Tanabe Naoya, Sato Susumu, Suki Béla, Hirai Toyohiro
Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Department of Biomedical Engineering, Boston University, Boston, MA, United States.
Front Physiol. 2020 Dec 21;11:603197. doi: 10.3389/fphys.2020.603197. eCollection 2020.
Chest CT is often used for localizing and quantitating pathologies associated with chronic obstructive pulmonary disease (COPD). While simple measurements of areas and volumes of emphysema and airway structure are common, these methods do not capture the structural complexity of the COPD lung. Since the concept of fractals has been successfully applied to evaluate complexity of the lung, this review is aimed at describing the fractal properties of airway disease, emphysema, and vascular abnormalities in COPD. An object forms a fractal if it exhibits the property of self-similarity at different length scales of evaluations. This fractal property is governed by power-law functions characterized by the fractal dimension (FD). Power-laws can also manifest in other statistical descriptors of structure such as the size distribution of emphysema clusters characterized by the power-law exponent D. Although D is not the same as FD of emphysematous clusters, it is a useful index to characterize the spatial pattern of disease progression and predict clinical outcomes in patients with COPD. The FD of the airway tree shape and the D of the size distribution of airway branches have been proposed indexes of structural assessment and clinical predictions. Simulations are also useful to understand the mechanism of disease progression. Therefore, the power-law and fractal analysis of the parenchyma and airways, especially when combined with computer simulations, could lead to a better understanding of the structural alterations during the progression of COPD and help identify subjects at a high risk of severe COPD.
胸部CT常用于定位和量化与慢性阻塞性肺疾病(COPD)相关的病变。虽然对肺气肿和气道结构的面积和体积进行简单测量很常见,但这些方法无法捕捉COPD肺部的结构复杂性。由于分形概念已成功应用于评估肺部复杂性,本综述旨在描述COPD中气道疾病、肺气肿和血管异常的分形特性。如果一个物体在不同的评估长度尺度上表现出自相似性,那么它就形成了一个分形。这种分形特性由以分形维数(FD)为特征的幂律函数控制。幂律也可以体现在结构的其他统计描述符中,如以幂律指数D为特征的肺气肿簇的大小分布。虽然D与肺气肿簇的FD不同,但它是表征疾病进展空间模式和预测COPD患者临床结果的有用指标。气道树形的FD和气道分支大小分布的D已被提出作为结构评估和临床预测的指标。模拟对于理解疾病进展机制也很有用。因此,对实质和气道进行幂律和分形分析,特别是与计算机模拟相结合时,可能会更好地理解COPD进展过程中的结构改变,并有助于识别重度COPD高危患者。