Computational Fractal-Based Analysis of Brain Tumor Microvascular Networks

  • Antonio Di IevaEmail author
  • Omar S. Al-Kadi
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI)


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 the computational-based morphometrics, for the objective description of the 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.


Angioarchitecture Brain tumor Fractal dimension Fractal analysis Glioblastoma multiforme Microvascularity 


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Neurosurgery Unit, Faculty of Medicine and Health SciencesMacquarie UniversitySydneyAustralia
  2. 2.Garvan Institute of Medical ResearchSydneyAustralia
  3. 3.Medical University of ViennaViennaAustria
  4. 4.University of TorontoTorontoCanada
  5. 5.Institute of BioengineeringEcole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
  6. 6.King Abdullah II School for ITUniversity of JordanAmmanJordan

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