Diffeomorphometry applied to functional connectivity in schizophrenia using ultrahigh resolution MRI

使用超高分辨率 MRI 将微分形态测量应用于精神分裂症的功能连接

• 批准号: 10551860
• 负责人: RUSSELL L MARGOLIS
• 金额: $ 24.5万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-17 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10551860
• 关键词: 3-Dimensional; Address; Affect; Area; Biological Markers; Biology; Brain region; Clinical; Diagnosis; Disease; Family; Functional Magnetic Resonance Imaging; Functional disorder; Goals; Image; Individual; Investigation; Magnetic Resonance Imaging; Major Mental Illness; Measurement; Measures; Medicine; Methods; Monitor; Patients; Pilot Projects; Prevalence; Prognosis; Protocols documentation; Resolution; Rest; Sample Size; Schizophrenia; Signal Transduction; Societies; Specific qualifier value; Structure; Surface; Symptoms; System; Testing; Thalamic structure; Thick; Variant; design; disease classification; frontal lobe; high risk; improved; mathematical methods; method development; novel; patient population; responders and non-responders; standard measure; tool; treatment response; ultra high resolution

Project Summary Schizophrenia is a disorder with a life-time world-wide prevalence of ~0.5% and devastating consequences for affected individuals, their families, and society. Improved understanding of the disruptions in cortical circuitry thought to underlie schizophrenia could go a long way toward addressing challenges in understanding the pathophysiology of schizophrenia, as well as the challenges of improving schizophrenia nosology, diagnosis, and treatment. Our guiding hypothesis is that schizophrenia is a consequence of cortical-cortical and cortical-subcortical functional dysconnectivity, and particularly the circuitry between the thalamus and the cortex. Understanding this dysconnectivity could have profound implications for the field. In this proposal, we will develop a new and potentially power method for the analysis of functional connectivity between thalamic subregions and deep and superficial layers of the cortex, using a sophisticated mathematical approach (diffeomorphometry) to precisely determine the thickness of the cortex at specified regions of the brain. In Aim 1, we will optimize this method for both resting and activated thalamocortical connectivity, using ultra-high field strength (7 Tesla) fMRI. In Aim 2, we will test the protocols developed in Aim 1 in 20 individuals with schizophrenia compared to 20 healthy controls. We will determine if subdividing the cortex using the diffeomorphometric approach will more clearly delineate the dysconnectivity in patients, with the potential benefit that investigations can use smaller sample sizes, and that more subtle clinical factors associated with aberrant connectivity can be discerned. In addition, this improved resolution at the cortex may facilitate more nuanced understanding of the specific thalamic origins of aberrant signals and the differences in dysconnectivity across different cortical layers. Overall, the goal is to establish methods that can be used to further develop functional connectivity as a biomarker useful in nosology and prognosis, and in the prediction and monitoring of treatment response.

项目摘要 精神分裂症是一种在全世界范围内终生患病率约为0.5%的疾病， 为受影响的个人、他们的家庭和社会。提高了对大脑皮层神经元损伤的认识 被认为是精神分裂症基础的电路可能会在很大程度上解决精神分裂症的挑战。 了解精神分裂症的病理生理学，以及改善精神分裂症的挑战 疾病分类诊断和治疗我们的指导假设是精神分裂症是 皮质-皮质和皮质-皮质下功能性连接障碍，特别是 丘脑和皮层理解这种连接障碍可能对该领域产生深远的影响。 在这个建议中，我们将发展一个新的和潜在的权力的方法来分析功能连接 在丘脑亚区和皮层的深层和浅层之间，使用复杂的 数学方法（骨形态测量法），以精确地确定在指定的皮质厚度 大脑的各个区域。在目标1中，我们将针对静息和激活的丘脑皮质优化该方法 连接，使用超高场强（7特斯拉）功能磁共振成像。在目标2中，我们将测试 目的1对20例精神分裂症患者和20例健康对照者进行比较。我们将决定是否细分 使用脑形态测量方法的皮层将更清楚地描绘患者的连接障碍， 潜在的好处是研究可以使用更小的样本量， 与异常连通性相关的信息。此外，这种提高的分辨率在皮层 可能有助于更细致地了解异常信号的特定丘脑起源， 不同皮质层之间的连接障碍差异。总的来说，目标是建立方法， 可用于进一步开发功能连接性，作为疾病分类学和预后中有用的生物标志物， 预测和监测治疗反应。