Detection of Cerebrovascular Disease with Mobile Application (Preprint)
BACKGROUND The prevalence of cerebrovascular disease has gradually increased to become the second leading cause of death in the world. Magnetic resonance angiography (MRA) evaluates the intracranial vessels without requiring invasive procedures. OBJECTIVE This study provides a novel anatomy cerebrovascular disease detection platform for mobile devices with Android systems that could be applied in the treatment of cerebrovascular disease, medical prevention, and health care. METHODS The system proposed herein can transfer information of a text, DICOM images, and the 3D cerebrovascular model from the server to the client. The platform design structure can be divided into five layers. The platform server was based on an event-driven mechanism and used an HTTP protocol to achieve faster and more effective data transmission. In addition, the client used a Model View Controller(MVC) model for platform development. RESULTS This study investigated the reliability and effectiveness of the platform and examined user-related questions. Forty students who represented common users and 21 doctors who represented professional users participated in the experiment. The results indicated that both common and professional users were satisfied with the platform usage. CONCLUSIONS The experimental results implied that the platform could be a useful tool for detecting cerebrovascular disease and that it could be integrated into existing diagnosis methods and treatments. Furthermore, the platform could be extended to the detection of other diseases such as respiratory and cardiovascular diseases. CLINICALTRIAL ChiCTR-OCH-12002508