Brain Connectivity Patterns in Chronic Temporomandibular Joint Disorders
慢性颞下颌关节疾病的大脑连接模式
基本信息
- 批准号:10212549
- 负责人:
- 金额:$ 24.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-01 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:AcuteAffectAmygdaloid structureAreaBackBase of the BrainBrainBrain imagingCareer ChoiceChronicClinicalClinical ResearchComplementDataDentistsDevelopmentDiagnosticEarly identificationEmotionalEmotionsFunctional disorderFutureGoalsHealth Care CostsHealthcareHumanImpairmentIndividualLearningMeasuresMedialMentorsMentorshipMethodsNeurosciencesNociceptionNucleus AccumbensOrofacial PainPainPain DisorderPain ResearchPain managementPain-FreePathway interactionsPatient Outcomes AssessmentsPatientsPatternPeripheralPersistent painPhasePhenotypePopulationPrefrontal CortexProtocols documentationPsychophysicsResearch PersonnelResearch TrainingRestRiskSamplingScientistSensorySignal TransductionSiteStimulusStructureSubgroupSymptomsTemporomandibular Joint DisordersTestingTissuesTooth structureTrainingTranslational ResearchTrigeminal SystemTweensUnited States National Institutes of Healthbiopsychosocialbrain pathwaybrief screeningcare seekingcareercareer developmentchronic painchronic pain patientchronic painful conditionclinical phenotypeconditioned pain modulationconnectomedisabilityeffective therapyhuman subjectimaging modalityimprovedinstrumentmidbrain central gray substancemultimodalityneuroimagingoutcome forecastpain inhibitionpain patientpain processingpreventpsychosocialresearch studyresponsestatisticstreatment strategy
项目摘要
Temporomandibular joint and muscle disorders (TMJD) are the most common cause of orofacial pain second
only to tooth pain, for which effective treatment strategies remain empirical. Approximately 15% of acute TMJD
patients will develop chronic pain, and some of these patients develop high pain-related disability that is
associated with poor prognosis, even with treatment, and greater health care costs. Chronic TMJD pain
pathophysiology includes dysregulation of brain circuits, and recent evidence suggests that connectivity
patterns within the thalamocortical, antinociceptive, and corticolimbic brain circuits are associated with
processing, modulation and persistence of pain. These brain circuits connectivity patterns have not been
described in chronic TMJD patients and it is unknown if they can distinguish pain-related disability levels in
patients. The overall objective of this proposal is to identify brain connectivity patterns that can differentiate
chronic TMJD patients with high pain-related disability. To attain this objective, Dr. Moana-Filho will be trained
under the mentorship of Dr. Christophe Lenglet in neuroimaging (primary mentor), Dr. David Bereiter in
trigeminal neuroscience and Dr. Lynn Eberly in statistics. During the K99 mentored phase (Years 1-2; Aims 1 &
2), Dr. Moana-Filho will learn advanced analyzes of neuroimaging data from the NIH Human Connectome
Project (HCP) (Aim 1) and will conduct a research study of chronic TMJD patients and pain-free controls using
validated clinical phenotyping protocol, endogenous pain controls testing and multi-modal neuroimaging
protocol developed by the HCP (Aim 2). Aim 1 will identify connectivity patterns within the thalamocortical,
antinociceptive, and corticolimbic brain circuits as potential measures of sensory, modulatory, and emotional
aspects of pain processing, respectively, from a large sample of healthy subjects from the HCP. Aim 2 will
identify intrinsic connectivity patterns within these brain circuits as potential “signatures” for pain-related
disability in chronic TMJD pain patients. During the R00 independent phase (Years 3-5; Aim 3), Dr. Moana-
Filho will conduct a second study of chronic TMJD patients and matched controls to determine if evoked
changes of connectivity patterns within those brain circuits evoked with noxious stimuli engaging endogenous
pain controls can differentiate patients with high disability. The overall goal is to combine clinical sensory
testing with psychosocial measures to enhance the precision and validity of brain imaging methods to
differentiate subgroups of chronic pain patients. These newly developed brain-based signatures used along
brief screening instruments are expected to guide clinicians and researchers in discriminating subgroups of
chronic pain patients. The proposed training will support Dr. Moana-Filho career development as a dentist
scientist dedicated to translational research in orofacial pain and is an initial step to achieve his long-term
career goal of identifying brain-based signatures for transition of acute to chronic TMJD pain, supporting early
identification of patients at risk for such transition and development of strategies to prevent it.
颞下颌关节和肌肉疾病(TMJD)是引起口腔面部疼痛的最常见原因,其次是
只对牙痛有效的治疗策略仍然是经验性的。约15%的急性TMJD
患者会出现慢性疼痛,其中一些患者会发展为高度疼痛相关的残疾,即
与预后差有关,甚至与治疗有关,以及更高的医疗费用。慢性TMJD疼痛
病理生理学包括大脑回路的失调,最近的证据表明,连接
丘脑皮质、抗伤害性感觉和皮质边缘脑回路中的模式与
疼痛的加工、调制和持续。这些大脑回路的连接模式还没有
在慢性TMJD患者中被描述,目前尚不清楚他们是否能区分疼痛相关残疾水平
病人。这项提案的总体目标是确定可以区分
具有高度疼痛相关残疾的慢性TMJD患者。为了实现这一目标,莫阿纳-菲略博士将接受培训
在Christophe Lenglet博士的指导下(主要导师),David Bereiter博士在
三叉神经科学和统计学中的林恩·埃伯利博士。在K99指导阶段(1-2年;AIMS 1&
2),Moana-Filho博士将学习来自NIH人类连接组的神经成像数据的高级分析
项目(HCP)(目标1),并将对慢性TMJD患者和使用
经过验证的临床表型方案、内源性疼痛控制测试和多模式神经成像
HCP制定的协议(目标2)。目标1将确定丘脑皮质内的连接模式,
抗伤害性和皮质边缘脑回路作为感觉、调节和情绪的潜在测量
分别从来自HCP的健康受试者的大样本中了解疼痛处理的各个方面。目标2将
确定这些大脑回路中的内在连接模式是与疼痛相关的潜在“信号”
慢性TMJD疼痛患者的残疾。在R00独立阶段(3-5年;目标3),莫阿纳博士-
Filho将对慢性TMJD患者和匹配的对照组进行第二项研究,以确定是否诱发了
伤害性刺激与内源性刺激诱发的脑回路内连接模式的变化
疼痛控制可以区分高度残疾的患者。总体目标是结合临床感官
用心理社会措施测试以提高脑成像方法的精确度和有效性
区分慢性疼痛患者的亚组。这些新开发的基于大脑的签名与
简要的筛查工具有望指导临床医生和研究人员区分不同的亚群
慢性疼痛患者。拟议的培训将支持莫阿纳-菲略博士作为牙医的职业发展。
致力于口面部疼痛的翻译研究的科学家,是实现其长期目标的第一步
职业目标:确定急性向慢性TMJD疼痛过渡的基于大脑的信号,支持早期
识别有这种过渡风险的患者,并制定预防策略。
项目成果
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Estephan J Moana-Filho其他文献
Estephan J Moana-Filho的其他文献
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{{ truncateString('Estephan J Moana-Filho', 18)}}的其他基金
Brain Connectivity Patterns in Chronic Temporomandibular Joint Disorders
慢性颞下颌关节疾病的大脑连接模式
- 批准号:
10466898 - 财政年份:2020
- 资助金额:
$ 24.9万 - 项目类别:
Brain Connectivity Patterns in Chronic Temporomandibular Joint Disorders
慢性颞下颌关节疾病的大脑连接模式
- 批准号:
10252071 - 财政年份:2020
- 资助金额:
$ 24.9万 - 项目类别:
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