Breast Cancer Risk Stratification with Resonant Electrical Impedance Spectroscopy
Breast Cancer Risk Stratification with Resonant Electrical Impedance Spectroscopy
批准号:
7804524
负责人:
DAVID GUR
金额:
$41.03万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-04-01 至 2012-03-31
关键词:
AddressAgeAlgorithmsBackBiological Neural NetworksBiopsyBreastBreast Cancer DetectionBreast Cancer Early DetectionCategoriesClassificationClinicalDataData SetDevicesDiagnosticDiagnostic ImagingDiagnostic ProcedureDigital MammographyDiseaseDropsEffectivenessEquipmentEvaluationExposure toFoundationsFrequenciesGeneral PopulationGenetic ProgrammingGoldHigh Risk WomanHumanImageImaging technologyIncidenceInjection of therapeutic agentMachine LearningMagnetic Resonance ImagingMalignant NeoplasmsMammary Gland ParenchymaMammographyMeasurementMeasuresMedicalMethodologyModalityModificationNoiseOffice VisitsPalpablePerformancePersonsPhasePlaguePopulationPremenopauseProceduresPropertyProspective StudiesPublic HealthRadiationRecommendationRecruitment ActivityRiskRoleScanningScreening procedureSensitivity and SpecificitySignal TransductionSiteSkinSpecificitySpectrum AnalysisStratificationSubgroupSurfaceSystemTechniquesTechnologyTestingTissuesTrainingWestern WorldWomanWomen&aposs Groupage groupbasebreast densitycancer riskcostdesignelectric impedancefollow-uphigh riskimaging modalityimprovedin vivomalignant breast neoplasmnovel strategiesolder womenpatient populationprototypesensortool
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Although risk for developing breast cancer at an earlier age is low in a substantial fraction of person-years lost it is attributed to women under the age of 40 who die from this disease. Unfortunately, screening mammography, the "gold standard" and accepted practice over the age of 40 for breast cancer detection, performs poorly in younger women and combined with radiation risk and expected low yield resulted in the recommendation that annual screening in the general population is not recommended below this age. Alternative imaging modalities exist (e.g. MRI, US), however, these techniques are not being used for this purpose for a variety of reasons. It would greatly facilitate breast cancer detection in younger women if an inexpensive, easy to use, widely available technology was available to pre-screen women and determine who would most likely benefit from more comprehensive imaging based studies. Currently, the only generally used screening tool in young women is Clinical Breast Exam (CBE). However, CBE has low sensitivity, high false- positive rate and is examiner dependent. Electrical Impedance Spectroscopy (EIS) is a promising technology for fulfilling a pre-screening risk identification role as it relies on relatively inexpensive equipment that could be widely disseminated to practitioners' offices and it has demonstrated some effectiveness in detecting breast cancer regardless of age or breast density. Unfortunately, EIS technologies have demonstrated a relatively low sensitivity (~ 25 - 35%) when a high specificity (>90%) is required. Recently a new approach to EIS measurements has been developed and used quite successfully in non-medical applications. This new approach measures shifts in impedance near the resonant frequency when tissue is made a part of an RLC electric circuit. We refer to this new approach as Resonant Electrical Impedance Spectroscopy (REIS). The sensitivity of EIS near the resonant frequency is extremely high and we believe that using this approach (REIS) a much greater diagnostic performance can be achieved than was previously obtainable with EIS. In the R21 phase of this study we will build a prototype REIS device for rapidly evaluating (less than 10 minues) the breast and demonstrate feasibility for pre-screening women with the REIS device to determine who would benefit from a diagnostic imaging workup. This is not a breast cancer detection device but rather a risk stratification approach. Namely, the ultimate objective is to develop and test an approach that would segment the younger women population (< 40 years old) into two groups. One (REIS negative) that is expected to have normal risk of having breast cancer and the other (REIS positive) which identifies a group of women in which the risk of having breast cancer is substantially higher than in older women (40 - 49 years old) who are currently routinely screened. In the R33 phase a much larger patient population will be recruited and will be used to optimize the classification algorithm. Comparisons will be made with existing EIS technology. In this application we are proposing building and evaluating a device for identifying pre-menopausal women who are at increased risk for breast cancer and would thus benefit from an imaging based evaluation of the breast. This would be achieved using a low cost, safe technology that could be used during routine office visits of young women who are not screened with mammography. If successful, this proposal will have a large public health impact via increased early detection of breast cancer.
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