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: 10348847
• 负责人: RUSSELL L MARGOLIS
• 金额: $ 22.02万
• 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 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10348847
• 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; Life; 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; Time; 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

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 精神分裂症是一种疾病，全世界范围内终生患病率约为0.5%，其后果是灾难性的 对于受影响的个人、他们的家庭和社会。提高了对大脑皮质损伤的理解 被认为是精神分裂症基础的电路可能在很大程度上有助于解决 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 病因学、诊断和治疗。我们的指导性假设是精神分裂症是 皮质-皮质和皮质下-皮质功能障碍，特别是大脑皮质-皮质和皮质下-皮质之间的回路 丘脑和大脑皮质。了解这种连接障碍可能会对该领域产生深远的影响。 在这个提案中，我们将开发一种新的、潜在的功率方法来分析功能连通性 在丘脑亚区域和皮质的深层和浅层之间，使用复杂的 精确测定特定区域皮质厚度的数学方法(微分形态计量法) 大脑的不同区域。在目标1中，我们将针对静息和激活丘脑皮质来优化这种方法。 连接，使用超高场强(7特斯拉)功能磁共振。在目标2中，我们将测试在 目的1/20例精神分裂症患者与20例健康对照进行比较。我们将确定是否细分 使用差异形态计量学方法的皮质将更清楚地描绘患者的连接障碍， 潜在的好处是，研究可以使用较小的样本量，以及更微妙的临床因素 与异常连接相关联。此外，这提高了大脑皮层的分辨率 可能有助于更细微地理解异常信号的特定丘脑起源和 不同大脑皮层之间连接障碍的差异。总体而言，目标是建立 可用于进一步发展功能连接，作为在病因学和预后中有用的生物标志物，以及 在治疗反应的预测和监测中。