Non-invasive Detection of Cerebral Aneurysm Recurrence after Endovascular Treatment Using Automated Image Processing

使用自动图像处理无创检测血管内治疗后脑动脉瘤复发

• 批准号: 9907673
• 负责人: Peng Roc Chen
• 金额: $ 22.5万
• 依托单位: MEDICAL INNOVATORS COMPANY, LLC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9907673
• 关键词: Adopted; Algorithms; Aneurysm; Angiography; Anterior; Blinded; Businesses; Catheters; Cerebral Aneurysm; Cerebral hemisphere hemorrhage; Clinical; Clinical Trials; Collaborations; Comb animal structure; Computational algorithm; Computer Analysis; Computer software; Consensus; Data; Data Set; Detection; Development; Diagnosis; Digital Subtraction Angiography; Ensure; Goals; Gold; Grant; Hematoma; Hemorrhage; Hospitals; Human; Human Resources; Imaging technology; Intracranial Aneurysm; Investigation; Lateral; Leadership; Manuals; Measures; Medical; Medical Care Costs; Medical Imaging; Methods; Monitor; Morphologic artifacts; Morphology; Non-Invasive Cancer Detection; Operative Surgical Procedures; Patients; Performance; Phase; Process; Protocols documentation; Radiation Dose Unit; Receiver Operating Characteristics; Recurrence; Reproducibility; Retreatment; Risk; Roentgen Rays; Rupture; Ruptured Aneurysm; Screening procedure; Sensitivity and Specificity; Shapes; Small Business Technology Transfer Research; Supervision; Techniques; Testing; Therapeutic Embolization; Time; Training; Validation; Visual; algorithm development; automated algorithm; automated analysis; base; clinical application; clinical practice; clinical risk; clinically significant; cohort; cost; cranium; embolic stroke; experience; follow-up; image processing; imaging software; imaging study; innovation; metallicity; morphometry; mortality; neurosurgery; non-invasive imaging; novel; novel strategies; patient screening; patient subsets; prevent; screening; side effect; skills; technique development; vascular injury

PROJECT SUMMARY Hemorrhage due to cerebral aneurysm rupture is a devastating condition with high mortality. For the more than 30,000 patients in the US who are diagnosed annually with an aneurysm, treatment consists of preventing rupture, and increasingly relies of endovascular techniques. However, treatment durability is unknown with recurrence estimated at 16-40% and the re-treatment of 10-20%. The current gold standard to ensure aneurysm obliteration is catheter-based digital subtraction angiography (DSA), an invasive method with significant side effects. Here, we propose an alternative that uses simple skull x-rays and automated image processing to identify patients who are high likelihood of recurrence and select them for further investigation. Development of this technique is the result of a collaboration between the Medical Innovations Company (MIC) and the UTHealth and Memorial Hermann Hospital (UTH/MHH). We plan to test the hypothesis that aneurysm recurrence can be detected using standard skull x-rays. In Aim 1, we will develop an automated computer algorithm that detects aneurysm recurrence after coiling. Data from an established cohort of patients treated at UTH/MHH. Automated computer analysis of the x-rays (at initial treatment and 6-month follow) will predict aneurysm recurrence using coil morphometry (size, shape, orientation). The algorithm will be trained by comparing it to the gold standard for follow up (DSA). In Aim 2, preliminary validation of algorithm performance will be tested in a novel dataset. A validation dataset (n=150) of similar patients treated with the same protocol as the training dataset will be processed using the automated algorithm. The performance of the algorithm will be assessed using receiver operator characteristics to determine optimal sensitivity/specificity. If successful, such an approach could stratify risk in patients and determine which should undergo angiography. Reducing utilization of angiography will significantly reduce complications and medical cost at an immense benefit to the public. This Phase I STTR grant will allow for algorithm development and testing prior to a Phase II application and broader clinical trials. The partnership between MIC and UTH/MHH combines experience commercializing medical software with clinical neurosurgery. CONFIDENTIAL- UTHEALTH

项目摘要 脑动脉瘤破裂出血是一种毁灭性的疾病，死亡率很高。为超过 美国每年有30，000名患者被诊断患有动脉瘤，治疗包括预防 破裂，并且越来越依赖于血管内技术。然而，治疗持久性是未知的， 估计复发率为16-40%，再治疗率为10- 20%。目前确保动脉瘤的黄金标准 闭塞是基于导管的数字减影血管造影术（DSA），这是一种有创方法， 方面的影响.在这里，我们提出了一种替代方案，使用简单的头骨x射线和自动图像处理来识别 复发可能性高的患者，并选择他们进行进一步研究。发展这一 这项技术是医疗创新公司（MIC）和UTHealth合作的结果。 纪念赫尔曼医院（UTH/MHH）我们计划检验动脉瘤复发可能 可以用标准的颅骨X光检测到在目标1中，我们将开发一种自动计算机算法， 检测弹簧圈栓塞后动脉瘤复发。数据来自UTH/MHH治疗的既定患者队列。 自动计算机分析X线片（初始治疗和6个月随访）将预测动脉瘤 使用线圈形态测定法（大小、形状、方向）进行复发。该算法将通过将其与 随访金标准（DSA）。在目标2中，算法性能的初步验证将在 新数据集采用与训练相同的方案治疗的类似患者的验证数据集（n=150） 将使用自动算法处理数据集。将评估算法的性能 使用接收者操作者特征来确定最佳灵敏度/特异性。如果成功的话， 这种方法可以对患者的风险进行分层，并确定哪些患者应该接受血管造影术。降低利用率 将大大减少并发症和医疗费用，对公众有巨大的好处。这 第一阶段STTR赠款将允许在第二阶段应用之前进行算法开发和测试， 临床试验MIC和UTH/MHH之间的合作伙伴关系结合了医疗商业化的经验 临床神经外科软件。 机密- UTHEALTH

项目成果

Utility of skull X-rays in identifying recurrence of coiled cerebral aneurysms.

• DOI: 10.7461/jcen.2021.e2020.10.002
• 发表时间: 2021-06
• 期刊: Journal of cerebrovascular and endovascular neurosurgery
• 作者: Chen PR;Lopez-Rivera V;Conner CR;Sanzgiri A;Sheth SA;Erkmen K;Kim DH;Day AL
• 通讯作者: Day AL