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Creating Tissue Finding and HPF Finding
Algorithms
Creating Tissue Finding and HPF Finding Algorithms requires familiarity with both Vectra and inForm
software, so PerkinElmer recommends reading the User’s Manuals for both of these systems before you
begin.
To fully utilize the imaging and tissue classification capabilities of the Vectra Intelligent Slide Analysis
System, you need to create at least two inForm algorithms (using inForm software version 1.4 or
greater) for each unique set of tissue slides. You then select these algorithms within the Vectra
protocols. In general, the Tissue Finding Algorithm (used prior to the low power scan) differentiates
between tissue and non-tissue regions, while the HPF (High Power Field) Finding Algorithm finds
specific targets such as tumor cells, inflammation, arterial plaque, etc. During an automated scan,
Vectra scans the slide in monochrome mode. Vectra then uses the Tissue Finding algorithm in the
protocol to search the monochrome images for tissue regions to subsequently scan in LP imaging
mode. When LP imaging is complete, the HPF Finding Algorithm searches the LP images for regions
that contain specific target(s) of interest. Finally, the Vectra system takes HP images of those target
regions.
Selecting a Slide Set for Algorithm Training
Before you can create algorithms using inForm software version 1.4 or greater, you first need to use
the Vectra Slide Analysis System to scan a few slides that you select from the slide set. For
example, if the study contains 50 – 100 slides, select approximately five sample slides that span
the heterogeneity of the entire slide set. The sample slides should contain examples of everything
the algorithms will encounter when classifying images during the Vectra slide scanning protocol.
Manually Acquiring a Dataset for Algorithm Training
Load and scan the sample tissue slides manually, one at a time. Make sure the Scan Area
includes the entire slide, and use the same wavelength and scan settings that you will use during
the actual scan of the complete slide set. Acquire and save Monochrome Images and Low
Power Images:
The Monochrome Imaging phase should capture everything that you expect the Tissue Finding
algorithm to encounter when it searches for tissue regions later. For example, tissue vs. nontissue regions, the edge of the cover slip and any strange fringing effects caused by the cover
slip, dust, dirt, air bubbles, and anything else the algorithm might have to deal with. Later, you will
open these monochrome images in inForm software version 1.4 or greater to create the Tissue
Finding Algorithm.
During the Low Power Imaging phase, manually select all fields that include examples of things
you expect the HPF Finding Algorithm to encounter, both positive and negative. This Low Power
Imaging phase is much more about finding specific targets, instead of just general tissue, which
means you need plenty of images of both. For example, if the target is cancer, select images that
contain cancer as well as images that do not. Include images that contain things that look like
cancer but are not, as well as images that contain artifacts, etc. Keep in mind that this LP color
imagery is necessary for training the HPF Finding Algorithm that ultimately identifies fields for HP
multispectral imaging.
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Vectra - User Help