Automatic Quantification and Labeling of Cerebral Microbleeds, Oxygen Saturation and Sources of Abnormal Susceptibility
Automatic Quantification and Labeling of Cerebral Microbleeds, Oxygen Saturation and Sources of Abnormal Susceptibility
批准号:
10026456
负责人:
Ewart Mark Haacke
金额:
$66.71万
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:
2019-08-01 至 2022-01-31
关键词:
3-DimensionalAddressAffectAlgorithmsAlzheimer&aposs DiseaseArteriogramArteriosclerosisBasal GangliaBlood VesselsBrainBrain hemorrhageBusinessesCerebral Amyloid AngiopathyCerebral hemisphere hemorrhageClinicalComputer softwareConsumptionDataData SetDementiaDetectionDevelopmentDiagnosisDiffuse Axonal InjuryDiseaseFeedbackGoalsHemorrhageHypertensionImageImage AnalysisImpaired cognitionInfarctionIronLabelLeadLinkLocationMagnetic ResonanceMagnetic Resonance ImagingMagnetismMapsMarriageMeasuresMethodsModelingMonitorMultiple SclerosisNeurodegenerative DisordersNeuropsychologyOutcomeOxygenPatient CarePatient-Focused OutcomesPatientsPerformancePerfusionPhasePlayPositioning AttributePredispositionPrevalenceProtocols documentationProtonsPublished CommentReportingRoleSamplingSiteSourceSpatial DistributionStrokeTBI PatientsTechniquesTestingThalamic structureThrombosisTimeTrainingTraumatic Brain InjuryVascular DementiaVeinsVenousbasecerebral microbleedscerebral veincomputerized data processingcontrast imagingdeep learningdensitydesignimage processingimprovedinnovationmild traumatic brain injurynervous system disorderneurovascularprototypequantitative imagingradiologiststroke risktooltreatment planninguser friendly software
中文摘要
摘要
脑微出血(CMBS)的检测、定位和定量在脑血管疾病中起着重要作用
神经退行性疾病尤其是血管退行性疾病的诊断和制定合适的治疗方案
痴呆症(VAD)。到目前为止,评估CMBS是耗时、不准确的,有时甚至是不可能的。我们
建议通过开发我们的软件“qSPIN”来缓解这些问题,该软件将提供快速且易于使用的
方法:1)CMBS和静脉的自动识别,2)CMBS的自动量化,3)自动
静脉血氧饱和度的量化,以及4)创建一个用户友好的练习软件
放射科医生。MRI的最新发展为研究CMBS的作用提供了新的手段
阿尔茨海默病(AD)、血管性痴呆(VAD)、中风和创伤性疾病中的静脉异常
脑损伤(TBI)。磁化率加权成像(SWI)已被证明是一种强大的检测工具
CMBS和定量磁化率图(QSM)可用于测量血氧饱和度的变化。
了解有多少CMBS可以预测VaD的发病,确定抗血小板治疗是否在
对于脑外伤患者,应该使用卒中,并与神经心理结果相关。我们的最新版本
多回声SWI的应用使得同时获得动脉造影和静脉造影成为可能。氧
饱和度也可以用来监测脑血流的变化,延长中风的治疗窗口。
目前,大多数放射科医生和技术人员没有时间进行如此详细的定量
因此它不是在临床上进行的。我们的qSPIN软件将提供这一定量数据。使用
CMBS或静脉异常的数目、大小和位置,才有可能得到更好的诊断。我们的
集团在解决这一问题方面处于独特的地位,开发了许多这样的技术。新奇之处
我们的方法是结合SWI、QSM、阶段和深度学习技术来检测这些血管
和功能异常。为了实现这项提议的目标,我们将开发用户友好的软件
这包含了来自SWI和QSM的所有成像信息,以标记CMBS。我们还将提供
Talairach中的CMBS使用模板数据集进行协调。最后,我们将全面了解
神经退行性疾病患者CMBS患病率、血氧饱和度异常及其部位
这将改善诊断,并可能改变他们的治疗方法。
英文摘要
ABSTRACT
The detection, localization and quantification of cerebral microbleeds (CMBs) plays an important role in
diagnosing and establishing appropriate treatment plans in neurodegenerative diseases specifically in vascular
dementia (VaD). To date, evaluating CMBs is time consuming, inaccurate and sometimes not possible. We
propose to mitigate these problems by developing our software, “qSPIN”, that will provide fast and easy-to-use
methods for: 1) automatic identification of CMBs and veins, 2) automatic quantification of CMBs, 3) automatic
quantification of oxygen saturation in veins, and 4) creation of a user-friendly software for the practicing
radiologist. Recent developments in MRI have provided a new means by which to study the role of CMBs and
venous abnormalities in neurological diseases such as Alzheimer’s Disease (AD), VaD, stroke and traumatic
brain injury (TBI). Susceptibility weighted imaging (SWI) has proven to be a powerful tool by which to detect
CMBs and quantitative susceptibility mapping (QSM) can be used to measure changes in oxygen saturation.
Knowing how many CMBs there are can predict the onset of VaD, determine whether anti-platelet therapy in
stroke should be used, and correlate with neuropsychological outcome for patients with TBI. Our recent version
of multi-echo SWI makes it possible to obtain both an arteriogram and a venogram simultaneously. Oxygen
saturation can also be used to monitor perfusion changes and extend the window of treatment in stroke.
Currently, most radiologists and technologists do not have time to perform such detailed quantitative
processing and thus it is not being done clinically. Our qSPIN software will provide this quantitative data. With
the number, size, and location of CMBs or venous abnormalities, a better diagnosis would be possible. Our
group is uniquely positioned to address this problem having developed many of these techniques. The novelty
of our approach is the marriage of SWI, QSM, STAGE and deep learning techniques to detect these vascular
and functional abnormalities. To accomplish the goals of this proposal, we will develop user friendly software
that incorporates all imaging information from SWI and QSM to label CMBs. We will also provide the location of
the CMBs in Talairach coordinates using a template dataset. In the end, we will have a complete picture of the
prevalence of CMBs, abnormal oxygen saturation and their locations in patients with neurodegenerative disease
that will improve diagnosis and potentially change their treatment.
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会议论文
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