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CT Imaging-Based Low-Attenuation Super Clusters in Three Dimensions and the Progression of Emphysema

机译:基于CT影像的三维低衰减超级团簇及肺气肿的进展

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Background Distributions of low-attenuation areas in two-dimensional (2-D) CT lung slices are used to quantify parenchymal destruction in patients with COPD. However, these segmental approaches are limited and may not reflect the true three-dimensional (3-D) tissue processes that drive emphysematous changes in the lung. The goal of this study was to instead evaluate distributions of 3-D low-attenuation volumes, which we hypothesized would follow a power law distribution and provide a more complete assessment of the mechanisms underlying disease progression. Methods CT scans and pulmonary function test results were acquired from an observational database for N?= 12 patients with COPD and N?= 12 control patients. The data set included baseline and two annual follow-up evaluations in patients with COPD. Three-dimensional representations of the lungs were reconstructed from 2-D axial CT slices, with low-attenuation volumes identified as contiguous voxels Results Low-attenuation sizes generally followed a power law distribution, with the exception of large, individual outliers termed "super clusters," which deviated from the expected distribution. Super cluster volume was correlated with disease severity (%?total low attenuation, ρ = 0.950) and clinical measures of lung function including FEVsub1/sub (ρ?= –0.849) and diffusing capacity of the lung for carbon monoxide Dlco (ρ?= –0.874). To interpret these?results, we developed a personalized computational model of super cluster emergence. Simulations indicated disease progression was more likely to occur near existing emphysematous regions, giving rise to a biomechanical, force-induced mechanism of super cluster growth. Conclusions Low-attenuation super clusters are defining, quantitative features of parenchymal destruction that dominate disease progression, particularly in advanced COPD.
机译:二维(2-D)CT肺切片中低衰减区域的背景分布用于量化COPD患者的实质破坏。但是,这些分段方法是有限的,可能无法反映出驱动肺气肿改变的真正的三维(3-D)组织过程。这项研究的目的是评估3-D低衰减量的分布,我们假设其将遵循幂定律分布,并提供对疾病进展机制的更完整评估。方法:从观察数据库中获得N = 12例COPD患者和N = 12例对照患者的CT扫描和肺功能检查结果。该数据集包括COPD患者的基线和两项年度随访评估。从二维轴向CT切片重建肺部的三维图像,将低衰减量确定为连续体素结果低衰减大小通常遵循幂定律分布,唯一的大型异常值称为“超簇” ”,这与预期的分布有所不同。超群体积与疾病严重程度(总低衰减百分比,ρ= 0.950)以及肺功能的临床指标(包括FEV 1 (ρ?= –0.849))和肺对碳的扩散能力相关。一氧化碳Dlco(ρ?= –0.874)。为了解释这些结果,我们开发了超级集群出现的个性化计算模型。模拟表明疾病进展更可能发生在现有的气肿区域附近,从而引起了生物力学,力诱导的超簇生长机制。结论低衰减的超级簇是主要的实质性破坏特征,定量特征主导着疾病的发展,特别是在晚期COPD中。

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