| Summary: | 博士 === 國立陽明大學 === 生物醫學影像暨放射科學系 === 101 === Stroke is one of the leading causes of death worldwide. In Taiwan, stroke is the 3rd leading cause of death; second only to cancer and cardiovascular disease in recent years thus it pays a huge impact on people's health and medical/economical issues. As the population of Taiwan gradually aging, stroke prevention, treatment and rehabilitation issues are important. With the rapid development of imaging techniques, medical imaging provides an indispensable role not only in the diagnosis and decision making of acute stroke but also as an imaging marker to predict early stroke in evolution and even functional outcome.
Stroke is the rapid loss of brain function due to disturbance in the blood supply to the brain. This can be due to ischemia or infarction caused by blockage (thrombosis, arterial embolism), or a hemorrhage (ICH). Computed tomography (CT) and magnetic resonance imaging (MRI) provide accurate diagnosis of cerebral hemorrhage and assist in treatment decisions. However, there is no reliable way to assess the damage caused by a blood clot on the surrounding brain tissue. MRI is very sensitive to detect cerebral infarction; CT and MRI perfusion imaging can decide whether the patient should undergo thrombolytic therapy. In the past, medical imagings are limited to qualitative interpretations. With the rapid development of imaging techniques, we are able to speculate the physiological and pathological changes in the brain with advanced quantitative image analysis.
This thesis is divided into three parts. The first part we used the diffusion-weighted imaging (DWI) to analysis the perihematomal edematous tissue in patients with ICH. The injury to the perihematomal edema brain region can be reversible (vasogenic edema) or irreversible (cytotoxic edema) and should be treated with different methods. The results showed that ratio of irreversible damage is associated with patient age and blood hemoglobin as well as creatine concentrations, the higher ratio of irreversible damage and the amount of changes in the diffusion coefficient in the acute period could predict the functional outcome of patients. The second part we used resting state functional MRI (fMRI) analysis of brain network in patients with cerebral infarction. We found that some important brain networks, such as the default mode network and motor network reduce the functional connectivity after cerebral infarction. This decline of network connectivity is highly correlated with patient’s clinical performance. In the third part of the thesis, we analyzed the resting Blood Oxygen Level Dependent signal (BOLD). The amplitude of low-frequency fluctuation (ALFF) of the BOLD signal is able to detect the region of ischemic penumbra just as the perfusion-weighted imaging.
Based on the above results, we believe that the use of quantitative imaging methods, especially DWI and fMRI will provide us with more brain physiology and functional information to help stroke diagnosis and outcome prediction.
|
|---|
