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Acquisition guidelines and quality assessment tools for analyzing neonatal diffusion tensor MRI data

机译:用于分析新生儿扩散张量MRI数据的采集指南和质量评估工具

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SUMMARY: Diffusion tensor imaging is a valuable measure in clinical settings to assess diagnosis and prognosis of neonatal brain development. However, obtaining reliable images is not straightforward because of the tissue characteristics of the neonatal brain and the high likelihood of motion artifacts. In this review, we present guidelines on how to acquire DTI data of the neonatal brain and recommend high-quality data acquisition and processing as an essential means to obtain accurate and robust parametric maps. Sudden head movements are problematic for DTI in neonates, and these may lead to incorrect values. We describe strategies to minimize the corrupting effects both in terms of acquisition (eg, more gradient directions) and postprocessing (eg, tensor estimation methods). In addition, tools are described that can help assess whether a dataset is of sufficient quality for further assessment.
机译:摘要:弥散张量成像是临床环境中评估新生儿脑发育的诊断和预后的一种有价值的措施。但是,由于新生儿大脑的组织特征和运动伪像的可能性很高,因此获得可靠的图像并非易事。在这篇综述中,我们提出了有关如何获取新生儿大脑DTI数据的指南,并建议高质量的数据获取和处理,作为获取准确而强大的参数图的必要手段。突然的头部运动对于新生儿的DTI有问题,并且可能导致不正确的数值。我们描述了在获取(例如,更多的梯度方向)和后处理(例如,张量估计方法)方面最小化破坏效果的策略。另外,描述了可以帮助评估数据集是否具有足够质量以进行进一步评估的工具。

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