Quantitative CT analysis in patients with pulmonary emphysema: is lung function influenced by concomitant unspecific pulmonary fibrosis?

Purpose: Quantitative analysis of CT scans has proven to be a reproducible technique, which might help to understand the pathophysiology of chronic obstructive pulmonary disease (COPD) and combined pulmonary fibrosis and emphysema. The aim of this retrospective study was to find out if the lung function of patients with COPD with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages III or IV and pulmonary emphysema is measurably influenced by high attenuation areas as a correlate of concomitant unspecific fibrotic changes of lung parenchyma. Patients and methods: Eighty-eight patients with COPD GOLD stage III or IV underwent CT and pulmonary function tests. Quantitative CT analysis was performed to determine low attenuation volume (LAV) and high attenuation volume (HAV), which are considered to be equivalents of fibrotic (HAV) and emphysematous (LAV) changes of lung parenchyma. Both parameters were determined for the whole lung, as well as peripheral and central lung areas only. Multivariate regression analysis was used to correlate HAV with different parameters of lung function. Results: Unlike LAV, HAV did not show significant correlation with parameters of lung function. Even in patients with a relatively high HAVof more than 10%, in contrast to HAV (p=0.786) only LAV showed a significantly negative correlation with forced expiratory volume in 1 second (r=−0.309, R2=0.096, p=0.003). A severe decrease of DLCO% was associated with both larger HAV (p=0.045) and larger LAV (p=0.001). Residual volume and FVC were not influenced by LAV or HAV. Conclusion: In patients with COPD GOLD stage III-IV, emphysematous changes of lung parenchyma seem to have such a strong influence on lung function, which is a possible effect of concomitant unspecific fibrosis is overwhelmed

Quantitative Analyse von Morphologie und Funktion der Lunge in Computertomographischen Aufnahmen

In clinical lung radiology, primary cancer, metastatic disease, and parenchymal diseases such as emphysema or fibrosis play central roles. In the examination of these and other lung diseases, Computed Tomography (CT) is the reference imaging modality. In current clinical routine, the standard procedure for examining lung CT data is visual inspection. However, visual inspection not only requires a large amount of concentration and time, but is also limited to a solely qualitative and highly subjective image assessment. This thesis is concerned with research, development, and evaluation of new methods in digital image processing that assist the radiologist in performing a quantitative CT-based assessment of pulmonary morphology and function in patients with parenchymal or tumorous lung disease. To support the regional analysis of the lung parenchyma in patients with parenchymal disease, fast robust methods for the automated segmentation of the lungs and their subsequent subdivision into lung lobes are developed. The lobe segmentation relies on an analysis of the vessel and airway anatomy rather than explicitly detecting the lobe-separating fissures. This makes it applicable to cases in which the fissures are concealed by pathology, incomplete, or missing. The new methods are extensively evaluated on a large heterogeneous set of pathological test cases to demonstrate their potential in the analysis of clinically relevant patient data. In the field of lung tumor analysis, previous research focused on supporting lung cancer screening by providing automatic segmentation methods for the volumetry of small pulmonary nodules. The algorithm presented in this thesis is designed to perform a fast, automated segmentation of small nodules and large lung metastases alike, and to be thereby equally suitable for application in the diagnosis of early stage lung cancer and monitoring of chemotherapy response. This flexibility is achieved by the introduction of an optimal opening procedure that, based on realistic model assumptions, permits a theoretically guaranteed separation of connected vasculature. Still, segmentation is merely the first step to volume measurement: The imaging variabilities caused by slight variations of the acquisition protocol are shown to severely impair clinical applicability of conventional segmentation-based volumetry approaches. This thesis proposes a volume quantification technique that compensates for these variabilities by exploiting the knowledge gained during segmentation and performing a selective volume averaging analysis at the tumor boundaries. Evaluation is performed on both in-vivo metastases and phantom nodules to demonstrate the robustness of the new segmentation method as well as the validity and significantly increased reproducibility of the developed volumetry technique.While the technical soundness of the developed solutions is crucial, clinical impact can only be achieved if attention is also paid to practical applicability, i.e., the capability of running robustly under clinical conditions and of blending in smoothly with the demanding radiological workflow. Thus, the developed algorithms are integrated into a software prototype that can be conveniently used by clinicians. In addition to the technical evaluation, several evaluation studies are performed by clinical experts to verify applicability and clinical usefulness of the novel methods

Quantitative Analysis of Lung Morphology and Function in Computed Tomographic Images

In clinical lung radiology, primary cancer, metastatic disease, and parenchymal diseases such as emphysema or fibrosis play central roles. In the examination of these and other lung diseases, Computed Tomography (CT) is the reference imaging modality. In current clinical routine, the standard procedure for examining lung CT data is visual inspection. However, visual inspection not only requires a large amount of concentration and time, but is also limited to a solely qualitative and highly subjective image assessment. This thesis is concerned with research, development, and evaluation of new methods in digital image processing that assist the radiologist in performing a quantitative CT-based assessment of pulmonary morphology and function in patients with parenchymal or tumorous lung disease. To support the regional analysis of the lung parenchyma in patients with parenchymal disease, fast robust methods for the automated segmentation of the lungs and their subsequent subdivision into lung lobes are developed. The lobe segmentation relies on an analysis of the vessel and airway anatomy rather than explicitly detecting the lobe-separating fissures. This makes it applicable to cases in which the fissures are concealed by pathology, incomplete, or missing. The new methods are extensively evaluated on a large heterogeneous set of pathological test cases to demonstrate their potential in the analysis of clinically relevant patient data. In the field of lung tumor analysis, previous research focused on supporting lung cancer screening by providing automatic segmentation methods for the volumetry of small pulmonary nodules. The algorithm presented in this thesis is designed to perform a fast, automated segmentation of small nodules and large lung metastases alike, and to be thereby equally suitable for application in the diagnosis of early stage lung cancer and monitoring of chemotherapy response. This flexibility is achieved by the introduction of an optimal opening procedure that, based on realistic model assumptions, permits a theoretically guaranteed separation of connected vasculature. Still, segmentation is merely the first step to volume measurement: The imaging variabilities caused by slight variations of the acquisition protocol are shown to severely impair clinical applicability of conventional segmentation-based volumetry approaches. This thesis proposes a volume quantification technique that compensates for these variabilities by exploiting the knowledge gained during segmentation and performing a selective volume averaging analysis at the tumor boundaries. Evaluation is performed on both in-vivo metastases and phantom nodules to demonstrate the robustness of the new segmentation method as well as the validity and significantly increased reproducibility of the developed volumetry technique.While the technical soundness of the developed solutions is crucial, clinical impact can only be achieved if attention is also paid to practical applicability, i.e., the capability of running robustly under clinical conditions and of blending in smoothly with the demanding radiological workflow. Thus, the developed algorithms are integrated into a software prototype that can be conveniently used by clinicians. In addition to the technical evaluation, several evaluation studies are performed by clinical experts to verify applicability and clinical usefulness of the novel methods

CADA Challenge: Rupture Risk Assessment Using Computational Fluid Dynamics

The phase 3 of the cerebral aneurysm detection and analysis (CADA) challenge involved rupture risk estimation of intracranial aneurysms using computational methods. In this work we performed computational fluid dynamics (CFD) on a subset of aneurysm cases provided by the challenge committee. A large number of aneurysm cases were available, CFD analysis using the lattice Boltzmann method (LBM) were performed on 18 of them. These 18 aneurysms were chosen on the basis of most distinct shape, size and location. Direct numerical simulations were performed to identify wall shear stress and pressure, and associate these hemodynamic quantities with the rupture status of aneurysms and eventually extrapolate those findings to other aneurysms. The results of the DNS may serve as inputs for data driven methods to identify qualitative maps of hemodynamic quantities in aneurysms. In this article we report the results of CFD and discuss hypotheses associating the flow characteristics with the rupture risk of aneurysms

Sex differences in emphysema phenotype in smokers without airflow obstruction.

Data on sex differences in emphysema are limited to chronic obstructive pulmonary disease. We aimed to verify whether such differences also exist in smokers without airflow obstruction, weighting their influence on the relationship between emphysema and clinical features. We evaluated both clinical and multidetector computed tomography (MDCT) data of 1,011 heavy smokers recruited by a lung cancer screening project. MDCT scans were analysed with software allowing lobar quantification of emphysema features. For these measures, multiple regression models were applied to assess the effect of patients sex, after allowance for age, body mass index (BMI), smoking history, forced expiratory volume in 1 s (FEV(1)) and forced vital capacity. The final study cohort consisted of 957 smokers without airflow obstruction. Compared with males, females exhibited an emphysema phenotype less extensive in each pulmonary lobe, characterised by smaller emphysematous areas and less concentrated in the core of the lung. However, in females, the increase of emphysema with age was more pronounced and displayed a more significant relationship with FEV(1)\% decline; conversely, in males there was a stronger association with the decrease in BMI. Males and females respond differently to the type and location of lung damage due to tobacco exposure. In smokers, sex influences the relationship between emphysema and clinical features

Proceedings of the Sixth International Workshop on Pulmonary Image Analysis

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