Detection of cancer stages through fractal dimension analysis of tissue microarrays (TMA) via optical transmission microscopy
저자: Gregoire Chouvet
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