I-Corps: Augmenting perfusion imaging for better stroke assessment
I-Corps: Augmenting perfusion imaging for better stroke assessment
批准号:
2030181
负责人:
Kaveh Laksari
金额:
$5.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-08-01 至 2023-07-31
中文摘要
这个I-Corps项目的更广泛的影响/商业潜力是开发一种技术,可以大大减少缺血性卒中的诊断时间。作为世界上最严重和最普遍的神经系统疾病之一,中风影响了很大一部分人口,并使医疗保健系统花费数十亿美元。 在通常与卒中管理相关的“黄金时间”内,诊断时间至关重要。使用比目前的灌注扫描计算机断层扫描(CT)机器更便宜的设备提供快速诊断的能力可能会增加在较不富裕地区正确诊断和快速治疗中风的患者数量。直接的好处是,由于治疗速度更快,死亡率和中风后残疾率降低,治疗的可及性增加,成本显着降低。尽管关注缺血性中风,但该方法可应用于与脑血流动力学系统相关的各种神经系统疾病,如脑血管意外、创伤性脑损伤(TBI)和脑肿瘤。该I-Corps项目基于一种医疗设备的开发,该设备使用医学图像处理、传感器测量、计算建模和机器学习来复制定量脑血流量的CT灌注图像,这是卒中严重程度评估和患者管理中最重要的指标。这种新颖的硬件/软件系统还提供了用于中风严重程度和风险评估的实时非侵入性患者特异性估计,沿着用于区分梗塞组织与可挽救的半影区的预测性测量。作为对现有CT扫描的增强,该技术满足了全球需求,特别是缺乏灌注成像设备的小型社区医院和中风中心的需求。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The broader impact/commercial potential of this I-Corps project is the development of a technology that may dramatically reduce the time-to-diagnosis of ischemic stroke. As one of the world’s most consequential and prevalent neurological diseases, stroke affects a large portion of the population and costs the healthcare system billions of dollars. The time-to-diagnosis is critical within the “golden hour” normally associated with stroke management. The ability to provide a rapid diagnosis with equipment less costly than currently perfusion-scan computed tomography (CT) machines may increase the number of patients in less affluent locations who are correctly diagnosed and rapidly treated for a stroke. The immediate benefits are reduction in the rate of mortality and post-stroke disabilities due to faster treatment, as well as an increase in the accessibility of treatment, and a significant decrease in costs. Despite the focus on ischemic strokes, this method may have applications on a variety of neurological diseases related to the brain’s hemodynamic systems, such as cerebrovascular accident, traumatic brain injury (TBI), and brain tumors. This I-Corps project is based on the development of a medical device that uses medical image processing, sensor measurements, computational modeling, and machine learning to replicate CT perfusion images quantifying cerebral blood flow, which is the most significant metric in stroke severity assessment and patient management. This novel hardware/software system also provides real-time non-invasive patient-specific estimates for stroke severity and risk assessment, along with predictive measures for differentiating infarct tissue from salvageable penumbra. The proposed technology, as an enhancement to existing CT scans, addresses the global demand, especially from small community hospitals and stroke centers that lack perfusion imaging devices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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