Reversibility of trapped air on chest computed tomography in cystic fibrosis patients.

PURPOSE: To investigate changes in trapped air volume and distribution over time and compare computed tomography (CT) with pulmonary function tests for determining trapped air. METHODS: Thirty children contributed two CTs and pulmonary function tests over 2 years. Localized changes in trapped air on CT were assessed using image analysis software, by deforming the CT at timepoint 2 to match timepoint 1, and measuring the volume of stable (TAstable), disappeared (TAdisappeared) and new (TAnew) trapped air as a proportion of total lung volume. We used the difference between total lung capacity measured by plethysmography and helium dilution, residual volume to total lung capacity ratio, forced expiratory flow at 75% of vital capacity, and maximum mid-expiratory flow as pulmonary function test markers of trapped air. Statistical analysis included Wilcoxon's signed rank test and Spearman correlation coefficients. RESULTS: Median (range) age at baseline was 11.9 (5-17) years. Median (range) of trapped air was 9.5 (2-33)% at timepoint 1 and 9.0 (0-25)% at timepoint 2 (p=0.49). Median (range) TAstable, TAdisappeared and TAnew were respectively 3.0 (0-12)%, 5.0 (1-22)% and 7.0 (0-20)%. Trapped air on CT correlated statistically significantly with all pulmonary function measures (p<0.01), other than residual volume to total lung capacity ratio (p=0.37). CONCLUSION: Trapped air on CT did not significantly progress over 2 years, may have a substantial stable component, and is significantly correlated with pulmonary function markers.

Mass preserving image registration for lung CT.

This paper presents a mass preserving image registration algorithm for lung CT images. To account for the local change in lung tissue intensity during the breathing cycle, a tissue appearance model based on the principle of preservation of total lung mass is proposed. This model is incorporated into a standard image registration framework with a composition of a global affine and several free-form B-Spline transformations with increasing grid resolution. The proposed mass preserving registration method is compared to registration using the sum of squared intensity differences as a similarity function on four groups of data: 44 pairs of longitudinal inspiratory chest CT scans with small difference in lung volume; 44 pairs of longitudinal inspiratory chest CT scans with large difference in lung volume; 16 pairs of expiratory and inspiratory CT scans; and 5 pairs of images extracted at end exhale and end inhale phases of 4D-CT images. Registration errors, measured as the average distance between vessel tree centerlines in the matched images, are significantly lower for the proposed mass preserving image registration method in the second, third and fourth group, while there is no statistically significant difference between the two methods in the first group. Target registration error, assessed via a set of manually annotated landmarks in the last group, was significantly smaller for the proposed registration method.

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.

Early detection of emphysema progression.

Emphysema is one of the most widespread diseases in subjects with smoking history. The gold standard method for estimating the severity of emphysema is a lung function test, such as forced expiratory volume in first second (FEV1). However, several clinical studies showed that chest CT scans offer more sensitive estimates of emphysema progression. The standard CT densitometric score of emphysema is the relative area of voxels below a threshold (RA). The RA score is a global measurement and reflects the overall emphysema progression. In this work, we propose a framework for estimation of local emphysema progression from longitudinal chest CT scans. First, images are registered to a common system of coordinates and then local image dissimilarities are computed in corresponding anatomical locations. Finally, the obtained dissimilarity representation is converted into a single emphysema progression score. We applied the proposed algorithm on 27 patients with severe emphysema with CT scans acquired five time points, at baseline, after 3, after 12, after 21 and after 24 or 30 months. The results showed consistent emphysema progression with time and the overall progression score correlates significantly with the increase in RA score.

Weight preserving image registration for monitoring disease progression in lung CT.

We present a new image registration based method for monitoring regional disease progression in longitudinal image studies of lung disease. A free-form image registration technique is used to match a baseline 3D CT lung scan onto a following scan. Areas with lower intensity in the following scan compared with intensities in the deformed baseline image indicate local loss of lung tissue that is associated with progression of emphysema. To account for differences in lung intensity owing to differences in the inspiration level in the two scans rather than disease progression, we propose to adjust the density of lung tissue with respect to local expansion or compression such that the total weight of the lungs is preserved during deformation. Our method provides a good estimation of regional destruction of lung tissue for subjects with a significant difference in inspiration level between CT scans and may result in a more sensitive measure of disease progression than standard quantitative CT measures.