Biocomplexity and Fractal Analysis: Theory and Applications

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 1565

Special Issue Editors


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Guest Editor
Center of Innovative Models and Technology for Ageing Care, Scientific Direction, IRCCS INRCA, 60121 Ancona, Italy
Interests: biocomplexity; fractals in biomedicine; aging and age-related pathologies; biomarkers of aging and disease; biomedical imaging; image processing and analysis

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Guest Editor
School of Science and Technology, University of Camerino, 62032 Camerino, Italy
Interests: applied mathematics; scientific computation; image processing

Special Issue Information

Dear Colleagues,

The application of paradigms such as the theories of complexity, chaos, and fractals to biosystems provide the foundation for new approaches and new tools for the study of biology and biomedicine.

Biosystems, as complex systems with chaotic behavior, can generate so-called ‘strange attractors’ that occur at critical points and can be described by fractals. This concept highlights the usefulness of fractal analysis as a suitable tool to measure biocomplexity and its changes at both structural and functional levels. Fractal analysis can measure variations of complexity in biosystems that follow different trajectories over time. Fractal analysis is therefore a promising tool to give insight into the search for good biomarkers. Toward this aim, a relevant role is played by methods and tools to support the fractal analysis of biosystems through biomedical imaging and other medical signal acquisition systems.

This Special Issue welcomes all types of articles (original research articles, reviews, short communications, commentaries, etc.) in the fields of biocomplexity and fractality with the aim of focusing on advanced research in topics relating to the theory, design, implementation, and application of fractal analysis in biomedicine. Topics that are invited for submission include (but are not limited to):

  • Complexity, chaos and fractality in biosystems: theories and applications;
  • Fractal analysis for parametric description of temporal and spatial sequences in biosystems;
  • Fractal modeling in physio-biology and medicine;
  • Applications of fractal analysis for biology and biomedicine;
  • Fractal analysis in medical imaging;
  • Fractal and multifractal analyses in the biomedical field as potential tools for the early diagnosis of disease onset and progression, and for treatment assessment.

Dr. Annamaria Zaia
Dr. Pierluigi Maponi
Guest Editors

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Keywords

  • biocomplexity
  • fractal analysis
  • biomathematical modeling
  • computer-aided diagnosis
  • biomarker
  • computational tools
  • biomedical imaging

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Published Papers (1 paper)

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Research

17 pages, 3351 KiB  
Article
Fractal Features of Muscle to Quantify Fatty Infiltration in Aging and Pathology
by Annamaria Zaia, Martina Zannotti, Lucia Losa and Pierluigi Maponi
Fractal Fract. 2024, 8(5), 275; https://doi.org/10.3390/fractalfract8050275 - 6 May 2024
Cited by 1 | Viewed by 1141
Abstract
The physiological loss of muscle mass and strength with aging is referred to as “sarcopenia”, whose combined effect with osteoporosis is a serious threat to the elderly, accounting for decreased mobility and increased risk of falls with consequent fractures. In previous studies, we [...] Read more.
The physiological loss of muscle mass and strength with aging is referred to as “sarcopenia”, whose combined effect with osteoporosis is a serious threat to the elderly, accounting for decreased mobility and increased risk of falls with consequent fractures. In previous studies, we observed a high degree of inter-individual variability in paraspinal muscle fatty infiltration, one of the most relevant indices of muscle wasting. This aspect led 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 ages (age range of 23–85 years) and physio-pathological status (healthy young, pre-menopause, menopause, and osteoporosis) were used to set up a method based on fractal-derived texture analysis of lean muscle area (contractile muscle) to estimate muscle fatty infiltration. In particular, lacunarity was computed by parameter β from the GBA (gliding box algorithm) curvilinear plot fitted by our hyperbola model function. Succolarity was estimated by parameter µ, for the four main directions through an algorithm implemented with this purpose. The results show that lacunarity, by quantifying muscle fatty infiltration, can discriminate between osteoporosis and healthy aging, while succolarity can separate the other three groups showing similar lacunarity. Therefore, fractal-derived features of contractile muscle, by measuring fatty infiltration, can represent good indices of sarcopenia in aging and disease. Full article
(This article belongs to the Special Issue Biocomplexity and Fractal Analysis: Theory and Applications)
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