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结构人类脑网络:弥散轨迹追踪中的热门话题。

Structural human brain networks: hot topics in diffusion tractography.

机构信息

NatBrainLab, Department of Neuroimaging, Institute of Psychiatry, King's College London, London, UK.

出版信息

Curr Opin Neurol. 2012 Aug;25(4):375-83. doi: 10.1097/WCO.0b013e328355d544.

Abstract

PURPOSE OF REVIEW

After more than 10 years of methodological developments and clinical applications, diffusion imaging tractography has reached a crossroad. Although the method is still in its infancy, the time has come to address some important questions. Can tractography reproduce reliably known anatomy or describe new anatomical pathways? Are interindividual differences, for example in tract lateralization, important to understand heterogeneity of clinical manifestations? Do novel tractography algorithms provide a real advantage over previous methods? Here we focus on some of the most exciting recent advancements in diffusion tractography and critically highlight their advantages and limitations.

RECENT FINDINGS

A flourishing of diffusion methods and models are bringing new solutions to the well known limitations of classical tractography based on the tensor model. However, these methods pose also new challenges and require the convergence and integration of different disciplines before they can replace what is currently widely available.

SUMMARY

Rigorous postmortem validation, clinical optimization and experimental confirmation are obligatory steps before advanced diffusion technologies can translate into clear benefits for neurological patients.

摘要

综述目的:经过 10 多年的方法学发展和临床应用,弥散成像轨迹追踪技术已经到了一个十字路口。虽然该方法仍处于起步阶段,但现在是时候解决一些重要问题了。轨迹追踪技术能否可靠地再现已知的解剖结构或描述新的解剖通路?个体间的差异,例如在束侧化方面,对于理解临床表现的异质性是否重要?新的轨迹追踪算法是否比以前的方法有真正的优势?在这里,我们关注弥散轨迹追踪技术中一些最令人兴奋的最新进展,并批判性地强调它们的优点和局限性。

最近的发现:丰富的弥散方法和模型为基于张量模型的经典轨迹追踪技术的一些众所周知的局限性带来了新的解决方案。然而,这些方法也带来了新的挑战,需要不同学科的融合和整合,然后才能取代目前广泛应用的方法。

总结:在高级弥散技术能为神经科患者带来明显益处之前,严格的尸检验证、临床优化和实验验证是必不可少的步骤。

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