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Fractal Anatomy of Human Organs: A Narrative Review of Structure, Function, and Clinical Perspectives
Immacolata Belviso1, Jacopo Junio Valerio Branca2, Giulia Guarnieri2
1Department of Psychology and Health Sciences, Telematic University Pegaso, Naples, Italy.
Abstract:
Fractal geometry describes complex, self-similar patterns that repeat across spatial scales and is increasingly recognized as relevant in anatomical research. Indeed, the fractal organization is consistently observed in respiratory, cardiovascular, gastrointestinal, nervous, renal, hepatic, and dermatological systems. A comprehensive literature search was conducted on PubMed, Scopus, and Web of Science (1977 to March 2025) identifying peer-reviewed original articles, reviews, and conference proceedings addressing the fractal organization of human organs at macrostructural or microstructural levels, with structural-functional relationships and/or clinical applications. Studies were excluded if they lacked direct translational relevance to humans, were not peer-reviewed, or did not utilize explicit fractal methodology. Key findings highlight that bronchial tree fractal dimension (FD) correlates with airflow limitation in chronic obstructive pulmonary disease, while in the vascular system, retinal metrics reflect systemic microvascular health. Moreover, the fractal modeling of hepatic and renal hemodynamic models supports system-level interpretation. In the nervous system, cortical gyrification and neuronal dendritic FD are associated with cognitive capacity and disease progression. Gastrointestinal mucosal FD decreases in inflammatory and neoplastic conditions. Advances in multiscale imaging (e.g., micro-CT, MRI) and computational methods enable both in vivo and ex vivo assessment, although methodological heterogeneity remains a limiting factor. Overall, fractal analysis provides a quantitative and reproducible descriptor of anatomical complexity with demonstrated associations to functional performance and disease severity. Standardization of methodology, development of normative datasets, and validation in large prospective cohorts are essential for routine clinical practice.
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