Title | Normal age-related quantitative CT values in the pediatric lung: from the first breath to adulthood. |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | Barrera CA, Andronikou S, Tapia IE, White AM, Biko DM, Rapp JB, Zhu X, Otero HJ |
Journal | Clin Imaging |
Volume | 75 |
Pagination | 111-118 |
Date Published | 2021 Jan 04 |
ISSN | 1873-4499 |
Abstract | OBJECTIVE: To characterize the normal progression of quantitative CT parameters in normal children from birth to adulthood. MATERIALS AND METHODS: Patients aged 0-18 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 <0.05 was considered significant. RESULTS: 220 patients (111 females, 109 males) were included. Mean age was 9.6 ± 5.9 years and mean height was 133.9 ± 35.1 cm. Simple linear regression showed a significant relationship between mean lung density with age (R 2 = 0.70) and height (R 2 = 0.73). Kurtosis displayed a significant exponential correlation with age (R 2 = 0.70) and height (R 2 = 0.71). Skewness showed a significant exponential correlation with age (R 2 = 0.71) and height (R 2 = 0.73). Lung mass showed a correlation with age (R 2 = 0.93) and height (R 2 = 0.92). Exponential regression showed a significant relationship between lung volume with age (R 2 = 0.88) and height (R 2 = 0.93). CONCLUSION: 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. |
DOI | 10.1016/j.clinimag.2020.12.021 |
Alternate Journal | Clin Imaging |
PubMed ID | 33524938 |