PREDICTING OUTCOME IN CHILDREN WITH NEW-ONSET TICS USING NEUROIMAGING DATA

使用神经影像数据预测新发抽动儿童的结果

基本信息

批准号：
8995710
负责人：
KEVIN J BLACK
金额：
$ 19.06万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-02-01 至 2017-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8995710
关键词：
Affect Age Attention deficit hyperactivity disorder Autistic Disorder Brain Brain Mapping Brain region Child Childhood Chronic Chronic Disease Classification Clinical Clinical Data Control Groups Data Development Developmental Course Diagnosis Disease remission Early Diagnosis Early Intervention Early treatment Enrollment Epidemiology Evaluation Expert Opinion Foundations Future Gilles de la Tourette syndrome Goals Health Image Individual Investigation Knowledge Lead Literature Longitudinal Studies Machine Learning Magnetic Resonance Imaging Measures Methods Morbidity - disease rate Motor Movement Neurobiology Neurodevelopmental Disorder Noise Outcome Patients Pattern Population Prevalence Prevention Process Publishing Quality of life Remittance Research Rest Sampling Scanning School-Age Population Sorting - Cell Movement Staging Subgroup Symptoms Tic disorder Transient Tics Vocal Tics Weight base clinical practice design developmental disease diagnostic accuracy disorder control falls follow-up high risk improved improved outcome individual patient innovation insight interest neuroimaging neuropsychiatric disorder novel outcome forecast predict clinical outcome prevent tool unpublished works

项目摘要

DESCRIPTION (provided by applicant): Childhood onset neuropsychiatric disorders are often debilitating and are increasing in prevalence. Tourette Syndrome/Chronic Tic Disorder (TS/CTD), we propose, has a course that lends itself especially well to discovering optimal strategies for early diagnosis and prevention of developmental disorders. Common clinical practice and epidemiological data suggest that a large fraction (10-25%) of all children manifest motor and/or vocal tics at some age. Yet only 1-3% of all children have tics for the full year required for diagnosis of TS/CTD. The objective of the proposed research is to understand the structural and functional neuroimaging features of children with new-onset tics ("New Tics"), as the neurobiology of this population has not been investigated. Studying children with New Tics should provide the most leverage in understanding why tics remit in some children but not others. This proposal compares neuroimaging features of New Tics to TS/CTD and to controls, implements machine-learning tools to predict whether children with New Tics will remit or develop TS/CTD, and utilizes longitudinal scans to identify within-subject changes that occur as tics remit or persist. The proposed study will apply resting-state functional connectivity MRI (rs fcMRI) and structural MRI methods to investigate children with New Tics. Neuroimaging will be conducted on children with current, new- onset tics, and comparisons will be made to existing MRI data from children with diagnosed TS/CTD and controls. Follow-up evaluation (1 year after tic onset) of New Tics will allow us to identify which children's tics remitted completely and whic were actually in the earliest stages of TS/CTD, thus sorting this group into Remitted Tics and Converted TS/CTD subgroups. Based on the epidemiological data, we expect most of New Tics subjects to fall in the Remitted Tics subgroup. Longitudinal scans of the New Tics children will enable us to assess within-subject changes that occur with remittance or persistence of tics. This study will also apply machine learning tools, specifically Support Vector Machines (SVMs), to characterize features that distinguish Remitted Tics and Existing TS/CTD groups. Those features will then be used to predict whether tics in the New Tics group will remit (Remitted Tics) or persist (Converted TS/CTD) on an individual patient basis. Thus, we will be poised to identify differences, and potentially early predictors, of remittance and TS/CTD. This study will provide innovative, important data on a common clinical presentation: the child with New Tics. Completing our aims successfully will allow individual prediction of remission or progression, or at least will allow a New Tics sample to be enriched for high risk of developing TS/CTD, which would make prevention studies for TS/CTD feasible. We will also gain insight into the neurobiology of New Tics. Finally, this study is an essential first step towards a definitive longitudinal study that can improve diagnostic accuracy and settle questions of cause and effect. With successful completion of our aims, similar methods can be applied to other childhood onset neuropsychiatric disorders, setting the stage for early treatment or prevention of chronicity.

描述（由适用提供）：儿童发作神经精神疾病常常使人衰弱，并且患病率正在增加。我们建议，Tourette综合征/慢性疾病（TS/CTD）的课程特别适合发现早期诊断和预防发育障碍的最佳策略。常见的临床实践和流行病学数据表明，所有儿童中有很大一部分（10-25％）在某个年龄表现出运动和/或人声抽动。然而，所有儿童中只有1-3％的孩子在TS/CTD诊断所需的全年中都有抽动。拟议的研究的目的是了解具有新发作的儿童（“新抽动”）的结构和功能性神经影像学特征，因为尚未研究该人群的神经生物学。研究新的抽动儿童应该提供最大的利益，以理解为什么抽动在某些孩子中屈服而不是其他孩子。该建议将新抽动的神经成像特征与TS/CTD和控件进行了比较，并实现了机器学习工具，以预测患有新抽动的儿童是否会汇总或开发TS/CTD，并利用纵向扫描来识别随着抽动恢复或持久持续存在的对象内的变化。拟议的研究将应用静止状态功能连通性MRI（RS FCMRI）和结构性MRI方法调查了新的抽动儿童。神经影像学将对具有当前，新发作的儿童进行，并将与患有TS/CTD诊断和对照儿童的现有MRI数据进行比较。对新抽动的后续评估（在发作后1年）将使我们能够确定哪些儿童抽动实际上处于TS/CTD的最早阶段，从而将该组分类为已恢复的TICS并转换为TS/CTD子组。根据流行病学数据，我们预计大多数新的抽动主体都会属于返回的抽动亚组。对新抽动儿童的纵向扫描将使我们能够评估汇款或持久性发生的受试者内部变化。这项研究还将应用机器学习工具，特别是支持向量机（SVM）来表征具有区分抽动和现有TS/CTD组的功能。然后，这些功能将用于预测新的TICS组中的抽动是否会汇总（汇款）或在单个患者基础上持续（转换为TS/CTD）。这是我们将被毒化的汇率和可能的早期预测因素而被毒化。这项研究将提供有关常见临床表现的创新，重要的数据：有新的抽动的孩子。成功完成我们的目标将允许个人预测缓解或进展，或者至少将允许新的抽动样本以高风险发展TS/CTD，这将使TS/CTD的预防研究可行。我们还将深入了解新抽动的神经生物学。最后，这项研究是迈向确定的纵向研究的重要第一步，该研究可以提高诊断准确性并解决因果关系的问题。通过成功完成我们的目标，可以将类似的方法应用于其他儿童时期神经精神疾病，为早期治疗或预防慢性病奠定了基础。