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

描述（由申请人提供）：我们之前使用了组合MRI图像集和迭代自组织数据分析（ISODATA），以获得中风动物模型和人类最终病变体积的时间无关预测。最近，我们已经完善和改进了这种方法，通过引入自适应神经网络（ANN）作为预测的T2加权图像在3个月，从而提供了一个基本上连续的描述符的组织结果，而不是粗糙得多的分类方案中产生的ISODATA。在此R 03申请中，我们建议将此方法应用于重新分析现有的人类研究数据集，该数据集由卒中项目资助的人类研究组在十年内获得，从而提供卒中结局的早期和可靠预测。外部中风数据库将被用作独立的验证集。最后，将进行抗血小板药物阿昔单抗的开放标签试验和盲法试验中的MRI变化检查。后面的检查将允许描述ANN预测器的操作特性（即，其与临床测量的连接）进行细化。如果这项努力取得成功，我们将产生一种替代的MRI结果指标，该指标将很快可用（基本上是真实的时间），以预测脑实质中风在急性和亚急性阶段的最终结果。中风。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：中风是美国死亡和残疾的主要原因。使用在中风早期拍摄的MRI图像，我们的目标是产生中风结果的预测因子，以便可以实时评估治疗干预。PHS 398/2590（2004年9月修订，2006年4月重新印发）1

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