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:
9975109
负责人:
Sarah Jane Nyante
金额:
$58.57万
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-DimensionalAddressAnxietyAreaAutomobile DrivingBenignBiologicalBiological FactorsBiological MarkersBiological ProcessBiologyBiopsyBiopsy SpecimenBiosensorBreastBreast Cancer DetectionBreast Cancer PatientBreast Cancer PreventionBreast Cancer Risk FactorBreast CarcinogenesisBreast DiseasesBreast biopsyCancer BurdenCancer PrognosisCharacteristicsCommunitiesComplementComplexCross-Sectional StudiesDataDevelopmentDimensionsElectronic Health RecordEstradiolEstrogen AntagonistsEstrogen TherapyEstrogensEstroneFoundationsFractalsGoalsHealthHealthcare SystemsHeterogeneityHistologicHistologyHormonalIndividualKnowledgeLengthLobularMalignant NeoplasmsMammographic DensityMammographyMeasurementMeasuresMedical Care CostsMenopausal StatusMethodsMissionMonitorMorphologyNational Cancer InstituteNewly DiagnosedNon-MalignantNorth CarolinaOutcomePathway interactionsPatientsPatternPopulationPreventionPropertyPublic HealthRadiology SpecialtyRecording of previous eventsReportingReproducibilityResearchRiskRoleRunningStructureTestingTextureTimeTissuesUniversitiesUnnecessary ProceduresUrineVariantWomanWomen&aposs Groupbasebreast 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
乳腺成分是一种潜在的乳腺生物标志物,但其实用性受到测量方法的限制。
视觉评估的定性尺度捕捉乳房内异质性,但主观和缺乏
再现性相比之下,全球乳腺密度的定量自动评估是可重复的,但
不包含关于乳房内变化的信息。这两种方法的局限性都可以克服
与实质纹理特征的测量。纹理特征是一种定量的度量,
乳房图像中像素密度的复杂特征,范围从描述性统计到高阶
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,人们对驱动这一过程的生物学机制知之甚少。
风险关系。本研究的目的是确定与脑实质相关的生物学过程,
纹理特征基本原理是,纹理特征反映特定生物学特征的直接证据
这些特性将为纹理特征作为乳腺癌的动态标记物的发展提供基础
风险和预后。这项研究将追求三个目标。使用病例对照分析,目标1将确定
与新诊断的女性乳腺癌独立相关的纹理特征
参加乳腺癌筛查。目标2将评估如何纹理特征,与
通过(i)纹理特征的横截面分析,
和15个尿雌激素和雌激素代谢产物,和(ii)纵向纹理变化的分析
抗雌激素治疗的乳腺癌患者的特征。目标3将评估
纹理特征与乳腺组织学特征(组织成分,良性)之间的相关性
乳腺疾病/LCIS,小叶复旧的措施)的妇女与良性活检。分析将
利用现有的乳房X线照片、活检标本和参与妇女的电子健康记录,
在北卡罗来纳州大学进行乳房X线摄影;将前瞻性收集尿液。纹理特征
将使用一种新的基于网格的网格方法进行测量,该方法由该研究的成员开发和验证
该团队允许来自整个乳房的信息为纹理测量提供信息。这些分析
将建立:基于网格的纹理特征和乳腺癌之间的关系的大小
在一般筛查人群中(目标1);纹理特征在多大程度上可以充当生物传感器
乳腺雌激素/抗雌激素活性(目标2);以及纹理特征是否可以作为放射学检查的指标。
已知与乳腺癌风险相关的组织学特征的替代物(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,
这些新用途有可能确定新的预防目标,
对有乳腺癌风险和正在接受乳腺癌治疗的妇女进行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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Understanding the biological basis for the association between parenchymal texture features and breast cancer risk
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批准号:10697306
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项目类别:
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资助金额:$48.55万
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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: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:
海外基金