Whole Slide Image Based Interpretation of Immunohistochemistry Stains in Challenging Prostate Needle Biopsies Jeffrey L Fine MD, Jonhan Ho MD, Yukako Yagi,

Whole Slide Image Based Interpretation of

Immunohistochemistry Stains in Challenging Prostate Needle

Biopsies

Jeffrey L Fine MD, Jonhan Ho MD, Yukako Yagi, Drazen Jukic MD PhD, John R Gilbertson MD, Sheldon I Bastacky

MD, Dana M Grzybicki MD PhD, Leslie Anthony, Robb Wilson, and Anil V Parwani MD PhD

Objectives

• Review whole slide image “landscape”

• Present research project

• Discuss implications arising from the study

Whole Slide Image (WSI)

• Digital facsimile of an entire glass microscope slide that is viewed by “virtual microscopy” (VM) software

• WSI are also known as “Virtual Slides” or “Digital Slides”

The Landscape: WSI Systems

• Systems are currently self contained– Image acquisition, management, storage, and

utilization (viewing and image analysis)

• Bar code capabilities limited to “reading”

“Obvious” Current Trends

• Decreasing cost for robots and storage

• Increasing speed for robots– Raw capture speed– Better “shortcuts”

• Involvement of traditional microscopy players– Olympus, Zeiss, Nikon

Nascent Trends

• Vendor concern about “workflow” and “integration”– How to slip a robot into an existing APLIS and

histology workflow

• Digital pathology workstations– Monitors (how many and how large)– Display calibration

Clinically-Oriented Research:WSI “Clinical Evaluation Group”

• Core affiliated group:– 4 pathologists; 1 fellow; study coordinator; data

coordinators; imaging technicians; LIS personnel

• Additional pathologists, depending upon study

• Prior studies– Quality Assurance– Primary Diagnosis

Current Project

• Goal: Validation of WSI technology for interpretation of immunohistochemistry (IHC) stains

• Why?– UPMC has a centralized IHC laboratory that supports

two academic hospitals– Electronic distribution (via WSI) could decrease turn-

around time for IHC stains• Better patient care; better service to clinicians• Decreased healthcare cost (shorter length of stay?)

– WSI could permit automated image analysis of IHC

Traditional workflow

1. Slides stained

2. Slides sorted and gathered– When a group of stains is complete they can

be shipped to pathologist

3. Slides packed and shipped (courier)

4. Received slides are sorted (again) and distributed to pathologists

WSI workflow

1. Slides are stained

2. Stained slides are placed into a slide scanning robot which reads their bar codes and does the heavy lifting (naming of file; copying of file to server; etc.)

3. Pathologist views the slides directly over the internet

4. Glass slides catch up later (optional?)

Prostate Needle Biopsies

• Availability at UPMC Shadyside

• Small set of “usual” IHC stains– p63; cytokeratin 903; racemase

• Typically signed out in an itemized fashion– Detailed information about each part or block

• Very challenging IHC interpretation

Cytokeratin 903“immuno stain”stains cytoplasm of basal cells

p63“immuno stain”stains nuclei of basal cells(positive = noninvasive)

racemase(aka AMACR)“immuno stain”stains cytoplasm of glandular cells in prostate

Retrospective Study:Possible UPMC Environment

• Stage I– Pathologist has glass H&E which requires IHC

staining for definitive diagnosis• Stage II

– Pathologist receives WSI of IHC stains and interprets them

• Stage III– Glass IHC stains are eventually received and are

checked by the pathologist• Consensus conferences

Study Design

• 100 cases screened– 30 difficult foci found

• Each study “case” represents one focus

Technology

• High throughput WSI system– T2 (Aperio Technologies, Vista, CA, USA)

• Viewing– Either WWW-based viewer or standalone

viewer (both supplied by WSI vendor)– “Standard” desktop PCs and microscopes

• Server– Nothing special (5 users and ~17 – 20 GB)

Data Collection

• Stain by stain interpretation (stages 2 – 3)

• Overall Diagnosis

• Confidence in diagnosis

• Time required to make diagnosis (roughly)

• Complexity of case

• Quality of each slide or image– Explanations for any defects or shortcomings,

including network speed

Stain Interpretations

• Positive

• Negative

• Can’t Tell (“?”)– Subcategories to help determine why the

pathologist couldn’t intrepret the stain

Additional Data Collection

• Consensus Diagnosis– Is mild disagreement OK (atypical vs. cancer)– How did this compare with original diagnosis

• Any relevant features or notes about case– Image defects (de-focused areas; color

reproduction; etc.)– Poor stain quality (not the image’s fault)

Results

Intra-observer Agreement(Stain Interpretation WSI vs Glass)

• Five Pathologists

• Average Intra-observer agreement– 80.6% (standard deviation 4.5%)– Range (75.7% - 86.0%)

Additional Results:Image Defects

• Pre-existing QC procedure did not detect several defective images

• Edge Defects

• Rotation Defects

Edge Defect

Rescanned

Rotation

H&E

Immuno

H&E

Imm

uno

Discussion

Validation

• Does this study validate WSI for interpretation of IHC stains?– Pathologists agreed with themselves about 80% of

the time– Need to find most common sources of disagreement

and see if they can be addressed

• It does highlight several points that need to be addressed prior to using WSI technology for real clinical applications

WSI Quality Control

• Each WSI must be checked for common defects– This has to be automated eventually

• All slides are not equal– IHC stains are susceptible to edge defects– Frozen section slides are hard to get focused

• Image quality standards do not exist yet for WSI

Modification to WSI Process

• Created a QC procedure (manual)– Includes solutions/fixes– Performed by technical support staff

• Documentation of QC activities (aka QA)– Log files– Monitor image quality

• Minimize sub-optimal or defective WSI that are “released” to pathologists

Workflow

• Glass was felt to be faster

• Current pathology systems do not accommodate WSI– Look up case in pathology system and click

on available slides

Viewer Limitations(Most Systems)

• Image navigation– (slow click and drag)– cannot rotate image easily (GI; skin; IHC stains)

• Presentation speed is slow– (pixels are visible until image can load completely)

• Lack of clinical data integration – (who’s slide is this?)

Study Flaws

• Pathologist subjects– Informatics fellows; non-GU pathologist; GU-

trained sub-specialists– Almost all pathologists were “informatics”

pathologists

• No standard display or VM software– 2 options for VM software– No “gold standard” for monitor/PC

• Loose track of time

Future Work

• Address flaws– Pathologist selection– Attention to software and computer used to

participate in study

• Other applications– Frozen Sections

Conclusions

• This study provided experience in the attempted production of “clinical grade” pathology images– Experience has altered our QC procedures– Further tools are needed (automation,

integration, etc.)

Conclusions

• If validated (not yet), WSI technology could permit electronic distribution of IHC stains– Reduced turn around time could improve service and

reduce healthcare cost– Centralized laboratories could support multiple

hospitals or pathologist groups

• Automated image analysis could be a future source of added value

Conclusions

• WSI technology is entering a new phase– Machines/systems are adequate for small

scale educational and research use– WSI systems are not yet capable of

integration with existing pathology systems

• This study (when published) can stimulate vendors and mainstream pathologists effectively transition to the next level

Acknowledgements

• Rebecca Crowley MD

• Michael Becich MD PhD

• Russ Silowash

• Jon Duboy