Automated Assessment of Aortic and Main Pulmonary Arterial Diameters using Model-Based Blood Vessel Segmentation for Predicting Chronic Thromboembolic Pulmonary Hypertension in Low-Dose CT Lung Screening

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by obstruction of the pulmonary vasculature by residual organized thrombi. A morphological abnormality inside mediastinum of CTEPH patient is enlargement of pulmonary artery. This paper presents an automated assessment of aortic and main pulmonary arterial diameters for predicting CTEPH in low-dose CT lung screening. The distinctive feature of our method is to segment aorta and main pulmonary artery using both of prior probability and vascular direction which were estimated from mediastinal vascular region using principal curvatures of four-dimensional hyper surface. The method was applied to two datasets, 64 low-dose CT scans of lung cancer screening and 19 normal-dose CT scans of CTEPH patients through the training phase with 121 low-dose CT scans. This paper demonstrates effectiveness of our method for predicting CTEPH in low-dose CT screening

Association analysis of SNPs with CT image-based phenotype of emphysema progression in heavy smokers

Chronic obstructive pulmonary disease (COPD) is predicted to become the third leading cause of death worldwide by 2030. Smoking is a well-known risk factor in the development of COPD. Association between COPD genes and smoking have been studied. This paper presents an association analysis of single nucleotide polymorphisms (SNPs) with a CT image-based phenotype of emphysema progression in heavy smokers. The emphysema progression was quantitatively represented by the annual increment of low attenuation volume (LAV) on CT scans for five years. 10 candidate SNPs were selected from 316 SNPs in 125 papers of genetic studies of COPD and lung cancer. The genotypes were determined by real-time polymerase chain reaction (PCR) using deoxyribonucleic acid (DNA) extracted from saliva samples. The association analysis was performed by Fisher's exact test and logistic regression analysis. This method was applied to a dataset with 144 participants (71 smokers, 61 past smokers, and 12 non-smokers). The results showed that the genotypes of rs3923564 and rs13180 SNPs were candidate SNPs associated with the CT image based-emphysema progression

Segmentation of aorta and main pulmonary artery of non-contrast CT images using U-Net for chronic thromboembolic pulmonary hypertension : evaluation of robustness to contacts with blood vessels

Enlargement of the pulmonary artery is a morphological abnormality of pulmonary hypertension patients. Diameters of the aorta and main pulmonary artery (MPA) are useful for predicting the presence of pulmonary hypertension. A major problem in the automatic segmentation of the aorta and MPA from non-contrast CT images is the invisible boundary caused by contact with blood vessels. In this study, we applied U-Net to the segmentation of the aorta and MPA from non-contrast CT images for normal and chronic thromboembolic pulmonary hypertension (CTEPH) cases and evaluated the robustness to the contacts between blood vessels. Our approach of the segmentation consists of three steps: (1) detection of trachea branch point, (2) cropping region of interest centered to the trachea branch point, and (3) segmentation of the aorta and MPA using U-Net. The segmentation performances were compared in seven methods: 2D U-Net, 2D U-Net with pre-trained VGG-16 encoder, 2D U-Net with pre-trained VGG-19 encoder, 2D Attention U-Net, 3D U-Net, an ensemble method of them, and our conventional method. The aorta and MPA segmentation methods using these U-Net achieved higher performance than a conventional method. Although the contact boundaries of blood vessels caused lower performance compared with the non-contact boundaries, the mean boundary distances were below about one pixel

Focal Spot, Spring 2000

https://digitalcommons.wustl.edu/focal_spot_archives/1084/thumbnail.jp

Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

Focal Spot, Summer 2003

https://digitalcommons.wustl.edu/focal_spot_archives/1094/thumbnail.jp

Focal Spot, Fall/Winter 1993

https://digitalcommons.wustl.edu/focal_spot_archives/1065/thumbnail.jp