Catalin I. Fetita

Pulmonary airways: 3-D reconstruction from multislice CT and clinical investigation

In the framework of computer-aided diagnosis, this paper proposes a novel functionality for the computerized tomography (CT)-based investigation of the pulmonary airways. It relies on an energy-based three-dimensional (3-D) reconstruction of the bronchial tree from multislice CT acquisitions, up to the sixth- to seventh-order subdivisions. Global and local analysis of the reconstructed airways is possible by means of specific visualization modalities, respectively, the CT bronchography and the virtual bronchoscopy. The originality of the 3-D reconstruction approach consists in combining axial and radial propagation potentials to control the growth of a subset of low-order airways extracted from the CT volume by means of a robust mathematical morphology operator-the selective marking and depth constrained (SMDC) connection cost. The proposed approach proved to be robust with respect to a large spectrum of airway pathologies, including even severe stenosis (bronchial lumen obstruction/collapse). Validated by expert radiologists, examples of airway 3-D reconstructions are presented and discussed for both normal and pathological cases. They highlight the interest in considering CT bronchography and virtual bronchoscopy as complementary tools for clinical diagnosis and follow-up of airway diseases.

3D automated lung nodule segmentation in HRCT

A fully-automated 3D image analysis method is proposed to segment lung nodules in HRCT. A specific gray-level mathematical morphology operator, the SMDC-connection cost, acting in the 3D space of the thorax volume is defined in order to discriminate lung nodules from other dense (vascular) structures. Applied to clinical data concerning patients with pulmonary carcinoma, the proposed method detects isolated, juxtavascular and peripheral nodules with sizes ranging from 2 to 20 mm diameter. The segmentation accuracy was objectively evaluated on real and simulated nodules. The method showed a sensitivity and a specificity ranging from 85% to 97% and from 90% to 98%, respectively.

Advanced navigation tools for virtual bronchoscopy

In the framework of computer-aided diagnosis, pulmonary airway investigation based on multi-detector computerized tomography (MDCT) requires the development of specific tools for data interaction and analysis. The 3D segmentation of the bronchial tree provides radiologists with appropriate examination modalities such as CT bronchography, for a global analysis, or virtual endoscopy, for a local endoluminal diagnosis. Focusing on the latter modality, this paper proposes a set of advanced navigation and investigation tools based on the automatic extraction of the central axis (CA) of the 3D segmented airways. In the case of complex branching structures, such as the bronchial tree, the automatic CA computation is a challenging problem raising several difficulties related to geometry and topology preservation. In this respect, an original approach is presented, combining 3D distance map information and geodesic front propagation in order to accurately detect branching points and to preserve the original 3D topology of the airways, irrespective to both caliber variability with the bronchial order and to bronchial wall irregularities. The CA information is represented as a multi-valued and hierarchic tree structure, making possible automatic trajectory computation between two given points, bronchial caliber estimation in the plane orthogonal to the bronchus axis at a given location, branch indexation, and so on. These applications are illustrated on clinical data including both normal and pathological airway morphologies.

Investigation of airways using MDCT for visual and quantitative assessment in COPD patients

Multidetector computed tomography (MDCT) acquisition during a single breath hold using thin collimation provides high resolution volumetric data set permitting multiplanar and three dimensional reconstruction of the proximal airways. In chronic obstructive pulmonary disease (COPD) patients, this technique provides an accurate assessment of bronchial wall thickening, tracheobronchial deformation, outpouchings reflecting dilatation of the submucous glands, tracheobronchomalacia, and expiratory air trapping. New software developed to segment adequately the lumen and walls of the airways on MDCT scans allows quantitative assessment of the airway dimensions which has shown to be reliable in clinical practice. This technique can become important in longitudinal studies of the pathogenesis of COPD, and in the assessment of therapeutic interventions.

Virtual investigation of pulmonary airways in volumetric computed tomography

This paper addresses the issue of non‐invasive investigation and functional assessment of pulmonary airways reconstructed from multi detector computed tomography clinical acquisitions. Such an analysis combines accurate 3D meshing of the inner bronchial wall surface and navigation and interactivity tools based on a robust central axis representation. A reliable endoluminal investigation of airways via virtual bronchoscopy is possible regardless of their anatomical/pathological specificity (small caliber bronchi, severe stenoses, …). Computational fluid dynamics simulations on real airway geometries allow to assess functional modifications induced by physiopathological changes. Copyright

Multidetector row computed tomography to assess changes in airways linked to asthma control.

Background: In asthma, multidetector row computed tomography (MDCT) detects abnormalities that are related to disease severity, including increased bronchial wall thickness. However, whether these abnormalities could be related to asthma control has not been investigated yet. Objective: Our goal was to determine which changes in airways could be linked to disease control. Methods: Twelve patients with poor asthma control were included and received a salmeterol/fluticasone propionate combination daily for 12 weeks. Patients underwent clinical, functional, and MDCT examinations before and after the treatment period. MDCT examinations were performed using a low-dose protocol at a controlled lung volume (65% TLC). Bronchial lumen (LA) and wall areas (WA) were evaluated at a segmental and subsegmental level using BronCare software. Lung density was measured at the base of the lung. Baseline and end-of-treatment data were compared using the Wilcoxon signed-rank test. Results: After the 12-week treatment period, asthma control was achieved. Airflow obstruction and air trapping decreased as assessed by the changes in FEV1 (p < 0.01) and expiratory reserve volume (p < 0.01). Conversely, LA and WA did not vary significantly. However, a median decrease in LA of >10% was observed in half of the patients with a wide intra- and intersubject response heterogeneity. This was concomitant with a decrease in lung density (p < 0.02 in the anteroinferior areas). Conclusions: MDCT is insensitive for demonstrating any decrease in bronchial wall thickness. This is mainly due to changes in bronchial caliber which may be linked to modifications of the elastic properties of the bronchopulmonary system under treatment.

Bronchial tree modeling and 3D reconstruction

Providing an in-vivo and non-invasive tool for 3D reconstruction of anatomical tree structures (vascular networks and bronchial tree) from 2D or pseudo-3D data acquisition remains today a key and challenging issue for computer vision in medical imaging. In this paper, we address this issue within the specific framework of airways. Our contribution consists of a realistic 3D modeling of the bronchial tree structure. Mathematical and physical principles here involved refer to 3D mathematical morphology (3DMM), Diffusion Limited Aggregation (DLA), energy-based modeling and fractal representations. Here, a model-based 3D reconstruction of the bronchial tree is achieved in a fully-automated way. The tree segmentation is performed by applying a DLA-based propagation. The initialization results from the 3DMM procedure. Energy modeling and fractals are used to overcome the well- known cases of subdivision ambiguities and artifact generation related to such a complex topological structure. Therefore, the proposed method is robust with respect to anatomical variabilities. The 3D bronchial tree reconstruction is finally visualized by using a semi-transparent volume rendering technique which provides brochogram- like representations. The developed method was applied to a data set acquired within a clinical framework by using both double- and multiple- detector CT scanners (5 patients corresponding to 1500 axial slices, including both normal and strong pathological cases). Results thus obtained, compared with a previously-developed 2D/3D technique, show significant improvements and accuracy increase of the 3D reconstructions.

Large Airways at CT: Bronchiectasis, Asthma and COPD

Combining helical volumetric CT acquisition and thin-slice thickness during breath hold provides an accurate assessment of both focal and diffuse airway diseases. With multiple detector rows, compared to single slice helical CT, multislice CT can cover a greater volume during a simple breath hold, and with better longitudinal and in-plane spatial resolution and improved temporal resolution. The result in data set allows the generation of superior multiplanar and 3-dimensional images of the airways, including those obtained from techniques developed specifically for airway imaging, such as CT bronchography and virtual bronchoscopy. Improvement in image analysis techniques and the use of spirometric control of lung volume acquisition have made possible accurate and reproducible quantitative assessment of airway wall, lumen areas and lung density. This quantitative assessment of the airways will lead to the increasing use of CT as a research tool for better insights in physiopathology of obstructive lung disease, particularly in COPD and asthma, with an ultimate benefit in clinical practice.

Modeling, segmentation, and caliber estimation of bronchi in high-resolution computerized tomography

In this paper, we address bronchi segmentation in high resolution computerized tomography in order to estimate the bronchial caliber. The method developed is based on mathematical morphology theory, and relies on morphological filtering, marking techniques derived from the concept of connection cost, and conditional watershed. In order to evaluate the robustness of the segmentation and the accuracy of the caliber estimates, a realistic bronchi modeling based on physiological characteristics has been developed. According to the size of the bronchi, the accuracy is up to 90%. Results are presented and discussed.

Quantitative computed tomography imaging of airway remodeling in severe asthma

Asthma is a heterogeneous condition and approximately 5-10% of asthmatic subjects have severe disease associated with structure changes of the airways (airway remodeling) that may develop over time or shortly after onset of disease. Quantitative computed tomography (QCT) imaging of the tracheobronchial tree and lung parenchyma has improved during the last 10 years, and has enabled investigators to study the large airway architecture in detail and assess indirectly the small airway structure. In severe asthmatics, morphologic changes in large airways, quantitatively assessed using 2D-3D airway registration and recent algorithms, are characterized by airway wall thickening, luminal narrowing and bronchial stenoses. Extent of expiratory gas trapping, quantitatively assessed using lung densitometry, may be used to assess indirectly small airway remodeling. Investigators have used these quantitative imaging techniques in order to attempt severity grading of asthma, and to identify clusters of asthmatic patients that differ in morphologic and functional characteristics. Although standardization of image analysis procedures needs to be improved, the identification of remodeling pattern in various phenotypes of severe asthma and the ability to relate airway structures to important clinical outcomes should help target treatment more effectively.