Title

Normal age-related quantitative CT values in the pediatric lung: from the first breath to adulthood.

Year of Publication

2021

Number of Pages

111-118

Date Published

2021 Jan 04

ISSN Number

1873-4499

Abstract

<p><strong>OBJECTIVE: </strong>To characterize the normal progression of quantitative CT parameters in normal children from birth to adulthood.</p>

<p><strong>MATERIALS AND METHODS: </strong>Patients aged 0-18&nbsp;years with non-contrast-enhanced chest CT and evidence of normal lung parenchyma were included. Patients with respiratory symptoms, incomplete anthropometric measurements, or sub-optimal imaging technique were excluded. Segmentation was performed using an open-source software with an automated threshold segmentation. The following parameters were obtained: mean lung density, kurtosis, skewness, lung volume, and mass. Linear and exponential regression models were calculated with age and height as independent variables. A p-value of &lt;0.05 was considered significant.</p>

<p><strong>RESULTS: </strong>220 patients (111 females, 109 males) were included. Mean age was 9.6&nbsp;±&nbsp;5.9&nbsp;years and mean height was 133.9&nbsp;±&nbsp;35.1&nbsp;cm. Simple linear regression showed a significant relationship between mean lung density with age (R 2&nbsp;=&nbsp;0.70) and height (R 2&nbsp;=&nbsp;0.73). Kurtosis displayed a significant exponential correlation with age (R 2&nbsp;=&nbsp;0.70) and height (R 2&nbsp;=&nbsp;0.71). Skewness showed a significant exponential correlation with age (R 2&nbsp;=&nbsp;0.71) and height (R 2&nbsp;=&nbsp;0.73). Lung mass showed a correlation with age (R 2&nbsp;=&nbsp;0.93) and height (R 2&nbsp;=&nbsp;0.92). Exponential regression showed a significant relationship between lung volume with age (R 2&nbsp;=&nbsp;0.88) and height (R 2&nbsp;=&nbsp;0.93).</p>

<p><strong>CONCLUSION: </strong>Quantitative CT parameters of the lung parenchyma demonstrate changes from birth to adulthood. As children grow, the mean lung density decreases, and the lung parenchyma becomes more homogenous.</p>

DOI

10.1016/j.clinimag.2020.12.021

Alternate Title

Clin Imaging

PMID

33524938

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