Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale

Abstract

The characterization of cancer histological sections as metastatic, M, or not-metastatic, NM, at the cellular size level is important for early diagnosis and treatment. We present timely warning markers of metastasis, not identified by existing protocols and used methods. Digitized atomic force microscopy images of human histological cross-sections of M and NM colorectal cancer cells were analyzed by multifractal detrended fluctuation analysis and the generalized moments method analysis. Findings emphasize the multifractal character of all samples and accentuate room for the differentiation of M from NM cross-sections. Two universal markers emphatically achieve this goal performing very well: (a) the ratio of the singularity parameters (left/right), which are defined relative to weak/strong fluctuations in the multifractal spectrum, is always greater than 0.8 for NM tissues; and (b) the index of multifractality, used to classify universal multifractals, points to log-normal distribution for NM and to log-Cauchy for M tissues. An immediate large-scale screening of cancerous sections is doable based on these findings.

Multifractality in Surface Potential for Cancer Diagnosis

“…The box-counting method has been widely used in previous studies to calculate the fractal parameters of biological samples, including cell analysis and cancer detection. Several studies in the field of cell analysis and cancer detection utilized image binarization for calculating the fractal dimension − and multifractal parameters. , By employing a similar methodology, we can better compare our results with the existing literature.…”

“…Physical properties such as cell stiffness, adhesion, and elasticity were used to identify cancerous tissue. , However, in some cases, AFM morphological imaging cannot differentiate between normal and cancer cells, while adhesion maps showed differences in fractality . Fractal − and multifractal , analyses were previously used for cancer diagnosis. Fractal geometry was used to describe the morphology of cancer cells and tissues by a single parameter, the fractal dimension, as a diagnostic biomarker. , The change in fractal dimension or self-similar organization of surface morphology by malignant transformation can be quantified.…”

Nanoscale Prognosis of Colorectal Cancer Metastasis from AFM Image Processing of Histological Sections

“…Indeed, during the transformation of single premalignant cells into cancerous ones [53], the fractal dimensionalities do not necessarily imply the existence of fractal geometrical features. However, the rational interpretation of variograms, theta statistics, and multifractal analysis [54] revealed unforeseen but significant outcomes.…”

A Non-Parametric Approach to Explainable Artificial Intelligence and Its Application in Medicine

“…компактностi Фрактальний аналiз став дуже поширеною технiкою в дослiдженнях структури пухлинних клiтин [6,13,35,41]. У той же час наявнiсть змiн, пов'язаних зi злоякiсним новоутворенням, у нормальних клiтинах стала загальновiдомим фактом [19,40].…”