Advancing Personalized Antidepressant Treatment Using PET/MRI

使用 PET/MRI 推进个性化抗抑郁治疗

• 批准号: 9045708
• 负责人: Christine Delorenzo
• 金额: $ 70.18万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9045708
• 关键词: Address; Aftercare; Algorithms; Anterior; Antidepressive Agents; Benchmarking; Biological Markers; Biology; Biometry; Blood; Blood specimen; Body Surface Area; Body mass index; Brain; Brain region; Categories; Catheters; Cerebrum; Chronic; Clinical; Clinical Research; Consensus; Data; Data Set; Development; Devices; Diagnosis; Diagnostic; Dimensions; Disease; Disease remission; Dose; Effectiveness; Escitalopram; Factor Analysis; Family; Functional disorder; Future; Glucose; Goals; Hamilton Rating Scale for Depression; Health; Image; Individual; Institution; Insula of Reil; Left; Magnetic Resonance; Magnetic Resonance Imaging; Major Depressive Disorder; Measures; Mental Depression; Metabolism; Methodology; Methods; Midbrain structure; Modeling; Morbidity - disease rate; National Institute of Mental Health; Neurobiology; Outcome Measure; Outcome Study; Physiological; Placebo Effect; Placebos; Plasma; Positron-Emission Tomography; Precision therapeutics; Prefrontal Cortex; Price; Procedures; Radioactivity; Randomized; Recurrence; Research Domain Criteria; Research Personnel; Sample Size; Sampling; Selection for Treatments; Selective Serotonin Reuptake Inhibitor; Signal Transduction; Symptoms; Techniques; Testing; Tracer; Training; Treatment Efficacy; Treatment outcome; Use Effectiveness; Validation; Venous; Wrist; base; brain metabolism; burden of illness; cost; cost effective; depressed patient; fluorodeoxyglucose; fluorodeoxyglucose positron emission tomography; imaging modality; improved; ineffective therapies; innovation; insight; lean body mass; metabolic rate; mortality; multidisciplinary; novel; novel therapeutics; predictive signature; relating to nervous system; response; software development; symptom treatment; symptomatic improvement; tool; treatment trial

 DESCRIPTION (provided by applicant): Major Depressive Disorder (MDD) is a highly prevalent, chronic and recurrent disorder predicted to be the leading cause of disease burden by the year 2030. Monotherapy with selective serotonin reuptake inhibitors (SSRIs) is the most widely used MDD treatment. However, on average, SSRIs require six weeks for onset of action, and two-thirds of those on SSRIs fail to achieve remission. Consequently, to reduce MDD morbidity and mortality, there is a critical need to improve our understanding of the neural signatures predictive of, and correlated with, an individual's SSRI treatment outcome. Positron Emission Tomography (PET) imaging with 2- [18F]-fluorodeoxyglucose (FDG), a sensitive indicator of cerebral function, has the potential to provide this insight. In this proposal, we wil image 100 MDD subjects using a simultaneous PET/MRI scanner prior to and following 12 weeks of antidepressant treatment. Subjects will be randomized to either escitalopram (an SSRI) or placebo, allowing separation of SSRI-induced changes from the placebo effect. This proposal overcomes limitations of previous FDG treatment studies (including our own) by using the largest sample size to date and full FDG quantification (including arterial blood analysis). Pretreatment images will allow the determination of a pretreatment marker of SSRI effectiveness. Post to pre-treatment image comparison will allow analysis of treatment-induced brain metabolism changes and the correlation between these changes and certain dimensions of NIMH's Research Domain Criteria (RDoC). Since these domains are independent of diagnosis, this study has the potential to improve our understanding and treatment of these symptoms across all diagnoses. Regardless of study outcome, these aims will provide insight into the pathophysiology of MDD and mechanism of SSRI action. This would have immediate and significant clinical utility. Further, identification of useful brain markers is the first step toward the development of other, potentially non-imaging based, diagnostics. In addition to these clinical aims, development and validation of significant and novel methodology/hardware pioneered by Stony Brook investigators is proposed. Our group has previously successfully developed and tested a simultaneous estimation algorithm that calculates a subject's arterial input function (required for the most accurate quantification) from a single blood sample. In this application, we will both validate this algorithm as well as use statistical or physiological modeling to obviate the need for any blood samples. We will also validate a miniature PET scanner that fits around the wrist for estimation of arterial samples. These innovative techniques have the potential to entirely eliminate the need for blood sampling (while obtaining full quantification), which would be a significant advantage for the majority of institutions that are nt equipped for blood analysis or cannot afford it. Our multidisciplinary team is uniquely able to perform this clinical and technical study, the results of which have the potential to advance the field, as well as reduce barriers (price and subject burden) to widespread clinical and research PET use.

 描述(由申请人提供)：严重抑郁障碍(MDD)是一种高度流行的慢性和复发性疾病，预计到2030年将成为疾病负担的主要原因。选择性5-羟色胺再摄取抑制剂(SSRIs)的单一疗法是最广泛使用的MDD治疗方法。然而，平均而言，SSRIs需要六周的时间才能开始行动，而服用SSRIs的人中有三分之二未能实现缓解。因此，为了减少MDD的发病率和死亡率，迫切需要提高我们对神经信号对个体SSRI治疗结果的预测和关联的理解。2-[18F]-氟代脱氧葡萄糖(FDG)正电子发射断层扫描(PET)是脑功能的灵敏指标，具有提供这种洞察力的潜力。在这项建议中，我们将在抗抑郁药物治疗12周之前和之后使用同步的PET/MRI扫描仪对100名MDD受试者进行成像。受试者将被随机分为艾司西普兰(一种SSRI)或安慰剂，允许将SSRI诱导的变化与安慰剂效果分开。这项建议克服了以前FDG治疗研究(包括我们自己的)的局限性，使用了迄今为止最大的样本量和完整的FDG量化(包括动脉血液分析)。前处理图像将允许确定SSRI有效性的前处理标记。治疗后与治疗前的图像比较将有助于分析治疗引起的大脑新陈代谢变化，以及这些变化与NIMH研究领域标准(RDoC)的某些维度之间的相关性。由于这些领域与诊断无关，这项研究有可能提高我们对所有诊断中这些症状的理解和治疗。无论研究结果如何，这些目的都将为深入了解MDD的病理生理学和SSRI的作用机制提供帮助。这将立即产生重大的临床效用。此外，识别有用的大脑标记是第一步。 其他可能不基于成像的诊断学的发展。除了这些临床目标，石溪研究人员还提议开发和验证由Stony Brook研究人员开创的重要和新颖的方法/硬件。我们团队之前已经成功地开发并测试了一种同步估计算法，该算法可以根据单个血液样本计算受试者的动脉输入函数(最准确的量化所需的)。在这个应用程序中，我们将验证该算法，并使用统计或生理建模来消除对任何血液样本的需求。我们还将验证一种安装在手腕上的微型PET扫描仪，用于评估动脉样本。这些创新技术有可能完全消除对血液采样的需要(同时获得完全量化)，这对大多数没有血液分析设备或负担不起血液分析的机构来说将是一个重大优势。我们的多学科团队独一无二地能够执行这项临床和技术研究，其结果有可能推动该领域的发展，并减少广泛使用临床和研究PET的障碍(价格和主题负担)。