SIENA-XL for Improving the Assessment of Gray and White Matter Volume Changes on Brain MRI
SIENA-XL for Improving the Assessment of Gray and White Matter Volume Changes on Brain MRI
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DOI：
10.1002/hbm.23828
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发表时间：
2018-03-01
影响因子：
4.8
通讯作者：
De Stefano, Nicola
中科院分区：
文献类型：
--
作者：
Battaglini, Marco;Jenkinson, Mark;De Stefano, Nicola
本文介绍了一种新的基于分割的纵向管道SIENA-XL，它的主要优点是：（1）与SIENAX等横截面分割方法相比，提高了对白色（WM）和灰色（GM）物质的纵向体积变化估计精度;以及（ii）当使用雅可比行列式时避免基于配准的方法中的潜在偏差，平滑程度大于组织界面之间的空间尺度，这是萎缩通常发生的地方。SIENA-XL在执行最终分割之前实施了新的大脑提取程序和多时间点强度均衡步骤，其中还包括使用FMRIB的集成配准和分割工具对深层GM结构进行单独分割。使用不同的健康对照（HC）和多发性硬化（MS）MRI数据集评估了SIENA-XL对GM和WM体积变化的检测，并与传统的SIENAX和两种基于雅可比的方法SPM 12和SIENAX-JI（SIENAX的一个版本，包括雅可比积分- JI）进行了比较。在HC的扫描重新扫描数据中，SIENA-XL显示：（i）与SIENAX相比，误差显著降低50-70%;（ii）在包括重新定位的扫描重新扫描HC数据集中，与SIENAX-JI和SPM 12相比，误差无显著差异。当在基线和1年随访后在HC数据集中进行扫描重新扫描测试时，SIENA-XL显示：（i）比SIENAX的精确度显著更高（P < 0.01）;（ii）与SIENAX-JI和SPM 12无显著差异。最后，在79例MS患者的2年随访数据集中，与SIENAX、SIENAX-JI和SPM 12相比，SIENA-XL显示样本量大幅减少，检测治疗效果为25%、30%和50%。(C)2017 Wiley Periodicals，Inc.
In this article, SIENA-XL, a new segmentation-based longitudinal pipeline is introduced, for: (i) increasing the precision of longitudinal volume change estimation for white (WM) and gray (GM) matter separately, compared with cross-sectional segmentation methods such as SIENAX; and (ii) avoiding potential biases in registration-based methods when Jacobians are used, with a smoothing extent larger than spatial scale between tissue-interfaces, which is where atrophy usually occurs. SIENA-XL implements a new brain extraction procedure and a multi-time-point intensity equalization step before performing the final segmentation that also includes separate segmentation of deep GM structures by using FMRIB's Integrated Registration and Segmentation Tool. The detection of GM and WM volume changes with SIENA-XL was evaluated using different healthy control (HC) and multiple sclerosis (MS) MRI datasets and compared with the traditional SIENAX and two Jacobian-based approaches, SPM12 and SIENAX-JI (a version of SIENAX including Jacobian integration - JI). In scan-rescan data from HCs, SIENA-XL showed: (i) a significant decrease in error, of 50-70% when compared with SIENAX; (ii) no significant differences in error when compared with SIENAX-JI and SPM12 in a scan-rescan HC dataset that included repositioning. When tested in a HC dataset with scan-rescan both at baseline and after 1 year of follow-up, SIENA-XL showed: (i) significantly higher precision (P < 0.01) than SIENAX; (ii) no significant differences to SIENAX-JI and SPM12. Finally, in a dataset of 79 MS patients with a 2 years follow-up, SIENA-XL showed a substantial reduction of sample size, by comparison with SIENAX, SIENAX-JI, and SPM12, for detecting treatment effects of 25, 30, and 50%. (C) 2017 Wiley Periodicals, Inc.