What difference does a difference make?

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What difference does a difference make?

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

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Talk overview

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

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Systems integration
source www.vagabondish.com
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The Hematoxylin Eosin (HE) slide

• Numbers
• In 2009, 330 million histology slides were
  produced in the United States
• 83 (274 million) were stained with HE
• Pathologist
• Potential first look at the disease state
• Cost
• Dollars vs. thousands of dollars for more
  advanced testing

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Impacts of HE 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

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Antecedents that are helpful for HE 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

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Staining variables we cannot control- tissue
type affects stain intensity
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Pixel count (N)
Intensity Level
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Staining variables that we have some control over
- tissue thickness impacts stain intensity
2 micron
4 micron
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Pixel count (N)
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Talk overview

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

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Possible sources of variations in section
thickness in the histology laboratory

• Fixative
• Duration of fixation
• Tissue processing
• Paraffin
• Tissue block
• Microtome
• Histologist

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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

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Tissue thickness variability testing outline

• Section
• Tissue was sectioned using a microtome setting of
  4 microns
• Measure Section Thickness
• Interferometry
• Stain
• HE
• Measure intensity
• Whole slide imaging

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Measuring tissue thickness using vertical
scanning interferometry
source cnx.org
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Tissue thickness using interferometric
measurements

• Glass vs. paraffin
• Tissue was not measured
• Interferometer limitation
• Glass level variability
• Measurements taken at 6 locations repeatedly

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How well are we using the interferometer?
Source Standard deviation Contribution
Total measurement (gage) 0.29 0.80
Repeatability equipment variation 0.29 0.79
Reproducibility operator variation 0.03 0.01
Slide variation 3.20 99.20
Total variation 3.21 100.00
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How good is our tissue thickness measuring
system? - gage R R
Equipment variation 0.79
Operator variation 0.01
Sample variation 99.20
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Slice thickness variation by histologist
Histologist Number of slides Measured thickness average S.D. (mm)
Combined 128 4.74 0.16
1 64 4.65 0.10
2 64 4.84 0.16

• Nominal setting was 4 microns
• Both Histologists cut significantly thicker than
  4 microns
• Both Histologists cut at significantly different
  thicknesses from each other

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Manual vs. automated microtomy impact on tissue
thickness
Histologist Microtome setting Measured thickness S.D. (mm)
1 Automated 4.65 0.13
1 Manual 4.65 0.08
2 Automated 4.91 0.16
2 Manual 4.76 0.12

• 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

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Block influences tissue thickness
Tissue block Measured thickness average S.D. (um)
Tissue one (n32) 4.65 0.13
Tissue two (n16) 4.60 0.12
Tissue three (n16) 4.36 0.12

• Histologist 1 was the cutter
• Automated setting used
• Tissue 3 was cut significantly thinner than
  tissues 1 2

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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

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Talk overview

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

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

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Lymph node 1 micron makes a measurable
difference
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Talk overview

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

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Grey scale intensity differences
Pixel count (N)
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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

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Further studies

• Intensity vs. tissue type
• Microtome bounce
• Histology vs.
• Drift
• Knife
• Location in block
• Degrees of fixation

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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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