A TOF, DOI, MRI compatible PET detector to support sub-millimeter neuroPET imaging
A TOF, DOI, MRI compatible PET detector to support sub-millimeter neuroPET imaging
批准号:
9791188
负责人:
Sergei Dolinsky
金额:
$53.7万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-25 至 2021-07-31
关键词:
AgingAlgorithmsAreaBenchmarkingBrainBrain imagingClinicalCrystallizationDataDetectionDevelopmentDevicesDimensionsDiseaseElectronicsElementsEvaluationEventFunctional ImagingGeometryGoalsGuidelinesHumanImageImaging technologyIndividualInvestigationLaboratory ResearchLeadLengthMachine LearningMagnetic Resonance ImagingMathematicsMeasurementMeasuresMethodsModelingMonte Carlo MethodMultimodal ImagingNeurosciencesOpticsOutcomePerformancePhysiologic pulsePositioning AttributePositron-Emission TomographyPropertyResearchResearch PersonnelResolutionRoleRunningSideSiliconSurfaceSystemTechnologyTestingTimeUnited States National Institutes of HealthUniversitiesVendorWashingtonWorkbasebrain researchdesigndetectordigitalimaging detectorimaging systemimprovedinnovative neurotechnologiesinnovative technologieslearning strategyneuroimagingnext generationnoveloperationprototypetemporal measurementtool
中文摘要
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英文摘要
Abstract
The overall goal of this research is to develop next generation positron emission tomography (PET) detector
technology to support non-invasive, quantitative brain imaging at spatial and temporal resolutions currently not
achievable with human neuro-PET systems. The developed PET detector technology will also be compatible
with operation in an MRI system. The proposed research is targeted to the NIH Brain Research through
Advancing Innovative Neurotechnologies (BRAIN) initiative. Human brain imaging with PET/MRI will be an
essential tool in neuroscience studies to "Develop innovative technologies to understand the human brain and
treat its disorders; create and support integrated brain research networks." The key advancement that we
introduce is a PET detector with <100 psec time-of-flight (TOF) PET coincidence resolution, <2 mm continuous
depth of interaction (DOI) positioning and intrinsic detector spatial resolution to support <1 mm PET image
resolution throughout the system imaging field of view (FOV). Detector modules have been designed that
individually achieve these performance metrics; however, no detector module has been designed that supports
all of them. To make disruptive advancements in neuro-imaging using PET, one must push the image spatial
resolution (i.e., currently 2-3 mm image resolution) as well as coincidence timing resolution and also be MRI
compatible. The impact of this project is that we will advance the state of the art in all of these critical
performance areas. We will achieve these goals by first understanding the role that different PET detector
performance parameters have on task-based figures of merit for neuroPET imaging. We will investigate how
both TOF and image resolution impact figure of merit performance for estimation, detection and
characterization imaging tasks. Monte Carlo simulation will be used along with both object-based (i.e.,
mathematical) and anthropomorphic digital phantoms. Next we will optimize SiPM device selection, electronics
and detector geometry for <100 psec TOF coincidence timing, 1 mm intrinsic spatial resolution and <2 mm DOI
positioning resolution. We will build and characterize a prototype PET detector module utilizing a novel dual-
sided slat crystal detector design. To advance coincidence timing performance we will investigate the use of
machine learning to estimate the arrival time of detected events. Finally, we will optimize the detector design
for MRI compatibility. We will fully test and characterize performance of our prototype detector on the benchtop
and in a MRI scanner while running clinical MRI pulse sequences. At the end of this developmental project we
will be in position to build a state of the art, MRI compatible, TOF, DOI PET imaging system.
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