Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
Computer Science, Vanderbilt University, Nashville, TN, USA.
Magn Reson Imaging. 2022 Jan;85:44-56. doi: 10.1016/j.mri.2021.10.017. Epub 2021 Oct 16.
Reproducible identification of white matter pathways across subjects is essential for the study of structural connectivity of the human brain. One of the key challenges is anatomical differences between subjects and human rater subjectivity in labeling. Labeling white matter regions of interest presents many challenges due to the need to integrate both local and global information. Clearly communicating the manual processes to capture this information is cumbersome, yet essential to lay a solid foundation for comprehensive atlases. Segmentation protocols must be designed so the interpretation of the requested tasks as well as locating structural landmarks is anatomically accurate, intuitive and reproducible. In this work, we quantified the reproducibility of a first iteration of an open/public multi-bundle segmentation protocol. This allowed us to establish a baseline for its reproducibility as well as to identify the limitations for future iterations. The protocol was tested/evaluated on both typical 3 T research acquisition Baltimore Longitudinal Study of Aging (BLSA) and high-acquisition quality Human Connectome Project (HCP) datasets. The results show that a rudimentary protocol can produce acceptable intra-rater and inter-rater reproducibility. However, this work highlights the difficulty in generalizing reproducible results and the importance of reaching consensus on anatomical description of white matter pathways. The protocol has been made available in open source to improve generalizability and reliability in collaboration. The goal is to improve upon the first iteration and initiate a discussion on the anatomical validity (or lack thereof) of some bundle definitions and the importance of reproducibility of tractography segmentation.
跨受试者的可重现的白质通路识别对于人类大脑结构连接的研究至关重要。其中一个关键挑战是受试者之间的解剖差异和人类评分者在标记中的主观性。由于需要整合局部和全局信息,因此对白质感兴趣区域进行标记具有许多挑战。由于需要捕获这些信息,因此明确传达手动过程非常麻烦,但对于为全面图谱奠定坚实基础至关重要。分割协议必须设计为使请求任务的解释以及定位结构地标具有解剖学准确性、直观性和可重复性。在这项工作中,我们量化了首次迭代的开放式/公共多束分割协议的可重现性。这使我们能够为其可重现性建立基准,并确定未来迭代的限制。该协议在典型的 3T 研究采集巴尔的摩老龄化纵向研究(BLSA)和高采集质量人类连接组计划(HCP)数据集上进行了测试/评估。结果表明,基本协议可以产生可接受的内部评分者和外部评分者的可重现性。然而,这项工作强调了推广可重现结果的困难以及就白质通路的解剖描述达成共识的重要性。该协议已在开源中提供,以提高协作中的可泛化性和可靠性。目标是改进第一版,并就一些束定义的解剖有效性(或缺乏)以及轨迹分割的可重现性进行讨论。