Healthy Lung Vessel Morphology Derived From Thoracic Computed Tomography

Knowledge of the lung vessel morphology in healthy subjects is necessary to improve our understanding about the functional network of the lung and to recognize pathologic deviations beyond the normal inter-subject variation. Established values of normal lung morphology have been derived from necropsy material of only very few subjects. In order to determine morphologic readouts from a large number of healthy subjects, computed tomography pulmonary angiography (CTPA) datasets, negative for pulmonary embolism, and other thoracic pathologies, were analyzed using a fully-automatic, in-house developed artery/vein separation algorithm. The number, volume, and tortuosity of the vessels in a diameter range between 2 and 10mm were determined. Visual inspection of all datasets was used to exclude subjects with poor image quality or inadequate artery/vein separation from the analysis. Validation of the algorithm was performed manually by a radiologist on randomly selected subjects. In 123 subjects (men/women: 55/68), aged 59 +/- 17 years, the median overlap between visual inspection and fully-automatic segmentation was 94.6% (69.2-99.9%). The median number of vessel segments in the ranges of 8-10, 6-8, 4-6, and 2-4 mm diameter was 9, 34, 134, and 797, respectively. Number of vessel segments divided by the subject's lung volume was 206 vessels/L with arteries and veins contributing almost equally. In women this vessel density was about 15% higher than in men. Median arterial and venous volumes were 1.52 and 1.54% of the lung volume, respectively. Tortuosity was best described with the sum-of-angles metric and was 142.1 rad/m (138.3-144.5 rad/m). In conclusion, our fully-automatic artery/vein separation algorithm provided reliable measures of pulmonary arteries and veins with respect to age and gender. There was a large variation between subjects in all readouts. No relevant dependence on age, gender, or vessel type was observed. These data may provide reference values for morphometric analysis of lung vessels

Quantitative and semi-quantitative computed tomography analysis of interstitial lung disease associated with systemic sclerosis: A longitudinal evaluation of pulmonary parenchyma and vessels

Objectives To evaluate interstitial lung disease associated with systemic sclerosis (SSc-ILD) and its changes during treatment by using quantitative analysis (QA) compared to semi-quantitative analysis (semiQA) of chest computed tomography (CT) scans. To assess the prognostic value of QA in predicting functional changes. Materials and methods We retrospectively selected 35 consecutive patients with SSc-ILD with complete pulmonary functional evaluation, Doppler-echocardiography, immunological tests, and chest CT scan at both baseline and follow-up after immunosuppressive therapy. CT images were analyzed by two chest radiologists for semiQA and by a computational platform for texture analysis of ILD patterns (CALIPER) for QA. Concordance between semiQA and QA was tested. Traction bronchiectasis severity was scored. Analysis of ROC curves was performed. Results Seventy CT scans were analyzed and QA failed in 4/70 scans. Thus, the final population included 31/35 patients (51.3\ub112.1 years). QA had a weak-to-good concordance with semiQA (ICC reticular:0.275; ICC ground-glass:0.667) and QA correlated better than semiQA (r = -0.3 to -0.74 vs r = -0.3 to -0.4) with functional parameters. Both methods correlated with traction bronchiectases score and pulmonary artery diameter at CT. A pulmonary artery diameter 29mm distinguished patients with lower lung volumes and ILD extent greater than 39% (p<0.001). Changes in QA patterns during treatment were not accurate (AUC: 0.50 to 0.70; p>0.05) in predicting disease progression as assessed by functional parameters, whereas variation in total lung volume at QA accurately predicted changes in the composite functional respiratory endpoint with FVC% and DLco% (AUC = 0.74; 95%CI: 0.54 to 0.93; p = 0.03). Conclusions Pulmonary QA of CT images can objectively quantify specific patterns of ILD changes during treatment in patients with SSc-ILD. Changes in QA patterns do not correlate with functional changes, but variation in total lung volume at QA accurately predicted changes in the composite functional respiratory endpoint with FVC% and DLco%. Pulmonary artery diameter at CT reflects the interstitial involvement, identifying patients with more severe prognosis

3D Imaging for Planning of Minimally Invasive Surgical Procedures

Novel minimally invasive surgeries are used for treating cardiovascular diseases and are performed under 2D fluoroscopic guidance with a C-arm system. 3D multidetector row computed tomography (MDCT) images are routinely used for preprocedural planning and postprocedural follow-up. For preprocedural planning, the ability to integrate the MDCT with fluoroscopic images for intraprocedural guidance is of clinical interest. Registration may be facilitated by rotating the C-arm to acquire 3D C-arm CT images. This dissertation describes the development of optimal scan and contrast parameters for C-arm CT in 6 swine. A 5-s ungated C-arm CT acquisition during rapid ventricular pacing with aortic root injection using minimal contrast (36 mL), producing high attenuation (1226), few artifacts (2.0), and measurements similar to those from MDCT (p\u3e0.05) was determined optimal. 3D MDCT and C-arm CT images were registered to overlay the aortic structures from MDCT onto fluoroscopic images for guidance in placing the prosthesis. This work also describes the development of a methodology to develop power equation (R2\u3e0.998) for estimating dose with C-arm CT based on applied tube voltage. Application in 10 patients yielded 5.48┬▒177 2.02 mGy indicating minimal radiation burden. For postprocedural follow-up, combinations of non-contrast, arterial, venous single energy CT (SECT) scans are used to monitor patients at multiple time intervals resulting in high cumulative radiation dose. Employing a single dual-energy CT (DECT) scan to replace two SECT scans can reduce dose. This work focuses on evaluating the feasibility of DECT imaging in the arterial phase. The replacement of non-contrast and arterial SECT acquisitions with one arterial DECT acquisition in 30 patients allowed generation of virtual non-contrast (VNC) images with 31 dose savings. Aortic luminal attenuation in VNC (32┬▒177 2 HU) was similar to true non-contrast images (35┬▒177 4 HU) indicating presence of unattenuated blood. To improve discrimination between c

3D Imaging for Planning of Minimally Invasive Surgical Procedures

Novel minimally invasive surgeries are used for treating cardiovascular diseases and are performed under 2D fluoroscopic guidance with a C-arm system. 3D multidetector row computed tomography (MDCT) images are routinely used for preprocedural planning and postprocedural follow-up. For preprocedural planning, the ability to integrate the MDCT with fluoroscopic images for intraprocedural guidance is of clinical interest. Registration may be facilitated by rotating the C-arm to acquire 3D C-arm CT images. This dissertation describes the development of optimal scan and contrast parameters for C-arm CT in 6 swine. A 5-s ungated C-arm CT acquisition during rapid ventricular pacing with aortic root injection using minimal contrast (36 mL), producing high attenuation (1226), few artifacts (2.0), and measurements similar to those from MDCT (p\u3e0.05) was determined optimal. 3D MDCT and C-arm CT images were registered to overlay the aortic structures from MDCT onto fluoroscopic images for guidance in placing the prosthesis. This work also describes the development of a methodology to develop power equation (R2\u3e0.998) for estimating dose with C-arm CT based on applied tube voltage. Application in 10 patients yielded 5.48┬▒177 2.02 mGy indicating minimal radiation burden. For postprocedural follow-up, combinations of non-contrast, arterial, venous single energy CT (SECT) scans are used to monitor patients at multiple time intervals resulting in high cumulative radiation dose. Employing a single dual-energy CT (DECT) scan to replace two SECT scans can reduce dose. This work focuses on evaluating the feasibility of DECT imaging in the arterial phase. The replacement of non-contrast and arterial SECT acquisitions with one arterial DECT acquisition in 30 patients allowed generation of virtual non-contrast (VNC) images with 31 dose savings. Aortic luminal attenuation in VNC (32┬▒177 2 HU) was similar to true non-contrast images (35┬▒177 4 HU) indicating presence of unattenuated blood. To improve discrimination between c

Enhanced Ultrasound Visualization for Procedure Guidance

Intra-cardiac procedures often involve fast-moving anatomic structures with large spatial extent and high geometrical complexity. Real-time visualization of the moving structures and instrument-tissue contact is crucial to the success of these procedures. Real-time 3D ultrasound is a promising modality for procedure guidance as it offers improved spatial orientation information relative to 2D ultrasound. Imaging rates at 30 fps enable good visualization of instrument-tissue interactions, far faster than the volumetric imaging alternatives (MR/CT). Unlike fluoroscopy, 3D ultrasound also allows better contrast of soft tissues, and avoids the use of ionizing radiation.Engineering and Applied Science

A comparative evaluation for liver segmentation from spir images and a novel level set method using signed pressure force function

Thesis (Doctoral)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2013Includes bibliographical references (leaves: 118-135)Text in English; Abstract: Turkish and Englishxv, 145 leavesDeveloping a robust method for liver segmentation from magnetic resonance images is a challenging task due to similar intensity values between adjacent organs, geometrically complex liver structure and injection of contrast media, which causes all tissues to have different gray level values. Several artifacts of pulsation and motion, and partial volume effects also increase difficulties for automatic liver segmentation from magnetic resonance images. In this thesis, we present an overview about liver segmentation methods in magnetic resonance images and show comparative results of seven different liver segmentation approaches chosen from deterministic (K-means based), probabilistic (Gaussian model based), supervised neural network (multilayer perceptron based) and deformable model based (level set) segmentation methods. The results of qualitative and quantitative analysis using sensitivity, specificity and accuracy metrics show that the multilayer perceptron based approach and a level set based approach which uses a distance regularization term and signed pressure force function are reasonable methods for liver segmentation from spectral pre-saturation inversion recovery images. However, the multilayer perceptron based segmentation method requires a higher computational cost. The distance regularization term based automatic level set method is very sensitive to chosen variance of Gaussian function. Our proposed level set based method that uses a novel signed pressure force function, which can control the direction and velocity of the evolving active contour, is faster and solves several problems of other applied methods such as sensitivity to initial contour or variance parameter of the Gaussian kernel in edge stopping functions without using any regularization term