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采用改良 SIENA 方法评估颈椎脊髓萎缩。

Evaluation of cervical spinal cord atrophy using a modified SIENA approach.

机构信息

Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy; Siena Imaging S.r.l., Siena, Italy.

NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering Department, University College London, London, United Kingdom; e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain.

出版信息

Neuroimage. 2024 Sep;298:120775. doi: 10.1016/j.neuroimage.2024.120775. Epub 2024 Aug 4.

Abstract

Spinal cord (SC) atrophy obtained from structural magnetic resonance imaging has gained relevance as an indicator of neurodegeneration in various neurological disorders. The common method to assess SC atrophy is by comparing numerical differences of the cross-sectional spinal cord area (CSA) between time points. However, this indirect approach leads to considerable variability in the obtained results. Studies showed that this limitation can be overcome by using a registration-based technique. The present study introduces the Structural Image Evaluation using Normalization of Atrophy on the Spinal Cord (SIENA-SC), which is an adapted version of the original SIENA method, designed to directly calculate the percentage of SC volume change over time from clinical brain MRI acquired with an extended field of view to cover the superior part of the cervical SC. In this work, we compared SIENA-SC with the Generalized Boundary Shift Integral (GBSI) and the CSA change. On a scan-rescan dataset, SIENA-SC was shown to have the lowest measurement error than the other two methods. When comparing a group of 190 Healthy Controls with a group of 65 Multiple Sclerosis patients, SIENA-SC provided significantly higher yearly rates of atrophy in patients than in controls and a lower sample size when measured for treatment effect sizes of 50%, 30% and 10%. Our findings indicate that SIENA-SC is a robust, reproducible, and sensitive approach for assessing longitudinal changes in spinal cord volume, providing neuroscientists with an accessible and automated tool able to reduce the need for manual intervention and minimize variability in measurements.

摘要

脊髓(SC)萎缩通过结构磁共振成像获得,已成为各种神经疾病中神经退行性变的一个指标。评估 SC 萎缩的常用方法是比较两个时间点之间脊髓横截面积(CSA)的数值差异。然而,这种间接方法会导致所得到的结果存在相当大的差异。研究表明,通过使用基于配准的技术可以克服这一局限性。本研究介绍了脊髓萎缩的结构图像评估(SIENA-SC),这是原始 SIENA 方法的改编版本,旨在从临床大脑 MRI 中直接计算脊髓体积随时间的变化百分比,该 MRI 采用扩展视野获得,以覆盖颈 SC 的上部。在这项工作中,我们将 SIENA-SC 与广义边界位移积分(GBSI)和 CSA 变化进行了比较。在扫描-再扫描数据集上,SIENA-SC 的测量误差最小。当将 190 名健康对照者与 65 名多发性硬化症患者进行比较时,SIENA-SC 提供了患者比对照组更高的每年萎缩率,并且在测量 50%、30%和 10%的治疗效果大小时,所需的样本量更小。我们的发现表明,SIENA-SC 是一种用于评估脊髓体积纵向变化的稳健、可重复和敏感的方法,为神经科学家提供了一种易于使用的自动工具,能够减少手动干预的需要,并最大限度地减少测量的变异性。

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