Generalizing and Standardizing fMRI Tools for Differentiating Mental Illnesses and Predicting Medication-Class Response in Patients

泛化和标准化功能磁共振成像工具，用于区分精神疾病和预测患者的药物类别反应

• 批准号: 10264906
• 负责人: Henry Jeremy Bockholt
• 金额: $ 45.15万
• 依托单位: ADVANCED BIOMEDICAL INFORMATICS GROUP
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-16 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10264906
• 关键词: Algorithms; Antidepressive Agents; Back; Biological; Biological Markers; Bipolar Disorder; Brain; Brain imaging; Businesses; Classification; Clinic; Clinical Decision Support Systems; Clinical Trials; Clinical assessments; Collaborations; Combination Medication; Communities; Community Surveys; Complex; Consultations; Data; Data Analyses; Data Collection; Data Set; Demography; Depressed mood; Development; Diagnosis; Diagnostic and Statistical Manual of Mental Disorders; Differential Diagnosis; Disease remission; Early Intervention; Ensure; Evaluation; Face; Feedback; Financial cost; Functional Magnetic Resonance Imaging; Future; Generations; Geographic Locations; Goals; Image; Individual; Intuition; Lead; London; Machine Learning; Magnetic Resonance Imaging; Major Depressive Disorder; Manic; Mental Depression; Mental disorders; Minority; Modernization; Mood Disorders; New Mexico; Obsessive-Compulsive Disorder; Ontario; Patients; Pharmaceutical Preparations; Phase; Positioning Attribute; Post-Traumatic Stress Disorders; Procedures; Process; Protocols documentation; Psychiatric Diagnosis; Psychiatrist; Recording of previous events; Reporting; Research; Rest; Running; Scanning; Site; Societies; Standardization; Suicide; Surveys; Symptoms; Technology Transfer; Therapeutic; Time; Training; Universities; Validation; Work; accurate diagnosis; base; biomedical informatics; clinical care; clinical development; clinical trial readiness; cloud based; commercialization; computerized data processing; cost; data acquisition; data repository; data sharing; data tools; depressive symptoms; disability-adjusted life years; effective therapy; emerging adulthood; experience; high risk; imaging biomarker; machine learning method; member; mortality risk; neuroimaging; novel; precision medicine; quality assurance; response; support tools; tool; treatment planning; treatment response; treatment strategy; web portal

Project Summary/Abstract Mood disorders, like many psychiatric conditions, have their onset in emerging adulthood and often last a lifetime. Mental illnesses have an excessively large loading of Disability Adjusted Life Years, making early intervention crucial for both individuals and society. Differentiating bipolar disorder (BD) from major depressive disorder (MDD) based on the Diagnostic and Statistical Manual (DSM) can be especially challenging if clear mania is absent. In fact, BD patients go an average of 6-10 years without the proper diagnosis, with 70% misdiagnosed with MDD instead. The challenge of identifying BD patients among depressed individuals is complex but critical because diagnosis determines treatment. The use of antidepressant (AD) medications in patients with BD can lead to worsening of illness. We have recently shown that, using resting fMRI, we can predict future medication class response with high accuracy (> 90%). In this project we will build on this work to generalize to a new MRI scanner and clinical assessment protocol. In addition we will develop, in consultation with multiple psychiatrists, a cloud-based tool to analyze and report the results from the brain imaging protocol and machine learning analysis, in a timely, meaningful, and interpretable manner. Results are expected to be an important step forward in the eventual development of clinical useful markers of mental illness. 2

项目摘要/摘要 情绪障碍与许多精神病疾病一样，在成年后开始发作 寿命。精神疾病的残疾调整年份过多地负载，使早期 干预对个人和社会至关重要。区分躁郁症（BD）与主要抑郁症 基于诊断和统计手册（DSM）的障碍（MDD）如果清晰明了，可能特别具有挑战性 躁狂症不存在。实际上，BD患者平均患有6 - 10年没有适当的诊断，其中70％ 改用MDD误诊。在抑郁症患者中识别BD患者的挑战是 复杂但至关重要，因为诊断决定治疗。在使用抗抑郁药（AD）药物 BD患者可能导致疾病恶化。我们最近表明，使用静止fMRI，我们可以 高精度（> 90％）预测未来的药物类反应。在这个项目中，我们将以这项工作为基础 概括新的MRI扫描仪和临床评估方案。此外，我们将在咨询中发展 借助多个精神科医生，一种基于云的工具来分析和报告脑成像协议的结果 和机器学习分析，以及时，有意义且可解释的方式。结果预计将是 最终发展精神疾病的有用标记的重要一步。 2