Multimodal MRI Biomarker of Mild Cognitive Impairment in Breast Cancer
Multimodal MRI Biomarker of Mild Cognitive Impairment in Breast Cancer
批准号:
8551730
负责人:
SHELLI R KESLER
金额:
$51.33万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-27 至 2017-06-30
关键词:
Adjuvant ChemotherapyAffectAftercareAgeAgingAtrophicBehaviorBiological MarkersBrainBrain regionCancer PatientCancer SurvivorChemotherapy-Oncologic ProcedureClinicalCognitionCognitiveComorbidityDementiaDiagnosisDiseaseEpidemiologyEpisodic memoryFatigueFemaleFrequenciesGeneticGenotypeImaging TechniquesImpaired cognitionImpairmentIncidenceIndividualIntegration Host FactorsLifeLongitudinal StudiesMagnetic Resonance ImagingMeasuresMediatingMemoryMental DepressionMethodsModelingMoodsNerve DegenerationPathway interactionsPatternPerformancePopulationProblem SolvingPublic HealthQuality of lifeReportingResearchResearch DesignRiskRoleShort-Term MemorySocietiesTestingTimeWomancancer therapychemotherapycognitive controlcognitive functioncognitive reservedisabilityexecutive functiongray matterhigh riskimprovedinnovationmalignant breast neoplasmmild cognitive impairmentneuroimagingneuropsychologicalolder womenpredictive modelingprocessing speedprospectivepublic health relevancesatisfactionskillstherapy developmenttime intervalwhite matter
中文摘要
描述(由申请人提供):患有乳腺癌的女性,特别是那些年龄较大并接受辅助化疗的女性,患轻度认知障碍(MCI)的风险显著增加。我们先前的研究表明,在癌症治疗结束后很长一段时间内,持续和进展性的MCI。这种认知障碍往往涉及记忆和执行功能(即多任务、解决问题)方面的困难,这干扰了日常生活技能,降低了生活质量。默认模式网络(DMN)是对正常认知功能非常重要的大脑回路。随着年龄的增长,DMN脑区之间的联系会自然而然地减弱。DMN功能连接性已被证明是非癌症人群中MCI的一个非常有前途的神经成像生物标志物。DMN功能连接的中断与转化为痴呆症密切相关,甚至被证明是神经退行性变的其他生物标志物的先兆。之前的研究,包括我们自己的研究,显示乳腺癌化疗后DMN区域萎缩和连接这些区域的白质通路受损。我们认为化疗会加速DMN的下降,导致乳腺癌后MCI的发生率增加。然而,到目前为止,还没有研究直接评估乳腺癌中DMN或其与MCI的关系。因此,这项拟议研究的具体目标是:1)确定接受化疗的老年乳腺癌受试者发生MCI的频率;2)确定接受化疗的老年乳腺癌受试者的DMN神经成像生物标志物;以及3)开发预测这一人群易患MCI的模型。我们将通过将认知功能、情绪和行为的纵向多维神经心理学评估与先进的非侵入性多模式磁共振成像技术和APOE基因分型相结合来实现这些目标。我们将在化疗前、化疗后1个月和化疗后6个月评估55名原发性乳腺癌患者。我们将把接受化疗的组与55名未接受化疗的乳腺癌女性和55名健康女性进行比较,这些女性在重要的人口统计学和临床因素上都是匹配的。所有小组都将以相同的时间间隔进行评估。我们将强调对记忆和执行功能以及DMN功能连接性的评估。我们将把临床、人口统计学、精神病学(如抑郁、疲劳)和遗传因素(如APOE)与DMN连接纳入我们的MCI预测模型。识别与化疗相关的MCI背后的神经成像生物标记物将改善对神经退行性变风险最高的个人的识别,并有助于开发针对这些损伤的治疗方法。考虑到老龄化社会以及乳腺癌和MCI发病率和易感性的增加,这一点至关重要。
英文摘要
DESCRIPTION (provided by applicant): Women with breast cancer, particularly those who are older and who receive adjuvant chemotherapy, are at significantly increased risk for mild cognitive impairment (MCI). Our previous research shows persistent and progressive MCI long after cancer treatment has ended. This cognitive impairment tends to involve difficulties with memory and executive function (i.e. multi-tasking, problem solving) that interfere with daily livin skills and reduce quality of life. The default mode network (DMN) is a brain circuit important for normal cognitive function. The connections between the DMN brain regions tend to naturally decrease in strength as we age. DMN functional connectivity has been demonstrated to be a highly promising neuroimaging biomarker of MCI in non-cancer populations. Disruption of DMN functional connectivity is strongly associated with conversion to dementia and has even been show to precede other biomarkers of neurodegeneration. Previous studies, including our own, show atrophy of DMN regions and damage to the white matter pathways that connect these regions following breast cancer chemotherapy. We believe that chemotherapy treatment accelerates DMN decline resulting in increased frequency of MCI following breast cancer. However, no studies to date have directly assessed the DMN or its relationship to MCI in breast cancer. The specific aims of the proposed study are therefore to 1) determine the frequency of MCI in older breast cancer subjects who receive chemotherapy, 2) identify DMN neuroimaging biomarkers in older breast cancer subjects treated with chemotherapy, and 3) develop models that predict vulnerability to MCI in this population. We will accomplish these aims by integrating longitudinal multidimensional neuropsychological assessments of cognitive function, mood and behavior with advanced, non-invasive multimodal magnetic resonance imaging techniques and APOE genotyping. We will evaluate 55 women with primary breast cancer prior to chemotherapy, one month following chemotherapy and six months following chemotherapy. We will compare the chemotherapy-treated group to 55 women with breast cancer who do not receive chemotherapy and 55 healthy females, all matched on important demographic and clinical factors. All groups will be assessed at the same time intervals. We will emphasize the assessment of memory and executive function as well as DMN functional connectivity. We will incorporate clinical, demographic, psychiatric (e.g. depression, fatigue) and genetic (e.g. APOE) factors with DMN connectivity into our predictive models of MCI. Identifying neuroimaging biomarkers underlying chemotherapy-related MCI will improve identification of individuals at highest risk for neurodegeneration and aid the development of treatments for these impairments. This is of critical importance given an aging society and the increased incidence of and vulnerability to both breast cancer and MCI.
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