Additive Micro/Nano-manufacturing of Structured Piezoelectric Active Materials for Intelligent Stent Monitoring

用于智能支架监测的结构化压电活性材料的增材微/纳米制造

• 批准号: EP/Y003551/1
• 负责人: Ying-Lung HO
• 金额: $ 16.43万
• 依托单位: Northumbria University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY003551%2F1
• 关键词: Additive; Micro; Nano; manufacturing; Structured

Cardiovascular diseases, associated with stroke, heart failure, and end-stage renal disease, caused more than 30% of deaths worldwide. As of 2020, 19 million estimated deaths globally are attributed to cardiovascular diseases, which is an increase of 18.7% to that of 2010. Atherosclerosis is the common pathology that leads to this considerable amount of deaths. To treat atherosclerosis, the most common treatment is stenting, where its clinical efficacy resulted into millions of it implanted every year. A problem in this treatment however is the occurrence of restenosis, or the re-narrowing of the blood vessel due to adverse reaction of the body to the stent material. Methods to diagnose this condition however are invasive, have limited clinical outcomes and are done only when the patient is already feeling the symptoms. In addition, some of the implantable devices that diagnose this condition have limited battery-life and require even more surgeries for replacements. By integrating sensors with the stents (smart stents) early symptoms of restenosis can be detected by monitoring the blood fluid dynamics in the implanted area. Our study aims to create a smart stent making use of a new type of stretchable piezoelectric active sensor and radio frequency identification (RFID) technology in combination with artificial intelligence (AI)-based data processing and analytics.

与中风、心力衰竭和终末期肾病相关的心血管疾病导致全球30%以上的死亡。截至2020年，全球估计有1900万人死于心血管疾病，比2010年增加了18.7%。动脉粥样硬化是导致大量死亡的常见病理学。为了治疗动脉粥样硬化，最常见的治疗方法是支架植入术，其临床疗效导致每年植入数百万个支架。然而，这种治疗中的问题是由于身体对支架材料的不良反应而发生再狭窄或血管再狭窄。然而，诊断这种疾病的方法是侵入性的，临床结果有限，并且只有当患者已经感觉到症状时才进行。此外，一些诊断这种情况的植入式设备电池寿命有限，需要更多的手术来更换。通过将传感器与支架（智能支架）集成，可以通过监测植入区域的血液流体动力学来检测再狭窄的早期症状。我们的研究旨在创建一种智能支架，利用新型可拉伸压电有源传感器和射频识别（RFID）技术，结合基于人工智能（AI）的数据处理和分析。