Abstract
ObjectiveTo determine if there is any non-linearity in the biomagnetic recordings of uterine myomas and to find any differences that may be present in the mechanisms underlying their signal dynamics.MethodsTwenty-four women were included in the study. Sixteen of them were characterised with large myomas and 8 with small ones. Uterine artery waveform measurements were evaluated by use of Pulsatility Index (PI) (normal value PI<1.45).ResultsApplying nonlinear analysis to the biomagnetic signals of the uterine myomas, we observed a clear saturation value for the group of large ones (mean = 11.35 ± 1.49) and no saturation for the small ones.ConclusionThe comparison of the saturation values in the biomagnetic recordings of large and small myomas may be a valuable tool in the evaluation of functional changes in their dynamic behavior.
Highlights
Several aspects of nonlinear dynamics have been explored in physics and medical engineering in recent years [1]
The raw data were of high amplitudes in the large uterine myomas and of low amplitudes in the small ones
A statistically significant difference was observed in the Pulsatility Index (PI) values obtained from large and small
Summary
Several aspects of nonlinear dynamics have been explored in physics and medical engineering in recent years [1]. Descriptions of linear and nonlinear systems, fractal geometry, and neural networks are all relevant to the study of oncological problems. The complexity of biological processes is associated with interrelationships between many different factors, and mathematical simplifications via mechanical models can help elucidate biological behavioral patterns, whether on genetic, cell, tissue, tumor, organ, or whole-body scales. Dynamics describes systems that change in space and time – this is the nature of biological processes [2,3]. Tumor suppressor genes promote neoplasia as a consequence of the loss of their normal regulation. Tumors may exhibit an increase in complexity (e.g., tumor promoter genes) or a decrease in complexity (e.g., allelic loss and tumor suppression genes) [4]
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