Computed tomography quantification of tracheal abnormalities in COPD and their influence on airflow limitation

Item does not contain fulltextPURPOSE: To present a method to automatically quantify tracheal morphology changes during breathing and investigate its contribution to airflow impairment when adding CT measures of emphysema, airway wall thickness, air trapping and ventilation. METHODS: Because tracheal abnormalities often occur localized, a method is presented that automatically determines the most abnormal trachea section based on automatically computed sagittal and coronal lengths. In this most abnormal section, trachea morphology is encoded using four equiangular rays from the center of the trachea and the normalized lengths of these rays are used as features in a classification scheme. Consequently, trachea measurements are used as input for classification into GOLD stages in addition to emphysema, air trapping and ventilation. A database of 200 subjects distributed across all GOLD stages is used to evaluate the classification with a k nearest neighbour algorithm. Performance is assessed in two experimental settings: (a) when only inspiratory scans are taken; (b) when both inspiratory and expiratory scans are available. RESULTS: Given only an inspiratory CT scan, measuring tracheal shape provides complementary information only to emphysema measurements. The best performing set in the inspiratory setting was a combination of emphysema and bronchial measurements. The best performing feature set in the inspiratory-expiratory setting includes measurements of emphysema, ventilation, air trapping, and trachea. Inspiratory and inspiratory-expiratory settings showed similar performance. CONCLUSIONS: The fully automated system presented in this study provides information on trachea shape at inspiratory and expiratory CT. Addition of tracheal morphology features improves the ability of emphysema and air trapping CT-derived measurements to classify COPD patients into GOLD stages and may be relevant when investigating different aspects of COPD

CT-based weight assessment of lung lobes: Comparison with ex vivo measurements

PURPOSE We aimed to evaluate the validity of lung lobe weight assessment via computed tomography (CT) by comparing CT-derived and ex vivo measurements. MATERIALS AND METHODS Unenhanced CT scanning was performed in 30 consecutive patients before lobectomy for lung cancer. The CT images were analyzed using research software after allowing for lobar weight quantitation. The lobar weight estimated by CT was then compared with that measured after surgery using a precision scale (ex vivo measurement). Comparisons as well as assessment of intra- and interoperator variability were conducted using the Bland-Altman method and the coefficient of repeatability (CR). Correlations were examined using Pearson's correlation analysis. RESULTS Comparison analyses were feasible for 28 cases. The ex vivo lobe weight was 186.2 +/- 57.3 g, whereas the weights measured by the two operators by CT were 190.0 +/- 55 and 182.4 +/- 58.2 g, respectively. As compared with ex vivo weights, the CR was 36.4 for operator 1 and 50.4 for operator 2; the mean differences were 3.8 and -3.8 for operators 1 and 2, respectively. The intraoperator and interoperator CR were 20.9 and 36.6, respectively. The mean differences for the intra- and interoperator analysis were -1.5 and -7.5, respectively. The correlation was very high between CT-based and ex vivo measurements (r=0.95 and r=0.90 for operators 1 and 2, respectively; P < 0.001). CONCLUSION Estimation of lung lobe weight by semi-automated CT analysis is sufficiently reproducible and in agreement with ex vivo measurements

Lobe-wise assessment of lung volume and density distribution in lung transplant patients and value for early detection of bronchiolitis obliterans syndrome

Purpose: To evaluate quantitative computed tomography (CT) measurements of the lung parenchyma in lung transplant (LTx) patients for early detection of the bronchiolitis obliterans syndrome (BOS). Materials and Methods: 359 CT scans of 122 lung transplant patients were evaluated. Measurements of lung volume and density were performed for the whole lung and separately for each lobe. For longitudinal analysis the difference between the baseline at 6 months after LTx and follow-up examinations was calculated. Patients with and without BOS (matched 1:2) were compared at two different time points, the last examination before the BOS onset and the first examination within one year after BOS onset. Results: 30 patients developed BOS during the follow-up period. Longitudinal changes in the lung volume and lung density measured on CT differed significantly between those patients with and without early BOS, in particular the difference of the inspiratory and expiratory lung volume (p < 0.001), the ratio of the expiratory and inspiratory lung volume (p < 0.001-p = 0.001) and MLD (p < 0.001-p = 0.001), the volume on expiration (p < 0.001-p = 0.007), the MLD on expiration (p < 0.001-p = 0.007), and the percentiles on expiration (p < 0.001-p = 0.002) with an increase of lung volume and a decrease of lung density. Changes were pronounced in the lower lobes. Before BOS onset, patients with and without future development of BOS showed no significant differences. Conclusion: Longitudinal changes of lung volume and lung density measured on CT start markedly at BOS onset with increased lung volume and decreased lung density indicating increased inflation levels. Even though this method may help to diagnose BOS at onset it is not useful as a predictor for BOS before disease onset

Composite finite elements for 3D image based computing

We present an algorithmical concept for modeling and simulation with partial differential equations (PDEs) in image based computing where the computational geometry is defined through previously segmented image data. Such problems occur in applications from biology and medicine where the underlying image data has been acquired through, e.g. computed tomography (CT), magnetic resonance imaging (MRI) or electron microscopy (EM). Based on a level-set description of the computational domain, our approach is capable of automatically providing suitable composite finite element functions that resolve the complicated shapes in the medical/biological data set. It is efficient in the sense that the traversal of the grid (and thus assembling matrices for finite element computations) inherits the efficiency of uniform grids away from complicated structures. The method’s efficiency heavily depends on precomputed lookup tables in the vicinity of the domain boundary or interface. A suitable multigrid method is used for an efficient solution of the systems of equations resulting from the composite finite element discretization. The paper focuses on both algorithmical and implementational details. Scalar and vector valued model problems as well as real applications underline the usability of our approach