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10048 - PHH3, Breast Cancer

INTRODUCTION

This APP has been developed to quantify the mitotic index of PHH3 positive cells within breast carcinoma. Phosphohistone H3 (PHH3) is a mitotic marker and has prognostic capabilities when applied to breast cancer tissue [See REFERENCES: 3]. The mitotic index can be obtained by PHH3-immunohistochemical staining, which can be used as a supplement for diagnosis.

KEYWORDS

Breast carcinoma, PHH3, Phosphohistone, immunohistochemistry, breast cancer, quantitative, digital pathology, image analysis, mitotic index, TMA

METHODS

Tumor areas are manually outlined as regions of interest (ROIs) [See EXAMPLES: figure 2]. The ROIs are used for subsequent analysis limited to the inside of the tumor regions [See EXAMPLES: figure 3].

Segmentation is performed of all nuclei (both PHH3 positive and negative). The method for nuclei separation which is based on shape, size and nuclei probability is used, employing a fully automated watershed-based nuclei segmentation technique. A post-processing step involving a morphological closing operation is applied to avoid counting nuclei in the late mitotic phase (anaphase and telophase) as two nuclei.
The number of positive PHH3 nuclei and the mitotic index is calculated.

QUANTITATIVE OUTPUT VARIABLES

The output variables obtained from this protocol include the number of positive nuclei profiles, the area of tumor tissue and the mitotic index. The mitotic index is calculated as follows:

- NUC POS: number of positive nuclei profiles
- Mitotic index = NUC POS / Area of Tumor


AUXILIARY APPS (included)

Auxiliary APPs are used for additional process steps, e.g. finding Region of Interest (ROI).

There are no Auxiliary APPs available.



STAINING PROTOCOL

There is no staining protocol available.


ADDITIONAL INFORMATION

This APP has been developed in cooperation with Professor Mogens Vyberg from NordiQC and Aalborg University Hospital Denmark and assistant professor Mette Christa Zeuthen from the Danish University College Metropol.

The APP utilizes the EngineTM and Viewer software modules, where EngineTM offers an execution platform to expand processing capability and speed of image analysis. Viewer gives 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.
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

LITERATURE

1. Phosphohistone H3 expression has much stronger prognostic value than classical prognosticators in invasive lymph node-negative breast cancer patients less than 55 years of age, Ivar Skaland et al., Mod Pathol 20(12):1307-1315, October 2007.

2. Learning histopathological patterns, A. Kårsnäs, A. L. Dahl, R. Larsen, Journal of Pathology Informatics, 2(2):12, 2011

3. Segmenting Clustered Nuclei Using H-minima Transform-Based Marker Extraction and Contour Parameterization, C. Jung et al., IEEE Transactions on Biomedical Engineering 57(10): 2600-2604, 2010.

RUO
FIGURE 1
FIGURE 1
Original TMA-core stained with PHH3.
FIGURE 2
FIGURE 2
The ROI only outlines tumor regions. Tissue that is not tumor and the background are excluded manually.
FIGURE 3
FIGURE 3
Nuclei segmentation is performed only inside the tumor region. Green labels are positive PHH3 nuclei.