Literature DB >> 17784937

Fractal dimension as a quantitator of the microvasculature of normal and adenomatous pituitary tissue.

Antonio Di Ieva1, Fabio Grizzi, Giorgia Ceva-Grimaldi, Carlo Russo, Paolo Gaetani, Enrico Aimar, Daniel Levi, Patrizia Pisano, Flavio Tancioni, Giancarlo Nicola, Manfred Tschabitscher, Nicola Dioguardi, Riccardo Rodriguez Y Baena.   

Abstract

It is well known that angiogenesis is a complex process that accompanies neoplastic growth, but pituitary tumours are less vascularized than normal pituitary glands. Several analytical methods aimed at quantifying the vascular system in two-dimensional histological sections have been proposed, with very discordant results. In this study we investigated the non-Euclidean geometrical complexity of the two-dimensional microvasculature of normal pituitary glands and pituitary adenomas by quantifying the surface fractal dimension that measures its space-filling property. We found a statistical significant difference between the mean vascular surface fractal dimension estimated in normal versus adenomatous tissues (P = 0.01), normal versus secreting adenomatous tissues (P = 0.0003), and normal versus non-secreting adenomatous tissues (P = 0.047), whereas the difference between the secreting and non-secreting adenomatous tissues was not statistically significant. This study provides the first demonstration that fractal dimension is an objective and valid quantitator of the two-dimensional geometrical complexity of the pituitary gland microvascular network in physiological and pathological states. Further studies are needed to compare the vascular surface fractal dimension estimates in different subtypes of pituitary tumours and correlate them with clinical parameters in order to evaluate whether the distribution pattern of vascular growth is related to a particular state of the pituitary gland.

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Year:  2007        PMID: 17784937      PMCID: PMC2375776          DOI: 10.1111/j.1469-7580.2007.00804.x

Source DB:  PubMed          Journal:  J Anat        ISSN: 0021-8782            Impact factor:   2.610


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