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A contrario detection of focal brain perfusion abnormalities based on an arterial spin labeling template

机译:基于动脉旋转标记模板的局灶性脑灌注异常的逆向检测

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Arterial Spin Labeling (ASL) is a recent MRI perfusion technique which enables quantification of cerebral blood flow (CBF). The presence of regions with atypical CBF can characterize a pathology. In brain tumors for instance, perfusion increase can be directly related to the grading of the malignant tissues. It is therefore of great interest to identify these regions in order to provide the patients with the most appropriate therapy. In this paper, we propose to detect abnormal brain perfusion by using an a contrario framework and an ASL template as a model of normal perfusion. Validation was undertaken by qualitative comparison with CBF extracted from dynamic susceptibility weighted contrast enhanced (DSC) imaging. We experimented this framework on four patients presenting brain tumors. Results show that high perfusion regions found in DSC CBF maps are correctly identified as hyperperfusions with a contrario detection. Automatic detection has clear advantages over manual delineation since it is less time-consuming, does not depend on medical expertise and allows quantification of perfusion abnormalities within the detected regions.
机译:动脉自旋标记(ASL)是最新的MRI灌注技术,可量化脑血流(CBF)。具有非典型CBF的区域的存在可以表征病理。例如,在脑肿瘤中,灌注增加可能与恶性组织的分级直接相关。因此,非常感兴趣的是识别这些区域以便为患者提供最合适的治疗方法。在本文中,我们建议通过使用反向框架和ASL模板作为正常灌注模型来检测异常脑灌注。通过与从动态磁化率加权对比增强(DSC)成像中提取的CBF进行定性比较来进行验证。我们对出现脑肿瘤的四名患者进行了实验。结果表明,在DSC CBF图中发现的高灌注区域已被正确识别为具有逆向检测的过度灌注。自动检测相对于手动勾画具有明显的优势,因为它耗时少,不依赖医学专业知识并且可以对检测到的区域内的灌注异常进行量化。

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