Detection of cancer stages through fractal dimension analysis of tissue microarrays (TMA) via opt...

1. What

1.1. • Tumor = abnormal proliferation of cells • Cancer = dangerous tumor (malignant) • Self-similarity measurement (fractal dimension) • Optical transmission microscopy

2. Problem

2.1. • Increase of deaths year after year • Increase of cancer cases /!\ Current detection methods are mostly QUALITATIVE therefore SUBJECTIVE

3. Who / When

3.1. • L. Elkington, P. Adhikari, P. Pradhan • December 2020

4. Where

4.1. Department of Physics and Astronomy, Mississippi State University, USA

5. Basics

5.1. Tissues have a self-similar character |→ tumors affect the fractal dimension of a tisssue |→ possible quantification

6. Hypothesis

6.1. "Can we quantify the stage of a cancer using self-similarity quantity analysis?"

7. Method

7.1. [ MATERIAL ] • TMA (tissu microarray) x4 slides |→ Pancreas, breast, colon, prostate

7.2. [ FRACTAL ] ln (N(r)) Df: fractal dimension = degre of similarity • Df = ———— with N(r): number of pattenrs at scale r ln (1/r) r: scale [Length] |→ If Df increases ⇒ Self-similarity increases

7.3. [ MICROSCOPE USE ] • Bright field image conerted to binary ⇒ Graph of Df plotted ⇒ Slope = self-similarity degree

8. Results

8.1. Pancreas results: Df(I) = Df(normal) +4% Df(II) = Df(normal) +6% Df(III) = Df(normal) +9% (Same increase shapes for breast, colon and prostate) ⇒ As expected, Df increases with tumor stage

9. Conclusion

9.1. → Not the only study on the subject → Can detect QUANTITATIVELY and also lead to a large international OBJECTIVE database ⇒ Refinement of the method ⇒ Study of the demographic evolution of cancers