Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
J Neuroimaging. 2022 Nov;32(6):1080-1089. doi: 10.1111/jon.13042. Epub 2022 Aug 31.
Templates are a hallmark of image analysis in neuroimaging. However, while numerous structural templates exist and have facilitated single-subject and large group studies, templates based on functional contrasts, such as arterial spin labeling (ASL) perfusion, are scarce, have an inherently low spatial resolution, and are not as widely distributed. Having such tools at one's disposal is desirable, for example, in the case of studies not acquiring structural scans. We here propose an initial development of an ASL adult template based on high-resolution fast spin echo acquisitions.
High-resolution single-delay ASL, low-resolution multi-delay ASL, T -weighted magnetization prepared rapid acquisition 2 gradient echoes, and T fluid attenuated inversion recovery data were acquired in a cohort of 10 healthy volunteers (6 males and 4 females, 30± 7 years old). After offline reconstruction of high-resolution perfusion arterial transit time (ATT) and T1 maps, we built a multi-contrast template relying on the Advanced Normalization Toolbox multivariate template nonlinear construction framework. We offer examples for the registration of ASL data acquired with different sequences. Finally, we propose an ASL simulator based on our templates and a standard kinetic model that allows generating synthetic ASL contrasts based on user-specified parameters.
Boston ASL Template and Simulator (BATS) offers high-quality, high-resolution perfusion-weighted and quantitative perfusion templates accompanied by ATT and different anatomical contrasts readily available in the Montreal Neurological Institute space. In addition, examples of use for data registration and as a synthetic contrast generator show various applications in which BATS could be used.
We propose a new ASL template collection, named BATS, that also includes a simulator allowing the generation of synthetic ASL contrasts. BATS is available at http://github.com/manueltaso/batsasltemplate.
模板是神经影像学图像分析的标志。然而，虽然存在许多结构模板，并促进了单个体和大群体研究，但基于功能对比（如动脉自旋标记（ASL）灌注）的模板则很少，固有空间分辨率低，分布也不广泛。例如，在不获取结构扫描的情况下，拥有这些工具是很理想的。我们在此提出了一种基于高分辨率快速自旋回波采集的 ASL 成人模板的初步开发。
在一组 10 名健康志愿者（6 名男性和 4 名女性，30±7 岁）中，采集了高分辨率单延迟 ASL、低分辨率多延迟 ASL、T1 加权磁化准备快速获取 2 梯度回波和 T 液体衰减反转恢复数据。在离线重建高分辨率灌注动脉 transit time（ATT）和 T1 图后，我们构建了一个多对比度模板，该模板依赖于 Advanced Normalization Toolbox 多变量模板非线性构建框架。我们提供了使用不同序列采集 ASL 数据的注册示例。最后，我们提出了一个基于我们的模板和标准动力学模型的 ASL 模拟器，该模拟器允许根据用户指定的参数生成合成 ASL 对比。
波士顿 ASL 模板和模拟器（BATS）提供了高质量、高分辨率的灌注加权和定量灌注模板，同时还提供了易于在蒙特利尔神经学研究所空间中使用的 ATT 和不同的解剖对比度。此外，用于数据注册和作为合成对比生成器的使用示例展示了 BATS 可以用于各种应用。
我们提出了一个新的 ASL 模板集合，命名为 BATS，它还包括一个允许生成合成 ASL 对比的模拟器。BATS 可在 http://github.com/manueltaso/batsasltemplate 上获得。
