Center for Anatomy and Cell Biology, Institute of Systematic Anatomy, Medical University of Vienna, Austria.
Microvasc Res. 2010 Sep;80(2):267-73. doi: 10.1016/j.mvr.2010.04.003. Epub 2010 Apr 13.
Neuroradiological and metabolic imaging is a fundamental diagnostic procedure in the assessment of patients with primary and metastatic brain tumors. The correlation between objective parameters capable of quantifying the neoplastic angioarchitecture and imaging data may improve our understanding of the underlying physiopathology and make it possible to evaluate treatment efficacy in brain tumors. Only a few studies have so far correlated the quantitative parameters measuring the neovascularity of brain tumors with the metabolic profiles measured by means of amino acid uptake in positron emission tomography (PET) scans. Fractal geometry offers new mathematical tools for the description and quantification of complex anatomical systems, including microvascularity. In this study, we evaluated the microvascular network complexity of six cases of human glioblastoma multiforme quantifying the surface fractal dimension on CD34 immunostained specimens. The microvascular fractal dimension was estimated by applying the box-counting algorithm. As the fractal dimension depends on the density, size and shape of the vessels, and their distribution pattern, we defined it as an index of the whole complexity of microvascular architecture and compared it with the uptake of (11)C-methionine (MET) assessed by PET. The different fractal dimension values observed showed that the same histological category of brain tumor had different microvascular network architectures. Fractal dimension ranged between 1.19 and 1.77 (mean: 1.415+/-0.225), and the uptake of (11)C-methionine ranged between 1.30 and 5.30. A statistically significant direct correlation between the microvascular fractal dimension and the uptake of (11)C-methionine (p=0.02) was found. Our preliminary findings indicate that that vascularity (estimated on the histologic specimens by means of the fractal dimension) and (11)C-methionine uptake (assessed by PET) closely correlate in glioblastoma multiforme and that microvascular fractal dimension can be a useful parameter to objectively describe and quantify the geometrical complexity of the microangioarchitecture in glioblastoma multiforme.
神经影像学和代谢成像在原发性和转移性脑肿瘤患者的评估中是一项基本的诊断程序。能够量化肿瘤血管生成的客观参数与成像数据之间的相关性可能会提高我们对潜在病理生理学的理解,并有可能评估脑肿瘤的治疗效果。迄今为止,只有少数研究将测量脑肿瘤新生血管的定量参数与正电子发射断层扫描(PET)扫描中通过氨基酸摄取测量的代谢谱相关联。分形几何为描述和量化包括微血管在内的复杂解剖系统提供了新的数学工具。在这项研究中,我们通过对 CD34 免疫染色标本进行计数算法,评估了 6 例人类多形性胶质母细胞瘤的微血管网络复杂性,量化了表面分形维数。分形维数取决于血管的密度、大小和形状及其分布模式,因此我们将其定义为微血管结构整体复杂性的指标,并将其与通过 PET 评估的(11)C-蛋氨酸(MET)摄取进行比较。观察到的不同分形维数值表明,相同组织学类别的脑肿瘤具有不同的微血管网络结构。分形维数范围在 1.19 到 1.77 之间(平均值:1.415+/-0.225),(11)C-蛋氨酸摄取范围在 1.30 到 5.30 之间。微血管分形维数与(11)C-蛋氨酸摄取之间存在统计学上显著的直接相关性(p=0.02)。我们的初步发现表明,血管生成(通过分形维数在组织学标本上估计)和(11)C-蛋氨酸摄取(通过 PET 评估)在胶质母细胞瘤中密切相关,微血管分形维数可以成为客观描述和量化胶质母细胞瘤微血管结构几何复杂性的有用参数。