Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada.
Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands.
J Magn Reson Imaging. 2018 Jan;47(1):131-140. doi: 10.1002/jmri.25751. Epub 2017 May 8.
To compare registration strategies to align arterial spin labeling (ASL) with 3D T1-weighted (T1w) images, with the goal of reducing the between-subject variability of cerebral blood flow (CBF) images.
Multi-center 3T ASL data were collected at eight sites with four different sequences in the multi-center GENetic Frontotemporal dementia Initiative (GENFI) study. In a total of 48 healthy controls, we compared the following image registration options: (I) which images to use for registration (perfusion-weighted images [PWI] to the segmented gray matter (GM) probability map (pGM) (CBF-pGM) or M0 to T1w (M0-T1w); (II) which transformation to use (rigid-body or non-rigid); and (III) whether to mask or not (no masking, M0-based FMRIB software library Brain Extraction Tool [BET] masking). In addition to visual comparison, we quantified image similarity using the Pearson correlation coefficient (CC), and used the Mann-Whitney U rank sum test.
CBF-pGM outperformed M0-T1w (CC improvement 47.2% ± 22.0%; P < 0.001), and the non-rigid transformation outperformed rigid-body (20.6% ± 5.3%; P < 0.001). Masking only improved the M0-T1w rigid-body registration (14.5% ± 15.5%; P = 0.007).
The choice of image registration strategy impacts ASL group analyses. The non-rigid transformation is promising but requires validation. CBF-pGM rigid-body registration without masking can be used as a default strategy. In patients with expansive perfusion deficits, M0-T1w may outperform CBF-pGM in sequences with high effective spatial resolution. BET-masking only improves M0-T1w registration when the M0 image has sufficient contrast.
1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:131-140.
比较动脉自旋标记（ASL）与 3D T1 加权（T1w）图像配准的策略，目的是减少脑血流（CBF）图像的个体间变异性。
在多中心 GENetic Frontotemporal dementia Initiative（GENFI）研究中，8 个地点使用 4 种不同的序列采集了多中心 3T ASL 数据。在总共 48 名健康对照者中，我们比较了以下图像配准选项：（I）用于配准的图像（灌注加权图像[PWI]到分割灰质（GM）概率图（pGM）（CBF-pGM）或 M0 到 T1w（M0-T1w）；（II）使用的变换（刚体或非刚体）；以及（III）是否掩蔽（不掩蔽，基于 M0 的 FMRIB 软件库 Brain Extraction Tool[BET]掩蔽）。除了视觉比较外，我们还使用 Pearson 相关系数（CC）定量评估图像相似性，并使用 Mann-Whitney U 秩和检验。
CBF-pGM 优于 M0-T1w（CC 改善 47.2%±22.0%；P<0.001），非刚体变换优于刚体变换（20.6%±5.3%；P<0.001）。掩蔽仅改善了 M0-T1w 刚体配准（14.5%±15.5%；P=0.007）。
图像配准策略的选择会影响 ASL 组分析。非刚体变换很有前途，但需要验证。无掩蔽 CBF-pGM 刚体配准可作为默认策略。在灌注缺损扩展的患者中，在具有高有效空间分辨率的序列中，M0-T1w 可能优于 CBF-pGM。只有当 M0 图像具有足够的对比度时，BET 掩蔽才会改善 M0-T1w 配准。
1 技术功效：第 1 阶段 J. Magn. Reson. Imaging 2018；47：131-140。
