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

项目概要 脑动脉瘤破裂引起的出血是一种毁灭性的疾病，死亡率很高。对于超过 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，并且越来越依赖血管内技术。然而，治疗的持久性尚不清楚 复发率估计为 16-40%，再治疗率为 10-20%。目前确保动脉瘤的金标准 闭塞术是基于导管的数字减影血管造影（DSA），一种侵入性方法，具有显着的副作用 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，选择他们进行进一步检查。开发此 技术是医疗创新公司 (MIC) 和 UTHealth 合作的成果 和赫尔曼纪念医院 (UTH/MHH)。我们计划检验动脉瘤复发可以 使用标准颅骨 X 射线检测。在目标 1 中，我们将开发一种自动化计算机算法 检测弹簧圈栓塞后动脉瘤的复发情况。数据来自在 UTH/MHH 接受治疗的既定患者队列。 X 射线的自动计算机分析（初始治疗和 6 个月随访）将预测动脉瘤 使用线圈形态测量（大小、形状、方向）进行复发。该算法将通过与 随访金标准 (DSA)。在目标 2 中，算法性能的初步验证将在 新颖的数据集。使用与训练相同的方案治疗的类似患者的验证数据集 (n=150) 数据集将使用自动算法进行处理。将评估算法的性能 使用接收者操作员特征来确定最佳灵敏度/特异性。如果成功的话，这样的 该方法可以对患者进行风险分层，并确定哪些患者应该接受血管造影。减少利用率 血管造影术将显着减少并发症和医疗费用，为公众带来巨大利益。这 第一阶段 STTR 拨款将允许在第二阶段应用和更广泛的应用之前进行算法开发和测试 临床试验。 MIC 和 UTH/MHH 之间的合作结合了医疗商业化的经验 临床神经外科软件。 机密- UHEALTH

项目成果

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

颅骨 X 射线在识别盘绕脑动脉瘤复发中的效用。

• 发表时间: 2021-06
• 作者: Chen, Peng Roc;Lopez;Conner, Christopher R;Sanzgiri, Aditya;Sheth, Sunil A;Erkmen, Kadir;Kim, Dong H;Day, Arthur L
• 通讯作者: Day, Arthur L