Prediction of Stroke Outcome from Early MRI Data using an Adaptive Neural Network

使用自适应神经网络根据早期 MRI 数据预测中风结果

• 批准号: 7626823
• 负责人: JAMES R EWING
• 金额: $ 7.25万
• 依托单位: HENRY FORD HEALTH SYSTEM
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7626823
• 关键词: Acute; Animal Model; Antiplatelet Drugs; Biological Neural Networks; Blinded; Blood Platelets; Boxing; Brain; Cause of Death; Characteristics; Chronic; Classification Scheme; Clinical; Data; Data Analyses; Data Set; Databases; Descriptor; Diffusion weighted imaging; Gray unit of radiation dose; Hour; Human; Image; Infarction; Investigation; Lesion; Magnetic Resonance Imaging; Measures; Methodology; Outcome; Outcome Measure; Output; Patients; Pharmaceutical Preparations; Program Research Project Grants; Protons; Research; Staging; Stroke; Techniques; Therapeutic Intervention; Time; Tissue Viability; Tissues; Training; United States; Upper arm; Weight; Weights and Measures; abciximab; density; disability; improved; open label; public health relevance; treatment effect; vector

DESCRIPTION (provided by applicant): We have previously used combined MRI image sets and iterative self-organizing data analysis (ISODATA), to obtain a time-independent prediction of eventual lesion volume in animal models of stroke and in humans. Recently, we have refined and improved this approach by introducing an adaptive neural network (ANN) as a predictor of the T2-weighted image at 3 months, thus providing an essentially continuous descriptor of tissue outcome, rather than the much coarser classification scheme produced in ISODATA. In this R03 application, we propose to apply this methodology to the reanalysis of an existing data set of human studies obtained over a period of ten years by the human arm of a stroke program project grant, and thereby provide an early and robust predictor of outcome in stroke. An external stroke data base will be used as an independent validating set. Finally, an examination of MRI changes in an open-label trial, and in a blinded trial, of the anti-platelet drug abciximab will be conducted. This latter examination will allow the description of the operating characteristics of the ANN predictor (i.e., its connection to clinical measures) to be refined. If this effort is successful, we will produce a surrogate MRI outcome measure that will be quickly available (essentially in real time) to predict the final results of stroke in the parenchyma of the brain, at the acute and subacute stages of stroke. This will allow the real-time assessment of treatment effects in acute and subacute stroke patients. PUBLIC HEALTH RELEVANCE: Stroke is a leading cause of death and disability in the United States. Using MRI images taken in the early stages of stroke, we aim to produce a predictor of stroke outcome so that therapeutic interventions can be assessed in real-time. PHS 398/2590 (Rev. 09/04, Reissued 4/2006) 1 Continuation Format Page

描述(申请人提供)：我们先前已经使用组合的MRI图像集和迭代自组织数据分析(ISODATA)，以获得对中风动物模型和人类的最终病变体积的独立于时间的预测。最近，我们改进和改进了这种方法，引入自适应神经网络(ANN)作为3个月T2加权图像的预测器，从而提供了基本上连续的组织结果描述符，而不是ISODATA中产生的更粗糙的分类方案。在R03的应用中，我们建议将这一方法应用于对人类手臂中风计划项目拨款在十年期间获得的现有人类研究数据集的重新分析，从而提供一个早期和稳健的中风结果预测因子。外部笔画数据库将用作独立的验证集。最后，将在抗血小板药物阿昔单抗的开放试验和盲法试验中检查MRI的变化。后一种检查将允许对ANN预测器的操作特性(即，其与临床测量的联系)的描述得到改进。如果这一努力成功，我们将产生一种替代的MRI结果测量方法，它将迅速可用(基本上是实时的)，以预测中风在急性和亚急性阶段在大脑实质中的最终结果。这将允许对急性和亚急性中风患者的治疗效果进行实时评估。 公共卫生相关性：在美国，中风是导致死亡和残疾的主要原因。利用在中风早期阶段拍摄的MRI图像，我们的目标是产生中风结果的预测指标，以便能够实时评估治疗干预措施。PHS 398/2590(09/04版，2006年4月重新发布)1续订格式页

项目成果

Predicting final extent of ischemic infarction using artificial neural network analysis of multi-parametric MRI in patients with stroke.

• DOI: 10.1371/journal.pone.0022626
• 发表时间: 2011
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Bagher-Ebadian H;Jafari-Khouzani K;Mitsias PD;Lu M;Soltanian-Zadeh H;Chopp M;Ewing JR
• 通讯作者: Ewing JR