1. E-mail: gdounias@aegean.gr
COMPUTATIONAL INTELLIGENCE FOR THE DETECTION AND CLASSIFICATION OF MALIGNANT LESIONS IN SCREENING MAMMOGRAPHY DATA
E. Panourgias, A. Tsakonas, G Dounias, G. Panagi (Athens, Thessaloniki, Chios, Greece)

2. Early detection and diagnosis of breast cancer represents a very important factor in its treatment and consequently the survival rate
Screening mammography is considered the most reliable method of early detection, accounting for a decrease in mortality of up to 18-23%
Lancet 2003 Vol 361,Apr 26

3. Long term effect of screening mammmography on breast cancer death in 2 Swedish counties

4. Mammographic Appearance of Breast Cancer
Spiculated masses
Pleiomorphic,Heterogeneous Microcalcifications
Focal asymmetric densities with ill-defined margins or microlobulations
Architectural distortion

5. Mammographic Appearance of Breast Cancer
Spiculated masses
Pleiomorphic,Heterogeneous Microcalcifications
Focal asymmetric densities with ill-defined margins or microlobulations
Architectural distortion

6. AIM OF STUDY
We used data of 200 histologically proven malignant lesions discovered during screening to develop computer algorithms that may point in the direction of a specific histologic diagnosis.
Machine learning and Genetic Programming were applied.

7. INDUCTIVE MACHINE LEARNING
Method of computational intelligence based analysis
Has the ability to process large and complex databases
Constructs decision trees by intelligently reducing either,
Complexity of the search space or the size of the tree.

8. GENETIC PROGRAMMING Operates by mimicking a living population
Survival of the fittest
(fitness is how successful a member is in completing its assigned task- the least fit members are eliminated )
New members added (mutation, breeding, random generation)
- a population of random programs is generated

9. MATERIALS AND METHODS
For each case, all 4 standard views were used, as well as clinical and pathology data
All cases were rated according to the level of concern by using standard Breast Imaging Reporting and Data System, or BIRADS, recommendations

10. BIRADS LEXICON CATEGORY 1 NEGATIVE CATEGORY 2 BENIGN FINDING
PROBABLY BENIGN-MALIGNANCY CANNOT BE EXCLUDED
CATEGORY 4
SUSPICIOUS ABNORMALITY-BIOPSY RECOMMENDED
CATEGORY 5
HIGHLY SUGGESTIVE OF MALIGNANCY

11. ATTRIBUTES Mammographic parenchymal pattern (Pattern 1-5)
Age
Mammographic parenchymal pattern (Pattern 1-5)
Rt-Lt breast, Position-quadrant: Upper outer, upper inner, lower outer, lower inner, retroareolar
Mass-shape, margins
Microcalcifications
Architectural distortion
A system containing 5 mammographic patterns developed by Tabar helps classify the mammogram into subtypes, from the dense breast to the radiolucent fatty breast.

12. ATTRIBUTES Associated findings (nipple retraction, skin thickening)
BIRADS score
Histologic diagnosis
Histologic size
Lymph node status
Estrogen Receptor status
Progesterone Receptor status

13. MAIN HISTOLOGIC TYPES OF BREAST CANCER
Ductal cancer
DCIS (ductal carcinoma in situ)
Invasive ductal carcinoma
Lobular carcinoma
LCIS (lobular carcinoma in situ)
Invasive lobular carcinoma

14. Ductal Carcinoma Over 80% are variants of ductal carcinoma Two types:
Noninvasive (ductal carcinoma in situ-DCIS): tumor cells are confined to the duct epithelium and do not penetrate the basement membrane
Invasive (IDC) tumor cells penetrate the basement epithelium and invade the surrounding tissues

15. Lobular Carcinoma Noninvasive type or lobular carcinoma in situ (LCIS)
Does not form a palpable mass or visible lesion by mammography
Currently classified as a PREMALIGNANT lesion rather than a true cancer
Invasive Lobular Carcinoma (ILC)
Tends to be bilateral more often than ductal carcinoma (20% of cases are bilateral)
Tend to be multicentric within the same breast

16. observed in the RT breast in the UOQ, it is most likely IDC
Extracted Rule 1
If a mass with ill-defined margins, is
observed in the RT breast in the
UOQ, it is most likely IDC
Statistical prediction (0.875)
Several rules were extracted with an experiment with the data. These included the following

17. spiculated mass on a mammogram is almost pathognomonic of an
The presence of an ill-defined or
spiculated mass on a mammogram
is almost pathognomonic of an
Invasive Ductal Carcinoma
D. Kopans, Breast Imaging, 2nd ed., 1998

18. Extracted Rule 2
If patient presents with a Focal Asymmetric Density and a BIRADS score 3 in the RT breast, lesion
is suggestive of invasive ductal carcinoma (IDC) if size is <14mm
and invasive lobular carcinoma (ILC) if the lesion is >14mm or in BOTH breasts
(0.867)

19. expression which is a glue-like substance that provides cell-to-cell
ILC cells have decreased E-cadherin
expression which is a glue-like
substance that provides cell-to-cell
adhesion, a feature prominent in
IDC that causes cells to stick
together and produce a
mammographically visible mass
Neal Goldstein Am J Clin Pathology (3): ,2002

20. This is why ILC is frequently less apparent on mammograms and therefore, generally larger at diagnosis
Silverstein et al found that the average size at diagnosis for IDC’s was 23mm and for ILC’s 30mm.
Cancer 1994;73:
ILC tends to be bilateral more often than ductal carcinoma (20% of cases are bilateral)

21. Decision Tree Results
Woman presenting with a suspicious lesion and BIRADS score 5
in the UIQ of the RT breast and
size of lesion is <21mm, then it is IDC, >21mm it is ILC
Woman presenting with a FAD with BIRADS score 5
lesion size of <42mm then it is IDC,
>42mm, it is ILC

22. In a study that included 50 000 IDC’s and ILC’s, Arpino et al found that
54% of ILC’s are larger than 2cm, compared to 48% of IDC’s
14% of ILC’s presented as a large tumor exceeding 5cm, as compared with 9% of IDC’s
Grazia Arpino et al. Breast cancer Res 2004;6(3)R

23. Decision Tree Results If patient with a BIRADS score 4
presents with suspicious microcalcifications
(MC) on a mammogram in the UOQ and
an associated Architectural Distortion (AD),
then she is more likely to have IDC,
whereas if the MC are not accompanied by
AD, then the diagnosis of DCIS is more
probable

24. DCIS is a form of malignant transformation of the epithelial cells lining the mammary ducts and lobules
The proliferating cells are confined by an intact basement membrane
Necrotic debris in the lumen of the duct produces microcalcifications which are visible on a mammogram

25. Extracted Rules of GP
If the mass margin is equal to or greater than 3, then the histology diagnosis is IDC
If the mass margin is < 3 and the size <1cm, then the lesion is IDC, if it is > 1cm it is ILC.
Values of variables- Mass margin: 0=circumscribed, 1=ill-defined, 2= lobulated, 3=obscured, 4=spiculated

26. Conclusions
Despite the limited information (no prior studies, no normal cases, many more cases of IDC than other types of cancer) and
the fact that different types of abnormalities (MC, masses, AD) were included ,
the classification performances of determining that an identified lesion was a specific histological subtype was reasonable and consistent

27. Conclusions
The extracted rules often included the RT breast as a determining factor- needs further evaluation as this has not been proven in the literature
the computerized classification methods often used histology findings such as size to categorize the mammographic lesions

28. Conclusions
These issues have to be further investigated with larger datasets that include a greater number of attributes, a substantial amount of normal patients and more cases of cancers other than IDC’s, that composed that majority of our present dataset