SBIR Phase II: An AI-Enhanced Angiographic System to Guide Endovascular Treatment of Intracranial Aneurysms

SBIR II 期：人工智能增强血管造影系统指导颅内动脉瘤的血管内治疗

• 批准号: 2304388
• 负责人: Mohammad Mahdi Shiraz Bhurwani
• 金额: $ 99.99万
• 依托单位: QAS.AI INC
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2304388&HistoricalAwards=false
• 关键词: SBIR; Phase; II; AI; Enhanced

The broader impact of this Small Business Innovation Research (SBIR) Phase II project is improving the surgical outcome for patients undergoing neuro-endovascular interventions for the treatment of intracranial aneurysms (IAs). IAs affect 6% of the population and IA rupture results in lethal hemorrhagic strokes, which account for ~25% of cerebrovascular deaths despite improvements in management. Most ruptured IA patients (~65%) die due to the initial bleed or its immediate complications. Of the survivors, ~50% are left disabled and dependent on others for daily activities. When IAs become symptomatic and medical therapy or lifestyle changes are ineffective, treatment could involve neuro-endovascular interventions. Although these surgical approaches provide reliable and fast access to the lesion with fewer complications than open skull surgery, they do not achieve complete IA healing, with as many as 30% of the cases requiring repeated interventions. The artificial intelligence technology developed in this project will allow real-time assessment of the surgery progress by analyzing images acquired through the angiographic unit. The solution will provide the odds of failure to achieve healing of the IAs before the patient leaves the surgical suite.This Small Business Innovation Research (SBIR) Phase II project will support development of the world’s first artificial intelligence platform that enables real-time informed decision support for image-guided neuro interventions to treat intracranial aneurysms. The technology uses imaging biomarkers extracted from routinely acquired angiograms during image-guided endovascular procedures and machine learning methods to account for large heterogeneity in patient pathology, neuro-interventionalist approach, and imaging equipment characteristics. The platform includes multiple innovative aspects: 1) a fully automated method to identify the location and extent of the IA, (2) instantaneous extraction of the imaging biomarkers, (3) prognosis of the surgical outcome at one-year post-procedure in a fraction of a second to allow neuro-interventionalist to readjust the endovascular therapy, and (4) full integration with the angiographic systems regardless of the manufacturer.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.

该小企业创新研究 (SBIR) II 期项目的更广泛影响是改善接受神经血管内介入治疗颅内动脉瘤 (IA) 的患者的手术结果，影响 6% 的人口，而 IA 破裂会导致致命。尽管治疗有所改善，但出血性中风仍占脑血管死亡的约 25%，大多数 IA 破裂患者 (约 65%) 因初次出血或立即出血而死亡。当 IAs 出现症状并且药物治疗或生活方式改变无效时，约 50% 的幸存者会出现残疾，但可以进行神​​经血管内干预治疗，尽管这些手术方法可以提供可靠且快速的治疗方法。对于比开颅手术并发症更少的病灶，他们无法实现IA完全愈合，多达30%的病例需要重复干预，该项目开发的人工智能技术将允许实时评估手术进展。通过分析通过血管造影获得的图像该解决方案将在患者离开手术室之前提供 IAs 愈合失败的可能性。这个小型企业创新研究 (SBIR) 第二阶段项目将支持开发世界上第一个支持实时的人工智能平台。该技术使用在图像引导血管内手术期间从常规采集的血管造影中提取的成像生物标志物和机器学习方法来解释患者病理学的巨大异质性，为治疗颅内动脉瘤的图像引导神经干预提供明智的决策支持。该平台包括多个创新方面：1）识别 IA 位置和范围的全自动方法，（2）即时提取成像生物标志物，（3）手术预后。术后一年的结果只需几分之一秒，即可让神经介入医生重新调整血管内治疗，以及 (4) 与血管造影系统完全集成，无论制造商如何。该奖项反映了 NSF 的法定使命通过使用基金会的智力优点和更广泛的影响审查标准进行评估，并被认为值得支持。