After After
Before Before

10114 - Hot Spot

INTRODUCTION
One of the more recent approaches to Ki-67 scoring is the hot spot scoring method, which has been implemented to multiple scoring guidelines, e.g. the Swedish guidelines for breast cancer [1] and the Danish guidelines for breast cancer [2]. However, this scoring method lacks standardization and is often found to be subjective and prone to both intra- and inter-observer variability [3]. Using the Hot spot APP a standardized method for scoring in hot spots can be obtained.

The APP is independent on biomarker and tissue type, and may be used for analysis of biomarkers different from Ki-67 and on indications different from breast cancer. The APP can be configured in numerous ways, and can be customized for different use cases. The default Hot Spot APP configuration is the same as used in [4], where it was shown that digital image analysis of Ki-67 in hot spots is superior to both manual Ki-67 and mitotic counts in breast cancer.

KEYWORDS
Hot spot, Ki-67, breast cancer, image analysis, proliferation, digital pathology

METHODS
Based on objects already identified, e.g. with the APP “Ki-67, Breast Cancer”, a heatmap is created showing the “hottest” areas on the whole slide image. The heatmap can be created based on the density of positive nuclei or based on the ratio of positive and negative nuclei. A hot spot or multiple hot spots are then automatically placed based on the information in the heatmap. A hot spot can be defined as a circle of a fixed size, a square of a fixed size, an adaptive shape, that follows the contours of the heatmap until a predefined area is reached, or as an adaptive shape following the contours of the heatmap until a predefined number of nuclei is reached (see Figure 3-6).

QUANTITATIVE OUTPUT VARIABLES
The output variables obtained from this APP include:

  • Heatmap: The heatmap used for placing one or more hot spots. Can be created based on the density of positive nuclei or the ratio of positive and negative nuclei
  • Hot Spot Total Nuclei (#): The number of nuclei with the hot spot
  • Hot Spot Positive Percentage: The positive percentage with the hot spot. Calculated as: "Number of positive nuclei within hot spot" / "Hot Spot Total Nuclei (#)"

AUXILIARY APPs
Protocol: "01 Hot Spot Detection"
This protocol automatically creates a heatmap and places one or more hot spots based on the heatmap.
Protocol: "02 Hot Spot Quantification"
This protocol counts the nuclei present in the detected hot spot/hot spots and outputs the positive percentage for the hot spot(s).

WORKFLOW
Step 1: Load and run the protocol “01 Hot Spot detection” on an image already processed with an analytical APP, e.g. “Ki-67, Breast Cancer
Step 2: Load and run the protocol “02 Hot Spot Quantification” on the image already processed with “01 Hot Spot Detection”

STAINING PROTOCOL
The APP is independent of the staining.

ADDITIONAL INFORMATION
The APP utilizes the Visiopharm EngineTM and Viewer software modules, where EngineTM offers an execution platform to expand processing capability and speed of image analysis. The Viewer allows a fast review together with several types of image adjustment properties ex. outlining of regions, annotations and direct measures of distance, curve length, radius, etc. In addition the APP also utilizes the Tissuealign™ incl. VirtualDoubleStaining™ module, that facilitates a user-assisted computational alignment of serial sections and automatic tumor detection.
By adding the AuthorTM module the APP can be customized to fit other purposes. AuthorTM offers a comprehensive and dedicated set of tools for creating new fit-for-purpose analysis APPs, and no programming experience is required.

REFERENCES
1. KVAST, KVAST bröstcancer (2018), URL: http://www.svfp.se/foreningar/uploads/L15178/kvast/brostpatologi/KVASTbrostcancer2018.pdf, Accessed 2018-06-07

2. DBCG, Retningslinier – 3. Patologi, URL: http://www.dbcg.dk/PDF%20Filer/Kap_3_Patologi_22_juni_2017.pdf , Accessed 2018-06-07

3. Jang, Min Hye et al. “A Comparison of Ki-67 Counting Methods in Luminal Breast Cancer: The Average Method vs. the Hot Spot Method.” Ed. William B. Coleman. PLoS ONE 12.2 (2017): e0172031. PMC.

4. Stålhammar G, Robertson S, Wedlund L, Lippert M, Rantalainen M, Bergh J & Hartman J, Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer, (2018) Histopathology 72, 974–989. https://doi.org/10.1111/his.13452

RUO
Figure 1
Figure 1
Ki-67 stained slide.
Figure 2
Figure 2
The results produced by the Hot Spot APP for the image in Figure 1. The user is presented with the created heatmap and the hot spot (red outline). In this case the hot spot was defined to follow the heatmap contours until the hot spot contained 200 nuclei. This definition can be changed for different use cases.
Figure 3
Figure 3
The hot spot shape is defined in one of four ways, here as a circle of a fixed size.
Figure 4
Figure 4
The hot spot shape is defined in one of four ways, here as a shape that follows the heatmap contours until a predefined number of nuclei are reached.
Figure 5
Figure 5
The hot spot shape is defined in one of four ways, here as a shape that follows the heatmap contours until a predefined area is reached.
Figure 6
Figure 6
The hot spot shape is defined in one of four ways, here as a square of a fixed size.