Dynamic motion analysis of aorta : image processing methods for MDCT and Cine-MR image

Dept. of Biomedical Engineering/박사This dissertation was to study on image processing method for dynamic motion analysis of aorta using sequential images. The visualization of blood vessel motion and imaging protocols for cross-sectional aorta images are proposed.To accomplish assess the aorta motion, muti-steps image processing strategy was applied. First, the image pre-processing was applied to image enlargement and segmentation of aorta. Second, the intensity profile of aorta was used for wall boundary extraction. Third, semi-automatic extraction of target aorta boundary tracing over first frame is then automatically tracked throughout the image frames. The visualization of aorta motion in the sequential images provides a quantitative source of their motion in space. In order to visualize the blood vessel wall motion, velocity vector mapping was applied to the sequential images. It provided the information of aorta wall movement velocity and aortic displacement.To evaluate the proposed methods, clinical validation have been designed using MDCT and Cine-MR images.The aortic wall movement property, the movement profiles on aorta calcification, aortic displacement, and relations between wall movement and age were assessed using MDCT images. The number of subjects (14 men, 16 women; mean age, 55.9 ± 14.99 years; range, 31-80 years) were 30 and have valvular heart disease. The correlation between wall movement at three different position of thoracic aorta and entire study population group was -0.63 (p < 0.001), -0.51 (p < 0.05) and -0.45 (p < 0.05) respectively. The profiles of wall variation in aorta calcification indicate dyssynchoronous aorta expansion. The clusters which are include the calcification point showed low variation throughout the image samples.The aortic wall movement of Turner syndrome group were also assessed using Cine-MR images. The number of subjects (17 women; mean age, 21.6 ± 6.6 years; range, 11-38 years) were 17. The wall movement data of total subjects were presented as mean ± standard deviation. The movement of descending aorta at three different position were 0.79 ± 0.25, 0.59 ± 0.15 and 0.53 ± 0.15 respectively.There was a significant decrease of the aortic wall motion at all thoracic levels throughout the ages. Although specific assessment of vascular aging was not available for the diseased subjects, a potential distinction on the aorta aging at the different ages was possible.In contrast to the ascending aorta, the descending segments presented a significantly lesser magnitude of displacement and appear rather fixed at their thoracic position.The results of this dissertation provide the fundamental characteristics of blood vessel motion and could be used not only clinical researches also clinical applications, such as vascular aging, assessment of vascular disease, and early detection of vascular abnormalityope