Defining Translational Approaches for the Image-based Detection of Prenatal Alcohol Exposure

定义基于图像的产前酒精暴露检测的转化方法

• 批准号: 10684154
• 负责人: Michael Suttie
• 金额: $ 25.24万
• 依托单位: UNIVERSITY OF OXFORD
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10684154
• 关键词: 3-Dimensional; Address; Adolescent; Adult; Age; Agreement; Alcohols; Assessment tool; Automation; Brain; Categories; Cellular Phone; Cephalic; Child; Clinic; Clinical; Clinical assessments; Cognitive; Collaborations; Communities; Computer software; Corpus Callosum; Data; Data Management Resources; Data Set; Devices; Diagnosis; Discrimination; Elements; Ensure; Ethnic Origin; Evaluation; Face; Feedback; Fetal Alcohol Exposure; Fetal Alcohol Spectrum Disorder; Fetal Alcohol Syndrome; Fetal alcohol effects; Goals; Image; Image Analysis; Imaging Device; Impaired cognition; Individual; Infant; Intervention; Intervention Studies; Length; Life; Lip structure; Literature; Longevity; MRI Scans; Machine Learning; Mandible; Measurement; Methodology; Methods; Micrognathism; Morphology; Neonatal; Neurocognitive; Ocular orbit; Online Systems; Orbital separation excessive; Outcome; Output; Parents; Population; R24; Request for Applications; Research; Resources; Screening procedure; Secondary to; Sensitivity and Specificity; Sex Differences; Shapes; Smoking; Surface; System; Tablets; Techniques; Technology; Testing; Thinness; Three-Dimensional Image; Three-Dimensional Imaging; Time; Traction; Training; Translating; Trees; Ultrasonography; Validation; Variant; Work; alcohol consumption during pregnancy; alcohol exposure; brain morphology; brain shape; clinical application; clinical diagnosis; cloud platform; cognitive testing; comparative; cost; deep learning; experience; imaging detection; improved; midfacial hypoplasia; neural; neurocognitive test; offspring; polysubstance use; recruit; screening; sex; sexual dimorphism; skills; tool; trait; translational approach; translational goal; ultrasound

As a constituent component of CIFASD5, this project will focus on improving the identification of individuals with prenatal alcohol exposure (PAE), across the lifespan, with the primary goal of translation for clinical application. We target two main categories outlined in the Request for Application (RFA) 1. To identify FASD cases early and accurately, and 2. To expand and translate basic and mechanistic understandings of the effects of PAE. To address these topics, we aim to improve the accuracy and reliability of the clinical recognition of FASD, controlling for the influence of sex, co- exposures, and age. We seek to understand better how neurocognitive and facial morphology are correlative and covariant in FASD and exploit this relationship to improve screening accuracy. Previously, we have implemented methods and associated software for analyzing face shape and face - brain-cognitive relationships to detect the effects of PAE. In doing so, we have created an effective toolkit to automatically and objectively identify cardinal and subtle PAE-associated facial dysmorphism across the FASD spectrum. It is now a priority to refine and optimize our methods, utilizing low-cost 3D imaging devices to validate and distribute to the clinical community. To accomplish our goals, we propose to follow specific aims: 1. Explore the impact of factors secondary to alcohol exposure that may influence facial morphology; 2. Detect facial, cranial, and neural effects of prenatal alcohol exposure across the lifespan; 3. Develop, test, and validate automated methods for FASD screening, integrating neurocognitive assessment tools and distributing to the clinical community. Achieving aims 1 and 2 will dramatically refine FASD recognition by understanding the factors secondary to alcohol that may influence outcomes across the lifespan. Successful demonstration of aim 2 will achieve the earliest possible diagnosis enabling further research and feedback for intervention studies and also focus on recognizing traits in adults - a population significantly underreported in the literature. Ultimately, aim 3 encompasses the primary goal of the project, developing, testing, and validating multi-domain screening tools that assist with clinical identification. We will work closely with consortium partners who will recruit subjects and provide facial images and neurocognitive assessment data (U01: Chambers; U01: Coles & Weinberg; U01: Wozniak; U01: DiClemente; U01: Petrenko). Particularly close collaboration is required for the face-neurocognitive analysis, where we will integrate and combine facial and neurocognitive screening tools (U01: Mattson). We will rely on research resources for data management (R24: Wetherill) and to validate screening tools and gain clinical feedback (R24: Del Campo).

作为CIFASD5的一个组成部分，本项目将侧重于改进鉴定