Year: 2004
Type: dissertation
Abstract: With ever-shortening acquisition times and electrocardiographic (ECG) gating, magnetic resonance imaging (MRI) applications have been extended to the examination of organ function.In cine cardiac MRI, heart motion can be frozen at certain phases in the cardiac cycle to obtain information on the morphology as well as functioning of the heart.Consecutive images can then be viewed dynamically to depict motion.MRI allows direct measurement of flow with an appropriate MR velocity-sensitive pulse sequence.The segmented spoiled gradient echo sequences, which acquire several k-space lines in each cardiac phase, provide high-resolution dynamic images in a single breath-hold, thus avoiding respiratory artifacts.The purpose of the present study is to investigate the accuracy of conventional and breath-hold cine phase-contrast-interleaved imaging sequences with phantom measurements and apply the technique to study 3-D flow profiles at the left ventricular outflow tract during systole and at the mitral annulus during diastole.Conventional velocity-mapping sequences were also applied to assess the flow-wave velocity (FWV) in the aorta.FWV was chosen as an index of aortic stiffness.The aim was to assess the reduction in aortic stiffness with antihypertensive treatment.Nonvelocity-sensitive cine MRI was applied to develop and validate a method for studies of human atrial and right ventricular volumes and function.Nonvelocity-sensitive MRI was used to evaluate right atrial volumes (casts) using a spin-echo (SE) sequence and right ventricle (cast) using a gradient echo (GRE) sequence (FLASH).The aim of the right ventricular study was to identify the optimal imaging plane for the right ventricle.The right and left atrial volume cycles in healthy subjects was determined, using a GRE cine sequence (FISP).
Source: Työväentutkimus Vuosikirja
Author: Veli-Pekka Poutanen
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2188373661