Grizzi Fabio, Russo Carlo, Colombo Piergiuseppe, Franceschini Barbara, Frezza Eldo E, Cobos Everardo, Chiriva-Internati Maurizio
Scientific Direction, Istituto Clinico Humanitas, Via Manzoni 56-20089 Rozzano, Milan, Italy.
BMC Cancer. 2005 Feb 8;5:14. doi: 10.1186/1471-2407-5-14.
Modeling the complex development and growth of tumor angiogenesis using mathematics and biological data is a burgeoning area of cancer research. Architectural complexity is the main feature of every anatomical system, including organs, tissues, cells and sub-cellular entities. The vascular system is a complex network whose geometrical characteristics cannot be properly defined using the principles of Euclidean geometry, which is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, fractal geometry is a more powerful means of quantifying the spatial complexity of real objects.
This paper introduces the surface fractal dimension (Ds) as a numerical index of the two-dimensional (2-D) geometrical complexity of tumor vascular networks, and their behavior during computer-simulated changes in vessel density and distribution.
We show that Ds significantly depends on the number of vessels and their pattern of distribution. This demonstrates that the quantitative evaluation of the 2-D geometrical complexity of tumor vascular systems can be useful not only to measure its complex architecture, but also to model its development and growth.
Studying the fractal properties of neovascularity induces reflections upon the real significance of the complex form of branched anatomical structures, in an attempt to define more appropriate methods of describing them quantitatively. This knowledge can be used to predict the aggressiveness of malignant tumors and design compounds that can halt the process of angiogenesis and influence tumor growth.
利用数学和生物学数据对肿瘤血管生成的复杂发展和生长进行建模是癌症研究中一个新兴的领域。结构复杂性是包括器官、组织、细胞和亚细胞实体在内的每个解剖系统的主要特征。血管系统是一个复杂的网络,其几何特征无法用欧几里得几何原理恰当定义,欧几里得几何只能解释自然界中几乎不可能找到的规则和平滑物体。然而,分形几何是量化真实物体空间复杂性的更有力手段。
本文引入表面分形维数(Ds)作为肿瘤血管网络二维(2-D)几何复杂性的数值指标,以及其在计算机模拟的血管密度和分布变化过程中的行为。
我们表明,Ds显著取决于血管数量及其分布模式。这表明对肿瘤血管系统二维几何复杂性的定量评估不仅有助于测量其复杂结构,还能对其发展和生长进行建模。
研究新生血管的分形特性引发了对分支解剖结构复杂形式真正意义的思考,试图定义更合适的定量描述方法。这些知识可用于预测恶性肿瘤的侵袭性,并设计能够阻止血管生成过程并影响肿瘤生长的化合物。