Quantifying lung and diaphragm morphology using radiographs in normative pediatric subjects, and predicting CT‐derived lung volume

Abstract

Objective To quantify the effect of age on two‐dimensional (2D) radiographic lung and diaphragm morphology and determine if 2D radiographic lung measurements can be used to estimate computer tomography (CT)‐derived lung volume in normative pediatric subjects. Materials and Methods Digitally reconstructed radiographs (DRRs) were created using retrospective chest CT scans from 77 pediatric male and female subjects aged birth to 19 years. 2D lung and diaphragm measurements were made on the DRRs using custom MATLAB code, and Spearman correlations and exponential regression equations were used to relate 2D measurements with age. In addition, 3D lung volumes were segmented using CT scans, and power regression equations were fitted to predict each lung's CT‐derived volume from 2D lung measurements. The coefficient of determination (R2) and standard error of the estimate (SEE) were used to assess the precision of the predictive equations with p < .05 indicating statistical significance. Results All 2D radiographic lung and diaphragm measurements showed statistically significant positive correlations with age (p < .01), including lung major axis (Spearman rho ≥ 0.90). Precise estimations of CT‐derived lung volumes can be made using 2D lung measurements (R2 ≥ 0.95), including lung major axis (R2 ≥ 0.97). Interpretations The reported pediatric age‐specific reference data on 2D lung and diaphragm morphology and growth rates could be clinically used to identify lung and diaphragm pathologies during chest X‐ray evaluations. The simple, precise, and clinically adaptable radiographic method for estimating CT‐derived lung volumes may be used when pulmonary function tests are not readily available or difficult to perform.

In vitro coupled motions of the whole human thoracic and lumbar spine with rib cage

“…Intuitively, the results of this study lack the direct clinical utility possessed by results of in vivo studies that are influenced by the presence of other anatomical structures 59 as well as the neuromuscular system, a significant contributing factor to spinal coupled motion 43 . To better simulate physiological loading conditions, some previous in vitro studies have applied compressive preload or follower load during testing 10,53,54,60–64 .…”

Patient-specific finite element modeling of scoliotic curve progression using region-specific stress-modulated vertebral growth

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