Advertisement
Pediatric Radiology| Volume 75, P111-118, July 2021

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

      Highlights

      • Age, sex, and height are predictors of quantitative CT parameters in children
      • Lung density decreases linearly, but lung volume and mass increase exponentially
      • As children grow, density histogram shows a right-skewed distribution

      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.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Clinical Imaging
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

      1. Schittny JC, Mund SI, Stampanoni M (2008) Evidence and structural mechanism for late lung alveolarization. Am J Physiol Lung Cell Mol Physiol 294 (2):L246-L254. doi:https://doi.org/10.1152/ajplung.00296.2007.

        • Schittny J.C.
        Development of the lung.
        Cell Tissue Res. 2017; 367: 427-444https://doi.org/10.1007/s00441-016-2545-0
      2. Thacker PG, Vargas SO, Fishman MP, Casey AM, Lee EY (2016) Current update on interstitial lung disease of infancy: new classification system, diagnostic evaluation, imaging algorithms, imaging findings, and prognosis. Radiol Clin North Am 54 (6):1065–1076. doi:https://doi.org/10.1016/j.rcl.2016.05.012.

        • Long F.R.
        • Williams R.S.
        • Castile R.G.
        Inspiratory and expiratory CT lung density in infants and young children.
        Pediatr Radiol. 2005; 35: 677-683https://doi.org/10.1007/s00247-005-1450-6
        • Stein J.M.
        • Walkup L.L.
        • Brody A.S.
        • Fleck R.J.
        • Woods J.C.
        Quantitative CT characterization of pediatric lung development using routine clinical imaging.
        Pediatr Radiol. 2016; 46: 1804-1812https://doi.org/10.1007/s00247-016-3686-8
        • Spielberg D.R.
        • Walkup L.L.
        • Stein J.M.
        • et al.
        Quantitative CT scans of lung parenchymal pathology in premature infants ages 0-6 years.
        Pediatr Pulmonol. 2018; 53: 316-323https://doi.org/10.1002/ppul.23921
        • Rao L.
        • Tiller C.
        • Coates C.
        • et al.
        Lung growth in infants and toddlers assessed by multi-slice computed tomography.
        Acad Radiol. 2010; 17: 1128-1135https://doi.org/10.1016/j.acra.2010.04.012
        • American Association of Physicists in Medicine
        The measure, reporting and management of radiation dose in CT. Report # 96 of AAPM task group 23 of the diagnostic imaging council CT committee.
        2008
        • Mascalchi M.
        • Camiciottoli G.
        • Diciotti S.
        Lung densitometry: why, how and when.
        J Thorac Dis. 2017; 9: 3319-3345https://doi.org/10.21037/jtd.2017.08.17
        • Podolanczuk A.J.
        • Oelsner E.C.
        • Barr R.G.
        • et al.
        High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.
        Eur Respir J. 2016; 48: 1442-1452https://doi.org/10.1183/13993003.00129-2016
        • Rosenblum L.J.
        • Mauceri R.A.
        • Wellenstein D.E.
        • et al.
        Density patterns in the normal lung as determined by computed tomography.
        Radiology. 1980; 137: 409-416https://doi.org/10.1148/radiology.137.2.7433674
        • Lee K.N.
        • Yoon S.K.
        • Sohn C.H.
        • Choi P.J.
        • Webb W.R.
        Dependent lung opacity at thin-section CT: evaluation by spirometrically-gated CT of the influence of lung volume.
        Korean J Radiol. 2002; 3: 24-29https://doi.org/10.3348/kjr.2002.3.1.24
        • Verschakelen J.A.
        • Van fraeyenhoven L.
        • Laureys G.
        • Demedts M.
        • Baert A.L.
        Differences in CT density between dependent and nondependent portions of the lung: influence of lung volume.
        AJR Am J Roentgenol. 1993; 161: 713-717https://doi.org/10.2214/ajr.161.4.8372744
        • Rosenthal M.
        • Cramer D.
        • Bain S.H.
        • Denison D.
        • Bush A.
        • Warner J.O.
        Lung function in white children aged 4 to 19 years: II--single breath analysis and plethysmography.
        Thorax. 1993; 48: 803-808https://doi.org/10.1136/thx.48.8.803
      3. Castile R, Filbrun D, Flucke R, Franklin W, McCoy K (2000) Adult-type pulmonary function tests in infants without respiratory disease. Pediatr Pulmonol 30 (3):215–227. doi:10.1002/1099-0496(200009)30:3<215::aid-ppul6>3.0.co;2-v.

      4. Coppoletta JM, Wolbach SB (1933) Body length and organ weights of infants and children: a study of the body length and normal weights of the more important vital organs of the body between birth and twelve years of age. Am J Pathol 9 (1):55–70.

      5. Soliman A, De Sanctis V, Elalaily R, Bedair S (2014) Advances in pubertal growth and factors influencing it: can we increase pubertal growth? Indian journal of endocrinology and metabolism 18 (Suppl 1):S53–62. doi:https://doi.org/10.4103/2230-8210.145075.

        • Loeh B.
        • Brylski L.T.
        • von der Beck D.
        • et al.
        Lung CT densitometry in idiopathic pulmonary fibrosis for the prediction of natural course, severity, and mortality.
        Chest. 2019; 155: 972-981https://doi.org/10.1016/j.chest.2019.01.019
      6. . Coxson HO, Dirksen A, Edwards LD, Yates JC, Agusti A, Bakke P, Calverley PM, Celli B, Crim C, Duvoix A, Fauerbach PN, Lomas DA, Macnee W, Mayer RJ, Miller BE, Müller NL, Rennard SI, Silverman EK, Tal-Singer R, Wouters EF, Vestbo J, Evaluation of CLtIPSEI (2013) the presence and progression of emphysema in COPD as determined by CT scanning and biomarker expression: a prospective analysis from the ECLIPSE study. Lancet Respir Med 1 (2):129–136. doi:https://doi.org/10.1016/S2213-2600(13)70006-7.