Detection of Cancer Stages via Fractal Dimension Analysis of Optical Transmission Imaging of Tissue Micro Arrays (TMA)

TL;DR

This study demonstrates that fractal dimension analysis of optical transmission images of tissue micro arrays can effectively differentiate between various stages of colon cancer, offering a rapid and potentially more accurate diagnostic tool.

Contribution

The paper introduces a novel application of fractal dimension analysis on TMA samples for cancer staging, enhancing diagnostic accuracy and speed.

Findings

Fractal dimension varies significantly across different cancer stages.

Entropy and spatial correlation support fractal analysis results.

Method shows promise for non-invasive, quick cancer diagnostics.

Abstract

Cancer is an epidemic worldwide. At present one in four persons has cancer and this statistic will change to one in a two person in the near future. It is now known that war against cancer is the early, curable detection and treatment. Affordable, quick and easy detection methods are, therefore, essential. Standard pathologist way of detecting cancer is looking at the stained biopsy tissue samples under microscope, brings lots of human error. A tissue is a spatial heterogeneous medium and it has fractal properties due to its self-similarity in mass distribution. It is now known that with the progress of cancer the tissue heterogeneity changes due to more mass accumulations and rearrangement of intracellular macromolecules such as DNA and lipids etc. Furthermore, there are tissue micro array (TMA) samples available that provides array of hundred samples in one glass slides. In this study, using reflectance microscopy we have analyzed the fractal dimension of 5{\mu}m colon TMA samples to correctly distinguish between normal, adjacent to cancer, benign, stage-1 and stage-2 colon cancers. This fractal property of the tissues is also supported by entropy and spatial correlation calculations. The application of this method for diagnostic applications is also discussed.