This document describes research using image analysis to detect anaplastic cells in cancer samples. Anaplasia refers to dedifferentiation of cells and is a characteristic of malignant tumors. The researchers developed algorithms to analyze digitized tissue slides and detect anaplastic nuclei based on size, shape, and chromatin characteristics. The algorithm could identify 87% of anaplastic nuclei and highlight them for pathologists. This automated detection approach provides decision support for pathologists and could enhance cancer detection and optimize patient treatment.

1. Finding cancerous anaplastic
cells with image analysis
K. Nicol, M. Plaskow, T. Barr,
D. Billiter

2. Anaplasia
– refers to a reversion of differentiation in cells
and is characteristic of malignant
neoplasms/tumors
– literally means "to form backward"
It implies dedifferentiation, or loss of structural and
functional differentiation of normal cells
– Anaplasia is the most extreme disturbance in
cell growth encountered in the spectrum of
cellular proliferations

3. Anaplastic cells display marked pleomorphism
– The nuclei are characteristically extremely
hyperchromatic and large.
They may approach 1:1 instead of the normal 1:4 or 1:6
Anaplastic nuclei are variable and bizarre in size and shape
– The chromatin is coarse and clumped, and nucleoli may be of
astounding size
– With / without large atypical mitotic figures
– Giant cells that are considerably larger than their
neighbors may be formed and possess either one
enormous nucleus or several nuclei

5. Forms of Anaplasia
– Focal
Wilms
– Anaplastic cells confined to a sharply localized area within
the primary tumor
Rhabdomyosarcoma (RMS)
– Anaplastic cells scattered among nonanaplastic cells
– Diffuse
Wilms
– Non-localized anaplasia, or anaplasia noted beyond the
tumor capsule, or present in a biopsy specimen
RMS
– Anaplastic cells in clusters or continuous sheets

6. Significance of anaplasia
– Wilms tumor
Recognized as the only unfavorable histological
feature of this tumor
– Prognostically significant if anaplasia is seen in
extrarenal tumor sites
lower relapse-free survival rate
– Chemotherapy regimens are augmented if anaplasia is
seen

7. – Medulloblastoma
Younger age at diagnosis
Greater risk of extracranial metastasis
Lower survival
– Rhabdomyosarcoma
Significant association with anaplasia and clinical
outcome in Embryonal RMS
Older age at diagnosis with larger tumors

8. Utilization of image analysis to advance
cancer research
– The application was built using Microsoft
technologies
Visual Basic 6.0
Visual Basic .NET
C++.NET
SQLServer 2000-2005.

9. Our Review
– Identified cases of Wilms tumor and
Rhabdomyosarcoma having evidence of
anaplasia
– Scanned the slides using Aperio® scanscope
– Construct algorithms to analyze cellular
characteristics of the tissue on the slide

12. Anaplastic nuclei were detected by:
– ran many trials to determine constant pixel
characteristics to define the nuclei of cells on
the slide
– measured the nuclei based on total pixels of
area
– Compared the nuclear “size” within the tissue
section
– highlighted and “stored” the location of all
“suspect” nuclei on the tissue section

14. Pathologists are able
to set a custom
sensitivity for the
algorithm, which
effects the area
comparison between a
nucleus and all of the
others within the field
on tissue section.

17. Results:
– It currently takes the anaplasia algorithm 40
minutes to process an entire slide.
Slide specimens scanned in to high quality.
– TIF images (Tagged Image File) average from
80,000 to 150,000 pixels in width and 50,000 to
130,000 pixels in height, totaling 3 to 10 billion
pixels per slide specimen.

18. Using this method, 87% of all anaplastic
nuclei analyzed were located, counted,
and highlighted for the pathologist/
reviewer.

19. Conclusion
– Pathologists are able to get electronic decision
support in rapidly finding certain features for
malignant tumors
– The association and utilization of a high
performance computing environment within
cancer research will enhance detection and
optimize the pathology review process thus
allowing for rapid and specific patient therapy.

20. Thank You