User Reference Manual

User Reference Manual
STEATOSIS QUANTIFICATION [Version 1.0]
(Intended for research purposes only)
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Contents
Overview ......................................................................................................................... 3
System Requirements ..................................................................................................... 3
Compatible File Formats ................................................................................................. 4
Input Parameters ............................................................................................................. 4
Output Parameters .......................................................................................................... 6
Vacuole Diameter Histogram .......................................................................................... 7
Contact Information ......................................................................................................... 8
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Overview
The Indica Labs Steatosis Quantification tool is intended for research use only. It is
designed to count and measure retention of lipids in liver samples. Fat vacuoles are
identified, separated, and quantitated on a per cell basis. In the sample below, you can
see the results of running the image analysis tool on fatty mouse liver. The algorithm
detects the nuclei (marked blue) and the lipid vacuoles (marked red).
In its final step, the algorithm reports quantitative data describing the analyzed regions
of liver. The reported data includes total number of lipid vacuoles, total number of cells,
and various vacuole measurements on a per cell basis. The algorithm also generates a
histogram showing the frequency of vacuoles within certain diameter ranges. All output
data can be easily exported to an excel file, CSV (comma separated value) file.
System Requirements
The Indica Labs Steatosis Quantification tool is designed to integrate seamlessly into
the Aperio release 11 platform. This software can be installed to run server-side with
the Aperio Spectrum software as well as client side within the Aperio ImageScope
software. Both ImageScope and Spectrum should be at version 11.0 or later.
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Compatible File Formats
Since this software can be fully integrated into the Aperio platform it can be used to
analyze all image formats that are compatible with Aperio ImageScope and Spectrum.
At the time of writing this document, this includes the following image formats:
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JPG
TIFF
SVS (Aperio)
NDPI (Hamamatsu)
MRXS (Zeiss)
JP2
• CWS (Olympus)
Input Parameters
The Steatosis Quantification algorithm allows the user to fine tune the input parameters
to meet the user’s specific needs and to improve performance on a specific stain or
tissue type. The following section describes each of the input parameters are in detail:
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Minimum Vacuole Size – This parameter allows a user to exclude the smallest
vacuoles or regions that to too small to be true vacuoles. It’s an area
measurement in microns squared.
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Maximum Vacuoles Size – This parameter allows the user to exclude areas that
are too large to be true vacuoles. It’s an area measurement in microns squared.
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Minimum Vacuole Roundness – allows the user to eliminate vacuoles by
shape. The parameter ranges from 0.0 to 1.0 where 0 is the least round and one
is a perfect circle. Increasing this value will eliminate the least round vacuoles.
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Vacuole Segmentation Aggressiveness – Oftentimes multiple vacuoles can be
touching or overlapping resulting in what looks like a single connected object.
This tool uses a segmentation algorithm to separate the connected objects and
this particular parameter controls the level of segmentation that will occur. It
ranges from 0.0 to 1.0. Increasing this value will result in more aggressive
segmentation and ultimately a higher number of smaller vacuoles. This
parameter should be used in conjunction with Maximum Segmentation Length.
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•
Maximum Segmentation Length – This parameter affects the segmentation
algorithm described above. It restricts the length (in microns) of computer
segmentation lines created by the algorithm. Using this parameter you can
prevent the segmentation algorithm from separating large spans across vacuoles
while allowing it to segment across small spans.
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Nuclear Contrast Threshold – In order to detect nuclei, the algorithm relies on
sufficient contrast between the darker nucleus and the lighter background
staining. This value dictates how much contrast is required for nuclear detection.
The value ranges from zero to one. Decreasing the value results in fewer nuclei
detected, increasing the value results in more. Note, sometimes increasing this
value has the unexpected effect of removing nuclei. This occurs because
multiple nuclei are joined together and then disqualified because of their large
size.
Minimum Nuclear Size – This parameter allows the algorithm to exclude objects
that are too small to be nuclei. The specified value in microns squared should be
set to the smallest nucleus size that you’d like to detect. Objects smaller than
this will not be counted and objects larger than this might be counted.
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Maximum Nuclear Size – This parameter allows the algorithm to exclude
objects that are too large to be nuclei. The specified value in microns squared
should be set to the largest nucleus size that you’d like to detect. Objects larger
than this will not be counted and objects smaller than this might be counted.
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Histogram Start – The algorithm generates a “Vacuole Diameter Histogram”
which displays the frequency of vacuoles that fall within a given diameter range.
This value represents the minimum diameter length (in microns) that should be
counted in the histogram.
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Histogram End - The algorithm generates a “Vacuole Diameter Histogram”
which displays the frequency of vacuoles that fall within a given diameter range.
This value represents the maximum diameter length (in microns) that should be
counted in the histogram.
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Histogram Bin Count - The algorithm generates a “Vacuole Diameter
Histogram” which displays the frequency of vacuoles that fall within a given
diameter range. This value represents the number of bins that should fall
between “Histogram Start” and “Histogram End”.
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Output Parameters
This image analysis tool reports a set of results for each distinct analysis region and for
the entire digital slide if analyzed. These results include the following output
parameters:
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Vacuole Count –the total number of vacuoles discovered
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Avg Vacuole Area – The total vacuole area divided by the vacuole count.
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Avg Vacuole Diameter – Since vacuoles are not perfectly round, the algorithm
looks at all diameters through a centroid point of each vacuole. Of those
diameters, it assumes the median length diameter to be the diameter for the
vacuole. Next, it looks at each vacuoles median diameter and computes an
average diameter (in microns) of all the vacuoles.
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Avg Vacuole Perimeter – The algorithm calculates the perimeter length (in
microns) of each diameter. The avg vacuole perimeter represents the total sum
of all perimeter lengths divided by the total number of vacuoles.
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Total Vacuole Area – sum of all vacuole areas (in microns squared).
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Nuclear Count – the total number of nuclei that were detected.
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Avg Nuclear Area – the average size (in microns squared) of a nucleus.
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Total Nuclear Area – the total area (in microns squared) of all nuclei combined.
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Avg Vacuole Per Cell – the vacuole count divided by the nuclear count.
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Avg Vacuole Area Per Cell – the total vacuole area divided by the nuclear
count.
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Vacuole Diameter Histogram
This image analysis tool also generates a histogram which indicates the frequency of
vacuoles within certain diameter ranges. Those ranges are determined by the input
parameters described above (start, end, bin count). To access this histogram, click on
the histogram icon on the ImageScope annotation window.
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Contact Information
For technical support and other information, please contact Indica Labs, Inc.
Email: [email protected]
Visit: http://www.indicalab.com
Dial: +1 (505) 573-5167.
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