The normal brain has a highly complex microvascularity that is set in disarray in neoplastictransformation. Brain tumors are in fact supported by the development of a unique vascularbed. It is now recognized that different tumors show several angiogenic patterns. Thisheterogeneity can be also observed in the same neoplastic histotype. Glioblastoma multiforme(GBM), the most common and malignant brain tumor, shows a high microangioarchitecturalvariability. Although it has been suggested that vessel quantification can be used in addition tohistological grade for the tumor grading and prognosis, no objective parameters of themicrovasculature are currently widely accepted. The quantitative analysis of themicrovasculature of brain tumors could provide some morphological biomarkers predictingpatient prognosis and treatment response. The limitations of Euclidean approaches has led tothe introduction of the new mathematical paradigm of Fractal geometry to analyze thegeometrical complexity underlying the natural objects. Fractal analysis has also been provenas a useful means to quantify the microangioarchitectural networks in brain tumors.In order to explore the possibilities of using angiogenic patterns as morphometricbiomarkers, we developed a computer-aided fractal analysis for the quantification anddescription of microvascularity in the histological specimens of brain tumors, assessing theirmicrovascular fractal dimension (mvFD).In this chapter, we summarize the findings that distinct angioarchitectural subtypes canbe indexed by means of the mvFD, making this parameter a tool for quantifying andcategorizing different neoplastic microvascular patterns and a potential morphometricbiomarker to be used for clinical purposes.