Automated Imaging Differentiation of Parkinsonism

帕金森病的自动成像鉴别

• 批准号: 10613607
• 负责人: David E Vaillancourt
• 金额: $ 10.51万
• 依托单位: AUTOMATED IMAGING DIAGNOSTICS, LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10613607
• 关键词: Automated; Imaging; Differentiation; Parkinsonism

SUMMARY Across the globe the number of people diagnosed with Parkinsonism has increased considerably. From 1990 to 2015, the number of Parkinsonism diagnoses doubled, with over 6 million people currently carrying the diagnosis. Current estimates suggest that 12-14 million people will be diagnosed with Parkinsonism by 2040. Parkinson’s disease (PD), multiple system atrophy Parkinsonian variant (MSAp), and progressive supranuclear palsy (PSP), which are neurodegenerative forms of Parkinsonism, can be difficult to diagnose as they share motor and non-motor features and have an increased risk for dementia. Diagnostic accuracy in early PD (<5 years duration) is approximately 58%, and 54% of misdiagnosed patients have either MSA or PSP. While the FDA has approved dopamine transporter imaging with DaTscan™ to help identify Parkinsonism, abnormal DaTscan imaging cannot distinguish between Parkinsonism forms that share dopaminergic deficiency. Thus, no clinically approved current diagnostic marker can distinguish among forms of Parkinsonism. Correct diagnosis of Parkinsonism type is critical because the treatments, prognoses (often more rapid in atypical Parkinsonism), and pathologies of these diseases differ. Incorrect diagnoses result in patients receiving incorrect medications, deep brain stimulation surgeries performed in patients that do not have PD, diminished quality of life, and ineffective care. As outlined in our accepted Letter of Intent to the FDA Biomarker Qualification Program, a promising approach to identify different forms of Parkinsonism is diffusion magnetic resonance imaging (dMRI). Our software method is based on free-water imaging, which is a method for analyzing dMRI data of tissue microstructure associated with inflammation and neurodegeneration. We recently analyzed dMRI data from a retrospective multi-center cohort of 1002 participants collected with various acquisition protocols using 17 different MRI scanners across the world. Support vector machine (SVM) learning was conducted with an automated 5-fold cross-validation procedure in a training and validation cohort and then evaluated in an independent test cohort. In the independent test cohort, there was high area under the curve for distinguishing among PD, MSA, and PSP with AID-P across the MRI sites. Two key issues raised in the feedback from our FDA Biomarker Letter of Intent included 1) examination of AID- P at different levels of disease severity; and 2) examination of AID-P on one MRI scanner vendor versus combining across MRI scanner vendor. In this U01 project, we will be examining these two analytical issues to further enhance the rigor for our Final Qualification Plan. These key issues could have significant impact on model prediction accuracy and thus impact patient care.

概括 在全球范围内，被诊断出患有帕金森氏症的人的数量已谨慎增加。从1990年开始 到2015年，帕金森主义的诊断数量翻了一番，目前有超过600万人携带 诊断。目前的估计表明，到2040年，将被诊断出1,1-14万人被诊断出患有帕金森氏症。 帕金森氏病（PD），多系统萎缩帕金森氏症（MSAP）和进行性超级 帕金森氏症的神经退行性形式的麻痹（PSP）在共享时可能很难诊断 运动和非运动特征，痴呆症风险增加。早期PD的诊断准确性（<5 持续时间）约为58％，54％的诊断患者患有MSA或PSP。而 FDA已批准使用Datscan™的多巴胺转运蛋白成像，以帮助识别帕金森主义，异常 Datscan成像无法区分共享多巴胺能缺乏的帕金森主义形式。那， 没有临床认可的当前诊断标记可以区分帕金森主义形式。正确的 帕金森氏症类型的诊断至关重要，因为治疗，预后（通常在非典型上更快） 帕金森氏症）和这些疾病的病理不同。诊断不正确导致患者接受不正确 药物，不具有PD的患者进行的深脑刺激手术，质量降低 生活和无效的护理。 正如我们接受的意向书中概述了FDA生物标志物资格计划，这是一种有前途的方法 识别不同形式的帕金森氏症是磁共振成像（DMRI）的差异。我们的软件方法 基于自由水成像，这是一种分析组织微结构DMRI数据的方法 带有炎症和神经变性。我们最近分析了回顾性多中心的DMRI数据 使用17种不同的MRI扫描仪收集的1002名参与者的队列 世界。通过自动5倍交叉验证进行支持向量机（SVM）学习 培训和验证队列中的程序，然后在独立的测试队列中进行评估。在 独立的测试队列，曲线下方有高面积，可以区分PD，MSA和PSP 跨MRI站点的AID-P。 我们的FDA生物标志物意向书的反馈中提出的两个关键问题包括1）辅助检查 - p处于不同水平的疾病严重程度； 2）检查一个MRI扫描仪供应商对AID-P的检查 合并MRI扫描仪供应商。在这个U01项目中，我们将研究这两个分析问题 进一步增强了我们最终资格计划的严谨性。这些关键问题可能会对 建模预测准确性，从而影响患者护理。