Variability of bronchial measurements obtained by sequential CT using two computer-based methods

Abstract

This study aimed to evaluate the variability of lumen (LA) and wall area (WA) measurements obtained on two successive MDCT acquisitions using energy-driven contour estimation (EDCE) and full width at half maximum (FWHM) approaches. Both methods were applied to a database of segmental and subsegmental bronchi with LA > 4 mm(2) containing 42 bronchial segments of 10 successive slices that best matched on each acquisition. For both methods, the 95% confidence interval between repeated MDCT was between -1.59 and 1.5 mm(2) for LA, and -3.31 and 2.96 mm(2) for WA. The values of the coefficient of measurement variation (CV(10), i.e., percentage ratio of the standard deviation obtained from the 10 successive slices to their mean value) were strongly correlated between repeated MDCT data acquisitions (r > 0.72; p < 0.0001). Compared with FWHM, LA values obtained using EDCE were higher for LA < 15 mm(2), whereas WA values were lower for bronchi with WA < 13 mm(2); no systematic EDCE underestimation or overestimation was observed for thicker-walled bronchi. In conclusion, variability between CT examinations and assessment techniques may impair measurements. Therefore, new parameters such as CV(10) need to be investigated to study bronchial remodeling. Finally, EDCE and FWHM are not interchangeable in longitudinal studies.

Computed Tomographic Imaging of the Airways in COPD and Asthma

“…In addition, the interscan variability has to be established upfront. 72 This is a crucial prerequisite in order to define a threshold permitting to consider modifications in airway dimensions as significant.…”

Multidetector Row Computed Tomography to Assess Changes in Airways Linked to Asthma Control

“…Moreover, our results suggest that other parameters aside from WA should be considered for the evaluation of asthma control. These parameters would have to take into account the heterogeneity of bronchial geometry from one bronchus to another or along the bronchial axis [21]. Another interesting approach would be to compute fluid dynamics from the realistic 3-dimensional reconstructions of the lumen.…”

“…Such an approach associates a 3-dimensional computation of the central axis of the tracheobronchial tree (leading to skeletonization of the airway tree) and a 2-dimensional segmentation of bronchial boundaries (leading to the quantification of LA and WA) [11,15]. The bronchial segmentation is performed using an energy-driven contour estimation method which has proved to be as accurate as the full width at half maximum principle but induces less overestimation of LA for the smallest bronchi [21]. …”

“…p < 0.05 was considered statistically significant, taking into account that the variation of bronchial dimensions between values at baseline and at the end of treatment should exceed the 95% interscan variability of measurements. This variability was established using the Bland and Altman approach according to the methodology defined by Brillet et al [21], giving thresholds of 1.6 mm 2 , 2.71 mm 2 , and 2 mm for LA, WA, and Lg, respectively.…”

In Vivo Computed Tomography as a Research Tool to Investigate Asthma and COPD: Where Do We Stand?

“…Semiautomatic computational methods have been later developed to allow automated segmentation of the wall contours [12–14] and the bronchial tree [15, 16]. Briefly, active energy-driven contours are a region-based active contour model to extract the local image information.…”