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Detection of Children/Youth With Fetal Alcohol Spectrum Disorder Through Eye Movement Psychometric and Neuroimaging Data

机译:通过眼动心理测量和神经成像数据检测胎儿酒精频谱异常的儿童/青少年

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>Background: Fetal alcohol spectrum disorders (FASD) is one of the most common causes of developmental disabilities and neurobehavioral deficits. Despite the high-prevalence of FASD, the current diagnostic process is challenging and time- and money- consuming, with underreported profiles of the neurocognitive and neurobehavioral impairments because of limited clinical capacity. We assessed children/youth with FASD from a multimodal perspective and developed a high-performing, low-cost screening protocol using a machine learning framework.>Methods and Findings: Participants with FASD and age-matched typically developing controls completed up to six assessments, including saccadic eye movement tasks (prosaccade, antisaccade, and memory-guided saccade), free viewing of videos, psychometric tests, and neuroimaging of the corpus callosum. We comparatively investigated new machine learning methods applied to these data, toward the acquisition of a quantitative signature of the neurodevelopmental deficits, and the development of an objective, high-throughput screening tool to identify children/youth with FASD. Our method provides a comprehensive profile of distinct measures in domains including sensorimotor and visuospatial control, visual perception, attention, inhibition, working memory, academic functions, and brain structure. We also showed that a combination of four to six assessments yields the best FASD vs. control classification accuracy; however, this protocol is expensive and time consuming. We conducted a cost/benefit analysis of the six assessments and developed a high-performing, low-cost screening protocol based on a subset of eye movement and psychometric tests that approached the best result under a range of constraints (time, cost, participant age, required administration, and access to neuroimaging facility). Using insights from the theory of value of information, we proposed an optimal annual screening procedure for children at risk of FASD.>Conclusions: We developed a high-capacity, low-cost screening procedure under constrains, with high expected monetary benefit, substantial impact of the referral and diagnostic process, and expected maximized long-term benefits to the tested individuals and to society. This annual screening procedure for children/youth at risk of FASD can be easily and widely deployed for early identification, potentially leading to earlier intervention and treatment. This is crucial for neurodevelopmental disorders, to mitigate the severity of the disorder and/or frequency of secondary comorbidities.
机译:>背景:胎儿酒精谱系障碍(FASD)是发育障碍和神经行为缺陷的最常见原因之一。尽管FASD的患病率很高,但由于临床能力有限,当前的诊断过程仍然具有挑战性,并且既费时又费钱,但神经认知和神经行为障碍的特征报告不足。我们从多模式角度评估了患有FASD的儿童/青年,并使用机器学习框架开发了一种高性能,低成本的筛查方案。>方法和发现:患有FASD和年龄相匹配的参与者通常正在开发控制措施完成了多达六项评估,包括眼跳运动任务(扫视,反扫视和记忆引导扫视),免费观看视频,心理测验和call体神经成像。我们比较研究了应用于这些数据的新机器学习方法,以获取神经发育缺陷的定量特征,并开发了一种客观的高通量筛选工具来识别FASD的儿童/青少年。我们的方法提供了包括运动和视觉空间控制,视觉感知,注意力,抑制,工作记忆,学术功能和大脑结构在内的各个领域的各种不同措施的全面介绍。我们还表明,四到六次评估相结合可获得最佳的FASD与对照分类精度;但是,该协议昂贵且耗时。我们对这六项评估进行了成本/收益分析,并根据一部分眼动和心理测验开发了一种高性能,低成本的筛查方案,该方案在一定范围内(时间,成本,参与者年龄)达到了最佳结果,所需的管理权限以及使用神经影像设备的权限)。利用信息价值理论的见识,我们为处于FASD危险中的儿童提出了一种最佳的年度筛查程序。>结论:我们在约束条件下开发了一种高容量,低成本的筛查程序,预期的金钱利益,转诊和诊断过程的重大影响以及预期对受测个人和社会的最大长期利益。这项针对有FASD危险的儿童/青少年的年度筛查程序可以轻松,广泛地用于早期识别,有可能导致早期干预和治疗。这对于神经发育障碍,减轻疾病的严重性和/或继发合并症的频率至关重要。

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