Version 1
: Received: 23 February 2024 / Approved: 26 February 2024 / Online: 26 February 2024 (12:45:18 CET)
How to cite:
Zaia, A.; Zannotti, M.; Losa, L.; Maponi, P. Fractal features of muscle to quantify fatty infiltration in aging and pathology. Preprints2024, 2024021428. https://doi.org/10.20944/preprints202402.1428.v1
Zaia, A.; Zannotti, M.; Losa, L.; Maponi, P. Fractal features of muscle to quantify fatty infiltration in aging and pathology. Preprints 2024, 2024021428. https://doi.org/10.20944/preprints202402.1428.v1
Zaia, A.; Zannotti, M.; Losa, L.; Maponi, P. Fractal features of muscle to quantify fatty infiltration in aging and pathology. Preprints2024, 2024021428. https://doi.org/10.20944/preprints202402.1428.v1
APA Style
Zaia, A., Zannotti, M., Losa, L., & Maponi, P. (2024). Fractal features of muscle to quantify fatty infiltration in aging and pathology. Preprints. https://doi.org/10.20944/preprints202402.1428.v1
Chicago/Turabian Style
Zaia, A., Lucia Losa and Pierluigi Maponi. 2024 "Fractal features of muscle to quantify fatty infiltration in aging and pathology" Preprints. https://doi.org/10.20944/preprints202402.1428.v1
Abstract
The age-related loss of muscle mass and strength is referred to as “sarcopenia”. The combined effect of sarcopenia and osteoporosis is a devastating threat to the old adult, accounting for reduced mobility, risk for falls and subsequent fractures. In previous studies, we observed a high degree of inter-individual variability of paraspinal muscle fatty infiltration, one most relevant index of muscle wasting. This aspect solicited us to develop a computerized method to quantitatively characterize muscle fatty infiltration in aging and diseases.
Magnetic resonance images of paraspinal muscles from 58 women of different age (age range 23-85 years) and physio-pathological status (healthy young, pre-menopause, post-menopause, and os-teoporosis), were used to set up the method. It is based on fractal analysis of lean muscle area (contractile muscle) to estimate muscle fatty infiltration. In particular, lacunarity was computed by parameter β from our hyperbola model function, used to fit the GBA (gliding box algorithm) curvilinear plot. Succolarity was estimated by parameter µ, for the four main directions, through an algorithm implemented on purpose.
Results show that fractal lacunarity, by quantifying muscle fatty infiltration, can discriminate be-tween osteoporosis and healthy aging while succolarity can separate the other three groups showing similar lacunarity. Therefore, fractal features of contractile muscle, by measuring fatty infiltration, can represent good indices of sarcopenia in aging and disease.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
