Jarred R Mondoñedo1, Susumu Sato2, Tsuyoshi Oguma2, Shigeo Muro3, Adam H Sonnenberg4, Dean Zeldich5, Harikrishnan Parameswaran6, Toyohiro Hirai2, Béla Suki7. 1. Department of Biomedical Engineering, Boston University College of Engineering, Boston, MA; Boston University School of Medicine, Boston, MA. 2. Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan. 3. Department of Respiratory Medicine, Nara Medical University, Nara, Japan. 4. Department of Systems Engineering, Boston University College of Engineering, Boston, MA. 5. Department of Biomedical Engineering, Boston University College of Engineering, Boston, MA. 6. Department of Bioengineering, Northeastern University, Boston, MA. 7. Department of Biomedical Engineering, Boston University College of Engineering, Boston, MA. Electronic address: bsuki@bu.edu.
Abstract
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 < -960 Hounsfield units. 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 FEV1 (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.
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 < -960 Hounsfield units. 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 FEV1 (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.
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