ArticleJournal of applied physiology (Bethesda, Md. : 1985)2018
Metrics of lung tissue heterogeneity depend on BMI but not age.
Article in Journal of applied physiology (Bethesda, Md. : 1985), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 11 citations in OpenAlex.
- The Association between the Body Mass Index, Chronic Obstructive Pulmonary Disease and SUV of the Non-Tumorous Lung in the Pretreatment [Diagnostics (Basel, Switzerland) · 2024Article
- Asynchronous changes of normal lung lobes during respiration based on quantitative computed tomography (CT).Quantitative imaging in medicine and surgery · 2022Article
- Deriving Regionally Specific Biomarkers of Emphysema and Small Airways Disease Using Variable Threshold Parametric Response Mapping on Volumetric Lung CT Images.Academic radiology · 2022Article
- Could automated analysis of chest X-rays detect early bronchiectasis in children?European journal of pediatrics · 2021Article
- Estimating a Sleep Apnea Hypopnea Index Based on the ERB Correlation Dimension of Snore Sounds.Frontiers in digital health · 2020Article
- A clinical predictive model for the long-term survival of progressive fibrosis interstitial lung disease patients.Therapeutic advances in respiratory diseaseArticle
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Altered parenchymal microstructure and complexity have been observed in older age. How to distinguish between healthy, expected changes and early signs of pathology remains poorly understood. An objective quantitative analysis of computed tomography imaging was conducted to compare mean lung density, tissue density distributions, and tissue heterogeneity in 16 subjects, 8 aged >60 yr who were gender and body mass index matched with 8 subjects aged <30 yr. Subjects had never been smokers, with no prior respiratory disease, and no radiologically identified abnormalities on computed tomography. Volume-controlled breath hold imaging acquired at 80% vital capacity (end inspiration) and 55% vital capacity (end expiration) were used for analysis. Mean lung density was not different between the age groups at end inspiration ( P = 0.806) but was larger in the younger group at end expiration (0.26 ± 0.033 vs. 0.22 ± 0.026, P = 0.008), as is expected due to increased air trapping in the older population. However, gravitational gradients of tissue density did not differ with age; the only difference in distribution of tissue density between the two age groups was a lower density in the apices of the older group at end expiration. The heterogeneity of the lung tissue assessed using two metrics showed significant differences between end inspiration and end expiration, no dependence on age, and a significant relationship with body mass index at both lung volumes when heterogeneity was calculated using quadtree decomposition but only at end expiration when using a fractal dimension. NEW & NOTEWORTHY Changes to lung tissue heterogeneity can be a normal part of aging but can also be an early indicator of disease. We use novel techniques, which have previously not been used on thoracic computed tomography imaging, to quantify lung tissue heterogeneity in young and old healthy subjects. Our results show no dependence on age but a significant correlation with body mass index.
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