What difference does a difference make? - PowerPoint PPT Presentation

What difference does a difference make?. Elizabeth Little, Ph.D. 26-Oct- 2010. Talk overview. Introduction

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PowerPoint PPTX Transcript


What difference does a difference make?

Elizabeth Little, Ph.D. 26-Oct- 2010

Talk overview
  • Introduction
  • Tissue thickness variation
    • Using best histological practices
  • Stain intensity variation due to tissue thickness
  • The difference matters
    • Could impact algorithm functionality
Systems integration

source: www.vagabondish.com

The Hematoxylin & Eosin (H&E) slide
  • Numbers
    • In 2009, 330 million histology slides were produced in the United States
    • 83% (274 million) were stained with H&E
  • Pathologist
    • Potential first look at the disease state
  • Cost
    • Dollars vs. thousands of dollars for more advanced testing
Impacts of H&E stain variability
  • Pathologist workflow is impacted by staining variability
    • Repeat slides
  • Imaging workflow is also impacted by staining variability
    • Algorithms can by impacted by stain variability
Antecedents that are helpful for H&E slide image analysis
  • Control of the stain variation
    • Under best practices we can control stain variability to a certain degree
  • Algorithms that are robust against stain variation
Staining variables we cannot control- tissue type affects stain intensity

Pixel

count

(N)

Intensity Level

Staining variables that we have some control over - tissue thickness impacts stain intensity

2 micron

4 micron

Pixel

count

(N)

Talk overview
  • Introduction
  • Tissue thickness variation
    • Using best histological practices
  • Stain intensity variation due to tissue thickness
  • The difference matters
    • Could impact algorithm functionality
Possible sources of variations in section thickness in the histology laboratory
  • Fixative
  • Duration of fixation
  • Tissue processing
  • Paraffin
  • Tissue block
  • Microtome
  • Histologist
Objective – measure the sectioning process impact on tissue thickness
  • 1 tissue block used
  • 1 microtome
  • 2 settings
    • Automated (32 slides per histologist)
    • Manual (32 slides per histologist)
  • 2 histologists
    • 22 years of experience vs. 4 years of experience
Tissue thickness variability testing outline
  • Section
    • Tissue was sectioned using a microtome setting of 4 microns
  • Measure Section Thickness
    • Interferometry
  • Stain
    • H&E
  • Measure intensity
    • Whole slide imaging
Measuring tissue thickness using vertical scanning interferometry

source: cnx.org

Tissue thickness using interferometric measurements
  • Glass vs. paraffin
  • Tissue was not measured
    • Interferometer limitation
    • Glass level variability
  • Measurements taken at 6 locations repeatedly
How well are we using the interferometer?How good is our tissue thickness measuring system? - gage R & R

Equipment

variation – 0.79%

Operator

variation – 0.01%

Sample

variation – 99.20%

Slice thickness variation – by histologist
  • Nominal setting was 4 microns
  • Both Histologists cut significantly thicker than 4 microns
  • Both Histologists cut at significantly different thicknesses from each other
Manual vs. automated microtomy impact on tissue thickness
  • Histologist 1 mean thickness was not impacted by microtome setting
  • Both histologists had statistically significant more variability using the
  • automated setting as compared to the manual setting
Block influences tissue thickness
  • Histologist 1 was the cutter
  • Automated setting used
  • Tissue 3 was cut significantly thinner than tissues 1 & 2
Summary of tissue thickness measurement results
  • Histology (location within block, slice selection, soaking, etc.)
    • Difference in mean tissue thickness
  • Microtome setting – automated vs. manual
    • Both histologists were impacted by setting
  • Block
    • Blocks 1 and 2 were cut more thickly than block 3
Talk overview
  • Introduction
  • Tissue thickness variation
    • Using best histological practices
  • Stain intensity variation due to tissue thickness
  • The difference matters
    • Could impact algorithm functionality

Stain intensity variation due to tissue thickness - normal breast lymph node study

3 micron

4 micron

Objective – measure tissue thickness impacton stain intensity
  • Tissue was sectioned and measured for thickness
  • All slides were stained using the same method
  • All slides were scanned using whole slide imaging and their average intensities were measured

Lymph node – 1 micron makes a measurable difference

Talk overview
  • Introduction
  • Tissue thickness variation
    • Using best histological practices
  • Stain intensity variation due to tissue thickness
  • The difference matters
    • Could impact algorithm functionality
Grey scale intensity differences

Pixel count

(N)

Summary
  • Expected vs. measured is different
  • The difference is quantifiable
    • Tissue thickness
    • Stain intensity
  • The difference matters
    • Could impact algorithm functionality
  • Tissue thickness and stain intensity correlate as expected
Further studies
  • Intensity vs. tissue type
  • Microtome bounce
  • Histology vs.
    • Drift
    • Knife
    • Location in block
    • Degrees of fixation

Acknowledgments

Cindy Connolly

Wendy Lange

Allison Cicchini

Heather Free

Aaron Ewoniuk

Jonathan Hall

Mike Cohen, Ph.D.

David Clark, Ph.D.

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