Computational fractal-based analysis of brain tumor microvascular networks

Antonio Di Ieva, Omar S. Al-Kadi

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Brain parenchyma microvasculature is set in disarray in the presence of tumors, and malignant brain tumors are among the most vascularized neoplasms in humans. As microvessels can be easily identified in histologic specimens, quantification of microvascularity can be used alone or in combination with other histological features to increase the understanding of the dynamic behavior, diagnosis, and prognosis of brain tumors. Different brain tumors, and even subtypes of the same tumor, show specific microvascular patterns, as a kind of "microvascular fingerprint," which is particular to each histotype. Reliable morphometric parameters are required for the qualitative and quantitative characterization of the neoplastic angioarchitecture, although the lack of standardization of a technique able to quantify the microvascular patterns in an objective way has limited the "morphometric approach" in neuro-oncology.In this chapter, we focus on the importance of computational-based morphometrics, for the objective description of tumoral microvascular fingerprinting. By also introducing the concept of "angio-space," which is the tumoral space occupied by the microvessels, we here present fractal analysis as the most reliable computational tool able to offer objective parameters for the description of the microvascular networks.The spectrum of different angioarchitectural configurations can be quantified by means of Euclidean and fractal-based parameters in a multiparametric analysis, aimed to offer surrogate biomarkers of cancer. Such parameters are here described from the methodological point of view (i.e., feature extraction) as well as from the clinical perspective (i.e., relation to underlying physiology), in order to offer new computational parameters to the clinicians with the final goal of improving diagnostic and prognostic power of patients affected by brain tumors.

Original languageEnglish
Title of host publicationThe fractal geometry of the brain
EditorsAntonio Di Ieva
Place of PublicationSwitzerland
PublisherSpringer, Springer Nature
Chapter27
Pages525-544
Number of pages20
Edition2nd
ISBN (Electronic)9783031476068
ISBN (Print)9783031476051
DOIs
Publication statusPublished - 10 Mar 2024

Publication series

NameAdvances in neurobiology
PublisherSpringer, Springer Nature
Volume36
ISSN (Print)2190-5215
ISSN (Electronic)2190-5223

Keywords

  • Angioarchitecture
  • Brain tumor
  • Fractal analysis
  • Fractal dimension
  • Glioblastoma
  • Microvascularity

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