictive assays ENHANCE PATIENT CARE Genome Sequencing for a specific signature Histology-based for a aggressive phenotype PIPELINES OF DATA: NEW KNOWLWDGE Ganesan, S., et al. "Computerized Histologic Image-Based Risk Score (IbRiS) Classifier for ER+ Breast Cancer. Cancer Research Supplement 3 (2009).

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82 OSU Strategic Pathology Imaging Roadmap Static Images Patient reports/gross/microscopic Robotic Microscopes - Telepathology WSI-Education/QA WSI-LIS Integration WSI-Primary Diagnosis WSI- Pathology PACS DEEP LEARNING TOOLS/ARTIFICIAL INTELLIGENCE

83 what can we learn from the OSU EXPERIENCE? ~ Planning, planning, planning ~ Be prepared for set-backs ~ Put a robust governance and reporting structure in place ~ You can t do it alone it really takes a village ~ Take everyone along ~ Savor incremental wins ~ Allocate enough time for things to fall in place ~ Need leaders to keep the team focused ~ Communicate and communicate often with all stakeholders

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85 87 Thank You