Is digital pathology ready for use in routine histopathology? Dr David Snead University Hospitals of Coventry and Warwickshire NHS Trust Coventry UK

Size: px

Start display at page:

Download "Is digital pathology ready for use in routine histopathology? Dr David Snead University Hospitals of Coventry and Warwickshire NHS Trust Coventry UK"

Cornelius Morris
6 years ago
Views:

1 Is digital pathology ready for use in routine histopathology? Dr David Snead University Hospitals of Coventry and Warwickshire NHS Trust Coventry UK

in the history of pathology Johannes Müller (1801 1858).

2 Pathologists and microscopes Rudolph Virchow ( ), by many regarded as the greatest figure in the history of pathology Johannes Müller ( ). Müller was the source from which both histology and cellular pathology arose. He was one of the first to use the microscope in tissue analysis.

3 Pathologists 2010

5 Introduction The transition of glass slides to computerised viewing platforms Whole slide imaging, telemicroscopy, virtual microscopy Based on streaming digital information of images from computer server to a remote viewer Just another way of viewing slides?

6 Charged couple device

7 Digital microscopy Charged couple device (CCD) Tile stitching Line scanning Area scanning x20, x40, x60 magnification Resolution depends on numerical aperture: d=l/2na Microns per pixel UK providers: GE Healthcare (Omnyx), Hamamatsu, Phillips, Leica (Aperio), Roche, 3D Histec

8 Digital Pathology Partially proven Additional laboratory steps to convert slides to digital data Stability dependent on multiple factors Poor image quality on some older systems Limited to the most common applications High set-up and running costs High level of maintenance and support needed to ensure the service

9 Requirements of a digital pathology solution Rapid scanning Integration with the laboratory LIMS Stable Fast data transfer for real time reporting Validation - proven equity to light microscopy Value added tools International standard for digital archiving

11 UHCW activity data 27,000 surgicals 120,00 slides

12 Digital pathology at UHCW Innovation Local pathology network needs Academic potential Synergy with UoW computer science Enthusiastic consultant workforce Training opportunities

13 Immediate challenges Cost and return in investment Improved efficiency, grant income, and market opportunities Validation FDA decreed not class 1 exempt. Pre-market testing required CPA require validation against existing technology None inferiority study designed Audit meeting variations used as benchmark

14 Validation study power calculation

15 Validation study design Double reporting Glass first digital second Minimum of 3 week washout period Compare reports to detect differences Steering group meets weekly to assess and classify differences 3014 cases

16 Validation study data 3050 cases Slides 40x: 10,138 Slides 60x: 1,384 Data 2.45 TB Annual data size predicted 22TB

17 Validation study Scanned 3050 cases Double reported 2952 Pathologists don t remember cases Difficult cases are no easier on digital Bugs (H pylori, gram positive cocci) need x60 scans Z stack not so important on histology cases Renal Biopsies x60 Differences in diagnosis, so far, mainly due to interpretation Grading low grade dysplasia may be more difficult on digital than glass Measurements more accurate on digital

29 Challenges for routine practice Front and back end interface with LIMS needed Develop scanning rules Re-work laboratory protocols Improve section quality and tissue mounting Maintain streaming speed within the departmental security protocol Some things will still need glass Polarisation Over sized blocks Low grade dysplasia X100 oil (scanty organisms)

30 Problems Speed of streaming LIMS interface Tiles out of focus High quality sections work best

31 Positives Scan speed excellent mean around 90 seconds per slide Image quality excellent Workflow software excellent Very easy to use system Fits well in laboratory workflow Stable Excellent support

32 What does digital pathology offer? Economic advantages Increase efficiency of pathologists Reduce turn around time to report cases Improved review of cases including MDT/Tumour board review Quality advantages Reduced error rate Increased subspecialisation IHC scoring and indexing Tumour grading / dysplasia grading Cancer finder

33 Pathologist T&M Study Results Breakdown of Time Working Cases Slide Review 36.0% (1:56:13) Other 16.0% (0:51:43) Workflow Opportunities 13.4% (0:43:09) Reporting 34.6% (1:51:38)

34 Pathologist T&M Study Results Breakdown of Workflow Opportunities Workflow Opportunities Slide Review 36.0% (1:56:13) Other 16.0% (0:51:43) Organizing Cases 24.1% (0:10:25) Querying for Cases 18.5% (0:07:59) 13.4% Waiting for Delivery 11.2% (0:04:49) Matching 10.5% (0:04:32) Searching for Cases 9.4% (0:04:04) Transporting Cases 9.2% (0:03:58) Other 17.0% (0:07:21) Reporting 34.6% (1:51:38) 100% (0:43:09)

35 Pre-allocation of specimens Push system Laboratory Pathologist A Pathologist B Pathologist C Pathologist D Pathologist E Pathologist F Pathologist G Pathologist H Subspecialty 1 Subspecialty 1 Subspecialty 1 Subspecialty 2 Subspecialty 2 Subspecialty 3 Subspecialty 3 Subspecialty 4 Subspecialty 3 General Pool Subspecialty 4 Subspecialty 4 General Pool General Pool General Pool General Pool General Pool General Pool

36 Improved workflow efficiency Pull system Server Sub-specialist bench 1 Sub-specialist bench 2 Sub-specialist bench 3 Sub-specialist bench 4 General Pool bench Pathologist A Pathologist D Pathologist G Pathologist E All except Pathologist C Pathologist B Pathologist E Pathologist A Pathologist H Pathologist C Pathologist F Pathologist F Pathologist D

37 Algorithms in development Improved accuracy and patient safety Cancer grading tool prostate, breast, and bladder cancers Cancer finding tool, region of interest alert Alerts for slides or tissue samples not examined Overlay tool intelligently identifies regions of interest in sequentially cut sections Automation downstream quantitative ICC e.g ER, PR, Ki67, HER2 Quantification of tumour volume for molecular analysis

38 Warwick digital pathology centre of excellence Mitotic count tool 3 rd AMIDA Grand Challenge Nagoya 2013 Nuclear grading tool 1 st MITOS-Atypia 2014 Challenge Tumour grading tool Cancer finding tool IHC slides with quantitative scores Resection margin, depth of invasion exported directly to report Nasir Rajpoot Violeta Kovacheva Korsuk Sirinukunwattana Nick Trahearn Adnan Mujahid

39 Remote Laser Capture Microscopy - RELCAM

Digital Pathology Diagnosis Assistance System

August 3, 2011 Digital Pathology Diagnosis Assistance System Computer s s eye and Pathologist s s eye Ogura M, Saito A, Graf HP, Marugame A, Kiyuna T, Yamashita Y, Cosatto E, Malon C & Fukumoto M. Innovative