Optimization of Clinical and Research PET Imaging
Optimization of Clinical and Research PET Imaging
批准号:
10580601
负责人:
Suleman Surti
金额:
$49.55万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-04-01 至 2024-12-31
关键词:
AlgorithmsAreaBedsClinicalComplexComputers and Advanced InstrumentationDataDetectionDiagnosisDiagnosticDiagnostic Neoplasm StagingDoseEvaluationFutureGenerationsGoalsHumanImageImaging DeviceInjectionsLeadLesionMeasuresMethodologyModernizationMonitorMorphologic artifactsMotionMovementNoiseOncologyPET/CT scanPatient MonitoringPatient imagingPatientsPerformancePlayPositioning AttributePositron-Emission TomographyProtocols documentationRadiation Dose UnitRadiation exposureReceiver Operating CharacteristicsResearchResolutionRoleScanningSignal TransductionStudy modelsSystemTestingTimeTumor BiologyVendorVisionWorkX-Ray Computed Tomographyclinical imagingclinically relevantcomparativecostdesignhigh riskimage reconstructionimaging capabilitiesimaging modalityimprovedmolecular imagingnovelpersonalized medicineprecision medicinereconstructionscreeningstatisticssurveillance studytooltreatment responsetumoruptake
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The goal of this project is to quantitatively demonstrate improved clinical performance of the latest
PET/CT systems using task-specific image quality measures in realistic patient studies These results will
be correlated to the performance of simpler metrics that are easier to calculate. Our objective is to either
guide a reduction in injected activity or imaging time on these latest systems without sacrificing existing
clinical capabilities or to demonstrate new clinical capabilities. The evaluation will be performed as a
function of scanner design, image reconstruction, and patient habitus in order to maintain good clinical
performance over all patients. Currently, PET imaging protocols are designed based on imaging at or
near the peak noise equivalent counts (NEC). While the performance of these scanners has improved,
the patient injection protocols have remained constant while the imaging time is reduced. Also, while
NEC gives an estimate of the general pixel signal-to-noise ratio (SNR), its relation to clinically relevant
metrics is not obvious especially since it does not include the effects of spatial and TOF resolution, and
image reconstruction. In this project we perform a clinically realistic study replicating two tasks in
oncology: (i) lesion detection and localization common in diagnostic PET, and (ii) monitoring tumor
response to therapy with multiple scans. Our embed lesions in clinical patient data prior to image
reconstruction, thereby providing a ground-truth for comparison. The proposed work is accomplished
through the following specific aims: (1) Develop and evaluate a new simplified NEC metric for optimizing
PET images for clinically relevant tasks that includes spatial and TOF resolution effects and test its
correlation to a task-specific metric, (2) Perform a comprehensive human observer study for lesion
detection and localization, and (3) Perform a ROC study that models tumor response to therapy. In the
short term, the results of this work will quantitatively demonstrate improved clinical performance with the
latest PET/CT (commercial systems as well as PennPET Explorer scanner), thereby allowing shorter
imaging times and/or reduced injected activity. Correlation of the task-specific metric results to simplified
imaging metrics will also provide an important tool for future PET system design and image
reconstruction evaluation and optimization where complex, task-specific evaluations will not be practical.
Clinically, demonstration of good performance with very short scan times will open the possibility of
breath-hold imaging with no motion artifacts. Our results will also enable an expansion of PET imaging
into new clinical areas where patient radiation exposure is a limiting concern in the use of this molecular
imaging modality. We envision serial patient imaging for monitoring treatment response, as well as
screening/surveillance studies in high-risk patients, 2 areas of immediate relevance.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Data Driven Background Estimation in PET Using Event Energy Information
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批准号:10644161
-
项目类别:
-
资助金额:$57.86万
-
财政年份:2022
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负责人:Suleman Surti
-
依托单位:
Optimization of Clinical and Research PET Imaging
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批准号:10322759
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项目类别:
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资助金额:$49.55万
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财政年份:2020
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负责人:Suleman Surti
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依托单位:
Energy-Based Scatter Estimation Algorithm for Accurate Quantitative PET Imaging
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批准号:9975773
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项目类别:
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负责人:Suleman Surti
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依托单位:
High Performance, Quantitative Breast PET Scanner Integrated with Tomosynthesis
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批准号:9896791
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项目类别:
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财政年份:2016
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负责人:Suleman Surti
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依托单位:
IEEE Medical Imaging Conference
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批准号:9122828
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项目类别:
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资助金额:$1.0万
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财政年份:2016
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负责人:Suleman Surti
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依托单位:
High Performance, Quantitative Breast PET Scanner Integrated with Tomosynthesis
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批准号:9236176
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项目类别:
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资助金额:$67.98万
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财政年份:2016
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负责人:Suleman Surti
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依托单位:
A Time-of-Flight PET scanner for dedicated breast imaging
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批准号:7915241
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项目类别:
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资助金额:$41.42万
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财政年份:2009
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负责人:Suleman Surti
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依托单位:
A Time-of-Flight PET scanner for dedicated breast imaging
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批准号:8101195
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项目类别:
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资助金额:$35.27万
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财政年份:2009
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负责人:Suleman Surti
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依托单位:
A Time-of-Flight PET scanner for dedicated breast imaging
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批准号:7741517
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项目类别:
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资助金额:$31.35万
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财政年份:2009
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负责人:Suleman Surti
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依托单位:
A Time-of-Flight PET scanner for dedicated breast imaging
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批准号:8286967
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项目类别:
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资助金额:$38.18万
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财政年份:2009
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负责人:Suleman Surti
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依托单位:
Thick scintillation detector with continuous positioning & DOI capability for PET
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批准号:7359273
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项目类别:
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资助金额:$28.59万
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财政年份:2007
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负责人:Suleman Surti
-
依托单位:
Thick scintillation detector with continuous positioning & DOI capability for PET
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批准号:7492084
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项目类别:
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资助金额:$19.29万
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财政年份:2007
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负责人:Suleman Surti
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依托单位:
国内基金
海外基金
层出镰刀菌氮代谢调控因子AreA 介导伏马菌素 FB1 生物合成的作用机理
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批准号:2021JJ40433
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项目类别:省市级项目
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资助金额:--
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批准年份:2021
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负责人:孙磊
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依托单位:
寄主诱导梢腐病菌AreA和CYP51基因沉默增强甘蔗抗病性机制解析
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批准号:32001603
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项目类别:青年科学基金项目
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资助金额:24.0万元
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批准年份:2020
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负责人:段真珍
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依托单位:
AREA国际经济模型的移植.改进和应用
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批准号:18870435
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项目类别:面上项目
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资助金额:2.0万元
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批准年份:1988
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负责人:史树中
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依托单位: