Literature DB >> 29470150

Metrics of lung tissue heterogeneity depend on BMI but not age.

K Subramaniam1, A R Clark1, E A Hoffman2, M H Tawhai1.   

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 &amp; 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.

Entities:  

Keywords:  age differences; heterogeneity analysis; image processing; lung densitometry

Mesh:

Year:  2018        PMID: 29470150      PMCID: PMC6442663          DOI: 10.1152/japplphysiol.00510.2016

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  40 in total

Review 1.  Physiological changes in respiratory function associated with ageing.

Authors:  J P Janssens; J C Pache; L P Nicod
Journal:  Eur Respir J       Date:  1999-01       Impact factor: 16.671

2.  Establishing a normative atlas of the human lung: intersubject warping and registration of volumetric CT images.

Authors:  Baojun Li; Gary E Christensen; Eric A Hoffman; Geoffrey McLennan; Joseph M Reinhardt
Journal:  Acad Radiol       Date:  2003-03       Impact factor: 3.173

3.  Physiological Heterogeneity: Fractals Link Determinism and Randomness in Structures and Functions.

Authors:  James B Bassingthwaighte
Journal:  News Physiol Sci       Date:  1988-01-01

Review 4.  The comprehensive imaging-based analysis of the lung: a forum for team science.

Authors:  Eric A Hoffman; Anne V Clough; Gary E Christensen; Ching-Long Lin; Geoffrey McLennan; Joseph M Reinhardt; Brett A Simon; Milan Sonka; Merryn H Tawhai; Edwin J R van Beek; Ge Wang
Journal:  Acad Radiol       Date:  2004-12       Impact factor: 3.173

5.  Detection of age-related changes in thoracic structure and function by computed tomography, magnetic resonance imaging, and positron emission tomography.

Authors:  David S Well; Jeffrey M Meier; Anton Mahne; Mohamed Houseni; Miguel Hernandez-Pampaloni; Andrew Mong; Shipra Mishra; Ying Zhuge; Andre Souza; Jayaram K Udupa; Abass Alavi; Drew A Torigian
Journal:  Semin Nucl Med       Date:  2007-03       Impact factor: 4.446

6.  A novel model of senile lung: senescence-accelerated mouse (SAM).

Authors:  S Teramoto; Y Fukuchi; Y Uejima; K Teramoto; T Oka; H Orimo
Journal:  Am J Respir Crit Care Med       Date:  1994-07       Impact factor: 21.405

Review 7.  The lung physiome: merging imaging-based measures with predictive computational models.

Authors:  Merryn H Tawhai; Eric A Hoffman; Ching-Long Lin
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2009 Jul-Aug

8.  Aging of the lungs in asymptomatic lifelong nonsmokers: findings on HRCT.

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9.  Airspace size in lungs of lifelong non-smokers: effect of age and sex.

Authors:  M Gillooly; D Lamb
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