Understanding the biological basis for the association between parenchymal texture features and breast cancer risk
Understanding the biological basis for the association between parenchymal texture features and breast cancer risk
批准号:
10697306
负责人:
Sarah Jane Nyante
金额:
$48.55万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2024-08-31
关键词:
3-DimensionalAnxietyAreaAutomobile DrivingBenignBiologicalBiological FactorsBiological MarkersBiological ProcessBiologyBiopsyBiopsy SpecimenBiosensorBreastBreast Cancer DetectionBreast Cancer PatientBreast Cancer PreventionBreast Cancer Risk FactorBreast CarcinogenesisBreast DiseasesBreast biopsyCancer BurdenCancer PrognosisCharacteristicsClassificationCommunitiesComplementComplexCross-Sectional StudiesDataDevelopmentDimensionsElectronic Health RecordEstradiolEstrogen AntagonistsEstrogen TherapyEstrogensEstroneFoundationsFractalsGoalsHealthHealthcare SystemsHeterogeneityHistologicHistologyHormonalIndividualKnowledgeLengthLobularMalignant NeoplasmsMammographic DensityMammographyMeasurementMeasuresMedical Care CostsMenopausal StatusMethodsMissionMonitorMorphologyNational Cancer InstituteNewly DiagnosedNon-MalignantNorth CarolinaOutcomePathway interactionsPatientsPatternPopulationPreventionPropertyPublic HealthRadiology SpecialtyRecording of previous eventsReportingReproducibilityResearchRiskRoleRunningStructureTestingTextureTimeTissuesUniversitiesUnnecessary ProceduresUrineVariantVisualWomanWomen&aposs Groupbreast cancer diagnosisbreast densitybreast imagingbreast lesioncase controlclinical trial participantdensityevidence baseimprovedinsightlobular breast carcinoma in situlongitudinal analysismalignant breast neoplasmmammography registrymembermultidisciplinarynovelprecision medicineprospectiveradiomicsresponsescreeningspatial relationshipstandard carestatisticstooltreatment responseunnecessary treatmenturinary
中文摘要
乳房成分是一种潜在的乳房生物标志物,但其应用受到测量方法的限制。
肉眼评估的定性尺度反映了乳房内部的异质性,但具有主观性和缺乏
再现性。相比之下,全球乳房密度的定量自动评估是可重现的,但
不包含有关乳房内变异的信息。这两种方法的局限性都是可以克服的
与测量的实质纹理特征。纹理特征是一种量化度量,用于估计
乳房图像中像素密度的复杂特征,从描述性统计到更高阶
描述空间关系和结构模式的统计数据。先前的研究表明,纹理特征
独立预测乳腺癌风险。然而,人们对导致这一现象的生物学机制知之甚少。
风险关系。本研究的目的是确定与实质相关的生物学过程。
纹理特征。其基本原理是质地特征反映特定生物的直接证据
这些特性将为开发纹理特征作为乳腺癌的动态标记物提供基础
风险和预后。本研究将追求三个目标。使用病例对照分析,目标1将确定
与女性新诊断乳腺癌独立相关的纹理特征
参加乳腺癌筛查。目标2将评估如何将纹理特征与
这一人群中的乳腺癌随着雌激素水平的变化而变化,通过(I)质地特征的横断面分析
和15种尿雌激素和雌激素代谢物,以及(Ii)质地纵向变化的分析
接受抗雌激素治疗的乳腺癌患者的特点。AIM 3将评估
质地特征与乳腺组织学特征(组织成分、良性
乳房疾病/乳房疾病/乳房小叶退化的测量)。分析将
利用现有的乳房X光照片、活组织检查样本和参与研究的妇女的电子健康记录
在北卡罗来纳大学的乳房X光检查中,尿液将被前瞻性地收集。纹理特征
将使用一种新的基于网格的方法进行测量,该方法由研究成员开发和验证
允许来自整个乳房的信息来通知质地测量的团队。这些分析
将建立:基于网格的纹理特征与乳腺癌之间的关系的大小
在一般筛查人群中(目标1);纹理特征可作为生物传感器的程度
乳房雌激素/抗雌激素活性(目标2);以及质地特征是否可以作为放射学检查
替代已知与乳腺癌风险相关的组织学特征(目标3)。这些
结果将阐明实质纹理特征作为乳腺癌风险预测因子的潜在作用和
治疗反应;这种新用途有可能确定新的预防目标并减少
对于有乳腺癌风险和正在接受治疗的妇女来说,不必要的程序和治疗。
英文摘要
Breast composition is a potential breast biomarker, but its utility has been limited by measurement methods.
Visually-assessed qualitative scales capture within-breast heterogeneity but are subjective and lack
reproducibility. In contrast, quantitative automated assessments of global breast density are reproducible, but
contain no information about within-breast variation. Limitations of both of these approaches can be overcome
with the measurement of parenchymal texture features. Texture features are quantitative measures that estimate
complex characteristics of pixel density in the breast image, ranging from descriptive statistics to higher order
statistics that describe spatial relationships and structural patterns. Prior studies have shown that texture features
independently predict breast cancer risk. However, little is known about the biological mechanisms driving that
risk relationship. The objective of this study is to identify the biological processes associated with parenchymal
texture features. The rationale is that direct evidence that texture features reflect specific biological
properties will provide the basis for development of texture features as a dynamic marker of breast cancer
risk and prognosis. This study will pursue three aims. Using a case-control analysis, Aim 1 will identify the
texture features that are independently associated with newly-diagnosed breast cancer among women
attending breast cancer screening. Aim 2 will evaluate how the texture features that were associated with
breast cancer in this population vary with estrogen levels, through (i) cross-sectional analysis of texture features
and 15 urinary estrogens and estrogen metabolites, and (ii) analyses of longitudinal change in texture
features among breast cancer patients treated with anti-estrogenic therapy. Aim 3 will evaluate
associations between texture features and breast histologic characteristics (tissue composition, benign
breast disease/LCIS, measures of lobular involution) among women with a benign biopsy. Analyses will
draw on existing mammograms, biopsy specimens, and electronic health records from women participating
in mammography at the University of North Carolina; urine will be collected prospectively. Texture features
will be measured using a novel lattice-based grid method developed and validated by members of the study
team that allows information from the whole breast to inform the texture measurements. These analyses
will establish: the magnitude of the relationship between lattice-based texture features and breast cancer
in a general screening population (Aim 1); the extent to which texture features may act as biosensors of
breast estrogen/anti-estrogen activity (Aim 2); and whether texture features can serve as a radiologic
surrogate of histologic characteristics that have known associations with breast cancer risk (Aim 3). These
results will clarify the potential role of parenchymal texture features as predictors of breast cancer risk and
therapeutic response; such new uses have the potential to identify new prevention targets and reduce
unnecessary procedures and treatments for women at risk for and being treated for breast cancer.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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批准号:10359555
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批准号:10544316
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批准号:10589922
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Understanding the biological basis for the association between parenchymal texture features and breast cancer risk
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批准号:10241446
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项目类别:
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资助金额:$60.47万
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财政年份:2019
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负责人:Sarah Jane Nyante
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依托单位:
Understanding the biological basis for the association between parenchymal texture features and breast cancer risk
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批准号:10472712
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项目类别:
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资助金额:$50.31万
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财政年份:2019
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负责人:Sarah Jane Nyante
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依托单位:
Understanding the biological basis for the association between parenchymal texture features and breast cancer risk
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批准号:9975109
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项目类别:
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资助金额:$58.57万
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财政年份:2019
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负责人:Sarah Jane Nyante
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依托单位:
海外基金