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Neuroethics of Predictive MRI Testing: Parental Attitudes Towards Pre-Symptomatic Identification of Autism Spectrum Disorder

预测性 MRI 测试的神经伦理学：父母对自闭症谱系障碍症状前识别的态度

基本信息

批准号：
10003829
负责人：
Kate E. MacDuffie
金额：
$ 6.66万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-16 至 2020-09-15
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10003829
关键词：
Address Attitude BRAIN initiative Behavioral Model Belief Bioethics Brain Brain Diseases Brain imaging Categories Child Childhood Classification Clinical Complement Data Data Collection Data Set Decision Making Development Diagnosis Diagnostic Disclosure Disease Early Intervention Environmental Risk Factor Ethical Issues Ethics Face Future Genetic Genetic Research Genetic screening method Genomics Goals Guidelines Human Individual Infant Intention Interview Judgment Knowledge Literature Machine Learning Magnetic Resonance Imaging Measures Modality Neurosciences Neurosciences Research Parents Participant Pattern Pediatric Hospitals Population Predictive Factor Qualitative Research Reporting Research Research Methodology Research Personnel Research Training Review Literature Risk Sampling Site Surveys Symptoms Techniques Test Result Testing Time Training University resources Validation Washington Work autism onset autism spectrum disorder autistic children base career clinical Diagnosis clinical predictors frontier high risk infant imaging study interest neuroethics neuroimaging parental influence prediction algorithm predictive test programs recruit systematic review theories

项目摘要

PROJECT SUMMARY Machine-learning-based classification of neuroimaging data (hereafter ML-MRI) to predict clinical diagnoses has increased substantially in the last decade. Despite the promise of ML for clinical classification and prediction, no work has been done to anticipate the ethical obligations and challenges that emerge when ML algorithms predict clinical diagnoses in pre-symptomatic individuals. Two recent reports from the Infant Brain Imaging Study (IBIS) have exemplified the ML classification approach by predicting 24-month clinical diagnosis of autism spectrum disorder (ASD) from 6-month MRI data in infants at high and low familial risk for ASD. These preliminary results demonstrated—for the first time—the feasibility of identifying infants prior to onset of ASD symptoms, and raised critical ethical questions about whether and how to disclose predictive ML- MRI classification of ASD to parents of pre-symptomatic infants. The proposed research aims to investigate parental attitudes towards predictive ML-MRI testing in IBIS, and addresses a core principle of BRAIN Initiative: considering the ethical implications of neuroscience research. Aim 1 will review the bioethics literature on disclosure of results in genetic research, and identify overlapping and distinct ethical considerations for disclosure using ML-MRI vs. genetic testing for disease prediction. Aim 2 will use a theory-based approach to assess the attitudes of IBIS parents towards predictive ML-MRI testing through qualitative interviews and a quantitative survey. The knowledge gained through this research will help investigators make ethical decisions about disclosure in future neuroimaging studies of high-risk infants. Our long-term goal is to develop guidelines for navigating the unique ethical challenges posed by a new frontier in neuroimaging research: clinical prediction via increasingly powerful and sophisticated ML-based analyses of large neuroimaging datasets. The proposed research and training plan will leverage the resources of the University of Washington Autism Center, the Treuman Katz Center for Pediatric Bioethics at Seattle Children’s Hospital, and the multi-site, longitudinal Infant Brain Imaging Study. The applicant will receive formal training in neuroethics, pediatric bioethics, and qualitative research methods, which will complement her prior skillset and prepare her for an independent research career investigating ethical issues in pediatric neuroscience.

项目总结

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Presymptomatic Detection and Intervention for Autism Spectrum Disorder.

自闭症谱系障碍的症状前检测和干预。

DOI：
10.1542/peds.2020-032250
发表时间：
2021
期刊：
Pediatrics
影响因子：
8
作者：
MacDuffie,KatherineE;Estes,AnnetteM;Harrington,LucasT;Peay,HollyL;Piven,Joseph;PruettJr,JohnR;Wolff,JasonJ;Wilfond,BenjaminS
通讯作者：
Wilfond,BenjaminS

A "salad bowl" approach to neuroethics collaboration.

神经伦理学合作的“沙拉碗”方法。