Image Quality Improvement and Performance Assessment of Dedicated Breast CT
Image Quality Improvement and Performance Assessment of Dedicated Breast CT
批准号:
9899937
负责人:
Ioannis Sechopoulos
金额:
$19.66万
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-04-01 至 2023-03-31
关键词:
3-DimensionalAlgorithmsAmerican Cancer SocietyAnatomyBiopsyBreastBreast Cancer DetectionBreast Cancer Early DetectionBreast Cancer PatientBreast MicrocalcificationCancer DiagnosticsCharacteristicsClinicalClinical TrialsContrast MediaDevelopmentDiagnosisDiagnosticDiagnostic ProcedureDiseaseEarly DiagnosisEnsureHealthcareImageImage AnalysisImaging technologyInformation DistributionInjectionsKineticsLesionMalignant NeoplasmsMammographyMethodsModalityMorphologic artifactsNatureNeoadjuvant TherapyPatient imagingPatientsPerformancePhysiciansProbabilityProcessRadiopharmaceuticalsResolutionRoentgen RaysShapesSignal TransductionSurvival RateTestingThree-Dimensional ImageTimeTissuesUltrasonographyVisualizationWomanWorkX-Ray Computed Tomographybasebreast cancer diagnosisbreast densitybreast exambreast imagingcancer imagingchemotherapyclinical applicationclinical diagnosticsclinical efficacyclinical imagingcontrast enhanceddensitydetectordiagnostic accuracydigital imagingimage processingimage reconstructionimaging capabilitiesimaging modalityimaging studyimprovedmalignant breast neoplasmnovelnovel imaging technologyprospectivepublic health relevancequantitative imagingradiologistreconstructionresponsetomographytomosynthesistumortwo-dimensional
中文摘要
英文摘要
DESCRIPTION (provided by applicant): The diagnostic stage of early detection of breast cancer is currently far from perfect. With the current clinical imaging technology used for diagnostic work-up of suspicious lesions detected at breast cancer screening, approximately one out of six breast cancers are missed. This is in addition to the one out of six breast cancers already missed at the breast cancer screening stage. In addition, the rate of false positive diagnostic work-ups results in more than two out of three biopsies yielding a negative result. Clearly there is room for improvement in this very important clinical diagnostic procedure. Of the many novel imaging technologies being developed for breast cancer imaging, dedicated breast computed tomography (BCT) is one of very few that results in a true tomographic image of the breast with high contrast resolution and does not require the injection of a contrast agent or radiopharmaceutical. This makes it ideal for use as the frontline imaging technology for working up suspicious lesions detected during breast cancer screening or during clinical breast examination. In this project we propose to perform a prospective clinical trial to compare the accuracy of BCT to the current standard imaging technologies for diagnosis of breast cancer in patients with a suspicious lesion identified during breast cancer screening. To maximize the image quality of BCT we will apply to the BCT novel algorithms we have developed that result in more accurate, higher quality images with true quantitative characteristics. These algorithms involve the correction of the acquired BCT projections due to the presence of x-ray scatter, and a novel reconstruction algorithm that correctly represents the image acquisition process as one involving a spectrum of x-ray energy, rather than mono-energetic x-rays. Successful completion of this project will help introduce BCT to the clinical realm by characterizing its true potential or impact in the breast cancer diagnosis stage, where we expect it will result in fewer missed breast cancers and negative biopsies.
期刊论文(12)
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DOI:
10.1088/1361-6560/aae78d
发表时间:
2018-11-12
期刊:
Physics in medicine and biology
影响因子:
3.5
作者:
[Caballo M, Fedon C, Brombal L, Mann R, Longo R, Sechopoulos I]
通讯作者:
Sechopoulos I
DOI:
10.1016/j.compbiomed.2020.103629
发表时间:
2020-03
期刊:
Computers in biology and medicine
影响因子:
7.7
作者:
[]
通讯作者:
DOI:
10.1002/mp.12920
发表时间:
2018-06
期刊:
Medical physics
影响因子:
3.8
作者:
[Caballo M, Boone JM, Mann R, Sechopoulos I]
通讯作者:
Sechopoulos I
DOI:
10.1002/mp.13156
发表时间:
2018-10
期刊:
Medical physics
影响因子:
3.8
作者:
[Caballo M, Mann R, Sechopoulos I]
通讯作者:
Sechopoulos I
Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.
数字乳腺断层合成图像的深度学习重建,用于准确的乳腺密度和患者特定的辐射剂量估计。
DOI:
10.1016/j.media.2021.102061
发表时间:
2021
期刊:
Medical image analysis
影响因子:
10.9
作者:
[Teuwen,Jonas, Moriakov,Nikita, Fedon,Christian, Caballo,Marco, Reiser,Ingrid, Bakic,Pedrag, García,Eloy, Diaz,Oliver, Michielsen,Koen, Sechopoulos,Ioannis]
通讯作者:
Sechopoulos,Ioannis
共 7 条
Image Quality Improvement and Performance Assessment of Dedicated Breast CT
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批准号:8885449
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项目类别:
-
资助金额:$14.97万
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财政年份:2015
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负责人:Ioannis Sechopoulos
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依托单位:
Image Quality Improvement and Breast Compression Reduction in Breast Tomosynthesi
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批准号:8441522
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项目类别:
-
资助金额:$27.97万
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财政年份:2012
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负责人:Ioannis Sechopoulos
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依托单位:
Image Quality Improvement and Breast Compression Reduction in Breast Tomosynthesi
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批准号:8217892
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项目类别:
-
资助金额:$29.76万
-
财政年份:2012
-
负责人:Ioannis Sechopoulos
-
依托单位:
Image Quality Improvement and Breast Compression Reduction in Breast Tomosynthesi
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批准号:8616734
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项目类别:
-
资助金额:$28.86万
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财政年份:2012
-
负责人:Ioannis Sechopoulos
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依托单位:
海外基金