Ultrafast Quantitative pH MRI for Acute Ischemic Stroke Patients
用于急性缺血性中风患者的超快定量 pH MRI
基本信息
- 批准号:10328241
- 负责人:
- 金额:$ 38.48万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-02-15 至 2025-01-31
- 项目状态:未结题
- 来源:
- 关键词:3-DimensionalAcidosisAcuteAlteplaseAmidesAnaerobic BacteriaAnimal ModelAnimalsAreaBenignBrainBrain hemorrhageBrain imagingBrain regionCause of DeathChemicalsClinicClinicalClinical TrialsDecision MakingDiffusionDiffusion Magnetic Resonance ImagingExcisionFrequenciesGoalsHemorrhageHumanImageImaging TechniquesIncidenceInfarctionInterventionIntravenousIschemic PenumbraIschemic StrokeMagnetic Resonance ImagingMetabolismMethodsMorbidity - disease rateOutcomePatient SelectionPatientsPerfusionPhysiologic pulsePhysiologicalPopulationProbabilityProtocols documentationProtonsReperfusion TherapyResearch ProposalsRetrospective StudiesRiskScanningSelection for TreatmentsSensitivity and SpecificitySignal TransductionSpeedStrokeSymptomsTechniquesTestingTherapeuticTimeTissuesTrainingTranslatingTranslationsVariantVisualizationWorkacute strokebaseblood-brain barrier permeabilizationclinical translationdeep learningdeep learning algorithmdeep learning modeldesigndetection sensitivitydiagnostic accuracydisabilityendovascular thrombectomyhuman imagingimaging modalityimprovedmortalitymultimodalitynovelperfusion imagingpredict clinical outcomeradio frequencyrisk benefit ratiostandard carestroke patientstroke therapytargeted treatmentthrombolysistime usetreatment effect
项目摘要
ABSTRACT
Ischemic stroke is one of the leading causes of morbidity and mortality in the U.S. The goal of acute ischemic
stroke therapy is to salvage tissue that is at risk of infarction, but still viable, through the use of reperfusion
strategies. Current reperfusion therapies are limited by a tight time window for treatment and by the potential risk
of brain hemorrhage. Using this time-based approach, only a limited number of stroke patients are eligible for
treatment. Patients who present beyond the standard treatment time windows can benefit from therapy when
identified based on multimodal MRI; however, precise and accurate identification of the salvageable tissue is
essential, as the potential beneficial effect of treatment must be weighed against the risk of hemorrhage.
Although a diffusion/perfusion MRI mismatch has been suggested as a guide with which to identify the presence
of salvageable tissues and to serve as a selection marker for thrombolysis, the results of clinical trials using this
criterion have been inconclusive, in part because of the inclusion of regions of oligemia in the penumbra, which
overestimates the size of the tissue at risk. Amide proton transfer (APT) MRI has shown promise in detecting
such an acidosis-based ischemic penumbra in animal models and in human stroke patients. However, most
currently used APT imaging protocols are not very practical and not optimized with respect to the magnitude of
signal changes caused by the pH effect. More quantitative APT-MRI typically would require an even longer scan
time due to the use of multiple RF saturation frequencies, multiple acquisitions, and a long RF saturation pulse
(or pulse train), all of which hamper clinical translation due to the very small time-window between stroke onset
and possible thrombolysis treatment. Our long-term goal is to develop an ultrafast pH imaging technique for
routine clinical use to guide reperfusion therapies for hyperacute stroke patients at various therapeutic time
windows, as well as predict the risk of hemorrhagic transformation (HT) following acute ischemic stroke. The first
clinical hypothesis is that, similar to animal studies, the pH imaging penumbra due to ischemic tissue acidosis
predicts the maximum final infarction size if no reperfusion is initiated. Our second clinical hypothesis is that the
presence of severe tissue acidosis in the ischemic core is associated with an increased probability of secondary
HT. Our hypotheses will be tested through three specific aims: 1) to develop and optimize an ultrafast quantitative
pH imaging method; 2) to validate this technique and assess the diagnostic accuracy of the acidosis-based
ischemic penumbra in a clinical setting; and 3) to develop a novel deep-learning model with which to predict HT
following acute ischemic stroke, and quantify the sensitivity and specificity of pH imaging. This work is expected
to accelerate the translation of APT-MRI into a clinically viable and robust method. The addition of pH imaging
to the standard MRI protocol is expected to enable better visualization of the true ischemic penumbra, thus
improving predictions of clinical outcome and reducing the incidence of HT.
摘要
缺血性中风是美国发病率和死亡率的主要原因之一。
中风治疗是通过使用再灌注来挽救处于梗死风险但仍然存活的组织,
战略布局目前的再灌注治疗受到治疗时间窗紧和潜在风险的限制。
脑出血使用这种基于时间的方法,只有有限数量的中风患者有资格接受
治疗在以下情况下,超过标准治疗时间窗的患者可从治疗中获益:
基于多模式MRI进行识别;然而,精确且准确地识别可挽救组织是
这是必要的,因为治疗的潜在有益效果必须与出血风险相权衡。
尽管弥散/灌注MRI不匹配已被建议作为识别存在的指南,
的可挽救组织,并作为溶栓的选择标记,临床试验的结果,使用这个
标准一直是不确定的,部分原因是包括在半影区,
高估了危险组织的大小酰胺质子转移(APT)MRI在检测
这种基于酸中毒的缺血半暗带在动物模型和人类中风患者中。但大多数
当前使用的APT成像协议不是非常实用
由pH效应引起的信号变化。更定量的APT-MRI通常需要更长的扫描时间
由于使用多个RF饱和频率、多次采集和长RF饱和脉冲,
(or脉冲序列),由于中风发作之间的时间窗非常小,所有这些都妨碍了临床转化
以及可能的溶栓治疗。我们的长期目标是开发超快pH成像技术,
指导超急性卒中患者在不同治疗时间的再灌注治疗的常规临床应用
窗口,以及预测急性缺血性卒中后出血性转化(HT)的风险。第一
临床假设是,与动物研究相似,由于缺血性组织酸中毒,
如果不开始再灌注,预测最大最终梗死面积。我们的第二个临床假设是,
缺血核心中严重组织酸中毒的存在与继发性
HT。我们的假设将通过三个具体目标进行测试:1)开发和优化超快定量
pH成像方法; 2)验证该技术并评估基于酸中毒的诊断准确性
临床环境中的缺血半暗带; 3)开发一种新的深度学习模型来预测HT
急性缺血性卒中后,并量化pH成像的敏感性和特异性。这项工作预计
加速将APT-MRI转化为临床可行且稳健的方法。添加pH成像
标准MRI方案有望更好地显示真正的缺血半暗带,因此
改善临床结果的预测并降低HT的发生率。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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{{ truncateString('Hye Young Heo', 18)}}的其他基金
Chemical Exchange Saturation Transfer MR Fingerprinting
化学交换饱和转移 MR 指纹图谱
- 批准号:
10295906 - 财政年份:2021
- 资助金额:
$ 38.48万 - 项目类别:
Chemical Exchange Saturation Transfer MR Fingerprinting
化学交换饱和转移 MR 指纹图谱
- 批准号:
10491789 - 财政年份:2021
- 资助金额:
$ 38.48万 - 项目类别:
Chemical Exchange Saturation Transfer MR Fingerprinting
化学交换饱和转移 MR 指纹图谱
- 批准号:
10672421 - 财政年份:2021
- 资助金额:
$ 38.48万 - 项目类别:
Ultrafast Quantitative pH MRI for Acute Ischemic Stroke Patients
用于急性缺血性中风患者的超快定量 pH MRI
- 批准号:
10553103 - 财政年份:2020
- 资助金额:
$ 38.48万 - 项目类别:
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