Stroke treatment goes personalized: Gaining added diagnostic yield bycomputer-assisted treatment selection
Stroke treatment goes personalized: Gaining added diagnostic yield bycomputer-assisted treatment selection
批准号:
326824585
负责人:
Professor Dr. Björn Menze
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2017
资助国家:
德国
项目状态:
已结题
起止时间:
2016-12-31 至 2021-12-31
中文摘要
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英文摘要
There is now class I evidence that mechanical thrombectomy is a safe and effective therapy within an estimated time frame of 6 h after stroke onset. Seven prospective studies have recently evidenced the superiority in proximal vessel occlusions (MR-CLEAN, ESCAPE, EXTEND-IA, SWIFT-PRIME, REVASCAT, THRACE, and THERAPY). Mechanical thrombectomy has thus become the treatment option of choice to achieve an early and sustained revascularization of proximally occluded vessels in tertiary care stroke centers. These studies have illustrated that mechanical thrombectomy using stent retrievers is a highly effective treatment with low complication rates. However, due to the narrow inclusion criteria and limed time window for treatment, the studies do not provide a guide for the majority of clinical patients1 who do not match inclusion criteria such as for example presentation beyond the time window of 6 hours of or with large infarct core at initial imaging. The aim of decision making for endovascular stroke treatment is to maximized the number of patients who will benefit from recanalization and minimized the patients will futile recanalization after endovascular stroke treatment. To facilitate this, an individualized prediction model of the neurological outcome in case of recanalization compared to the natural history is necessary.These studies have highlighted the potential to select patients based on the size of the penumbra and ischemic core, but have raised new questions to be solved: 'can we predict a benefit in tissue survival if mechanical thrombectomy is successfully applied compared to the natural course of disease'. This question is strongly dependent on the presence of 'sufficient vs. insufficient collaterals'. The availability of a fast, safe, reproducible and reliable information about the expected tissue salvage would allow us not only to select patients that would benefit from mechanical thrombectomy, it would also permit selection of patients for revascularization in a more flexible time window that might exceed 6 h if sufficient collateral flow enables sustained tissue survival. The goal of the project is to provide a system capable of assessing patient risk in acute stroke, based on imaging features and quantification of collateral flow derived from pre-interventional imaging. This information will benefit stroke patients, by providing neuroradiologists and stroke neurologists with a fast, accurate, repeatable interpretation of multiple disparate information sources. Evidence from our system will enable better treatment selection by refining the estimation of irreversibly damaged vs. potentially salvageable penumbral tissue and its respective lesion load on eloquent areas of the brain. An accurate computer-assisted treatment selection module offers the potential to select patients with stable collaterals and preserved penumbral from even beyond the currently recommended window of 6 hours after stroke onset.
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批准号:283653538
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项目类别:Research Grants
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资助金额:$0.0万
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财政年份:2016
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负责人:Professor Dr. Björn Menze
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依托单位:
Patienten-adaptive Tumormodelle in der medizinischen Bildverarbeitung
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批准号:103012018
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项目类别:Research Fellowships
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资助金额:$0.0万
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财政年份:2008
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负责人:Professor Dr. Björn Menze
-
依托单位:
国内基金
海外基金
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