An index of the fractal characteristic of an airway tree is associated with airflow limitations and future body mass index reduction in COPD patients

Kinose, Daisuke; Ogawa, Emiko; Kawashima, Satoru; Matsuo-Kashiwagi, Yumiko; Yukimura-Seto, Ruriko; Yamazaki, Akio; Yoshihashi, Saiko; Hirayama, Yoko; Nakano, Yasutaka

doi:10.1152/japplphysiol.00461.2019

Cited by 3 publications

(4 citation statements)

References 31 publications

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“…The authors used data of human tracheobronchial geometry that was obtained from bronchial casts in two human lungs by Raabe et al (1976) and showed that the cumulative distribution of the internal lumen diameter of airway branches is governed by a power law. This concept was recently reproduced by Kinose et al (2020) who segmented airway tree from inspiratory CT scans and partitioned the whole tree into branches in 162 smokers with and without COPD. They measured the minimal inner CSA (iCSA) of airway branches and counted the cumulative number of airway branches N(x) having iCSA ≥ x.…”

Section: Airway Fractal Dimension and The Power-law Exponent D On Ctmentioning

confidence: 99%

“…Lung function decline, future exacerbation, and mortality (AFD: healthy 1.56, non-COPD smokers 1.52, COPD 1.45-1.50) Kinose et al, 2020 Airway lumen size distribution…”

Section: Authorsmentioning

confidence: 99%

“…performed simulations and found that AFD reflects the loss of airways which the conventional CT index of airway dimension, Pi10 (square root of the wall area of a hypothetical airway with a lumen perimeter of 10 mm), does not capture. Interestingly, Kinose et al (2020) showed that while both the power-law exponent D of iCSA and the AFD were correlated with airflow limitation, these indexes were weakly correlated with each other and proposed that the AFD based on box-counting of the airway tree and D of iCSA reflect different structural features. The AFD is related to the space-filling capacity of the entire tree in 3D whereas the power-law exponent D of the internal diameters characterizes the relative frequency of finding diameters larger than x, independent of their spatial arrangement in 3D.…”

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confidence: 99%

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Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease

et al. 2020

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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.

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Section: Airway Fractal Dimension and The Power-law Exponent D On Ctmentioning

confidence: 99%

“…Lung function decline, future exacerbation, and mortality (AFD: healthy 1.56, non-COPD smokers 1.52, COPD 1.45-1.50) Kinose et al, 2020 Airway lumen size distribution…”

Section: Authorsmentioning

confidence: 99%

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confidence: 99%

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Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease

et al. 2020

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“…Energy imbalance leading to weight loss in patients with COPD may result from increased work of breathing, chronic inflammation, acute exacerbations, and decreased energy intake due to anorexia. 10,38 Diversion from the ideal bronchial tree shape may increase the energy necessary for airflow; 39 patients with COPD showed increased EE. 40 However, patients with severe COPD tend to restrict daily activities, 41,42 potentially blunting the daily total EE increase.…”

Section: Discussionmentioning

confidence: 99%

Predictors of longitudinal changes in body weight, muscle and fat in patients with and ever‐smokers at risk of COPD

et al. 2023

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Background and ObjectiveWeight and muscle loss are predictors of poor outcomes in chronic obstructive pulmonary disease. However, to our knowledge, no study has investigated the predictors of longitudinal weight loss or its composition from functional and morphological perspectives.MethodsThis longitudinal observational study with a median follow‐up period of 5 years (range: 3.0–5.8 years) included patients with COPD and ever‐smokers at risk of COPD. Using chest computed tomography (CT) images, airway and emphysematous lesions were assessed as the square root of the wall area of a hypothetical airway with an internal perimeter of 10 mm (√Aaw at Pi10) and the percentage of low attenuation volume (LAV%). Muscle mass was estimated using cross‐sectional areas (CSAs) of the pectoralis and erector spinae muscles, and fat mass was estimated using the subcutaneous fat thickness at the level of the 8th rib measured using chest CT images. Statistical analyses were performed using the linear mixed‐effects models.ResultsIn total, 114 patients were enrolled. Their body mass index remained stable during the study period while body weight and muscle CSA decreased over time and the subcutaneous fat thickness increased. Reduced forced expiratory volume in 1 s and peak expiratory flow (PEF) at baseline predicted the future decline in muscle CSA.ConclusionSevere airflow limitation predicted future muscle wasting in patients with COPD and ever‐smokers at risk of COPD. Airflow limitation with a PEF slightly below 90% of the predicted value may require intervention to prevent future muscle loss.

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