  Tissues are fractal due to its self-similar structure, and the fractal
dimension change with the abnormalities such as in disease like cancer. The
optical imaging of thin slices of tissue using transmission microscopy can
produce an intensity distribution pattern proportional to its refractive index
which represents the mass density distribution pattern of the tissues. The
fractal dimension of tissue is calculated by analyzing this mass density
distribution and is known to increase with the progression of carcinogenesis.
This paper explores the viability of using this quantitative approach of
fractal dimension analysis to create a standardized accurate cancer diagnosis
test and staging which reduces the issues plaguing current testing methods. A
commonality for most of the deadliest cancers is their lethality due to the
difficulty in properly diagnosing them in the early stages or accurate late
staging. This difficulty can arise from the physical location of the organ
causing them to be hard to access and the lack of noticeable symptoms until the
late stages when there is almost no hope of treatment. To study some of these
deadly cancers, commercially available paraffin embedded tissue microarray
(TMA) samples containing multiple cores of different cases and stages of
Pancreatic, Breast, Colon, and Prostate cancer are analyzed. The fractal
dimension of different TMA samples is able to correctly differentiate between
the different stages of each cancer, raising the possibility of a standardized
system being created to increase diagnosis accuracy in the future.
