EXploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies
EXploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies
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DOI：
10.1016/j.neuroimage.2020.117031
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发表时间：
2020-10-01
期刊：
影响因子：
5.7
通讯作者：
Barkhof, Frederik
中科院分区：
文献类型：
--
作者：
Mutsaerts, Henk J. M. M.;Petr, Jan;Barkhof, Frederik
动脉自旋标记（ASL）自问世以来经历了重大发展，重点是提高其采集和定量的标准化和可重复性。在社区范围内努力实现强大和可重复的临床ASL图像处理的过程中，我们开发了ExploreASL软件包，允许跨中心和扫描仪进行标准化分析。ExploreASL中使用的程序利用了已发布的图像处理进步，并通过扫描仪特定处理和伪影减少来解决多中心数据集的挑战，以限制患者排除。ExploreASL是独立的，用MATLAB编写，基于统计参数映射（SPM），并在多个操作系统上运行。为了促进协作和数据交换，该工具箱遵循数据结构、来源和最佳分析实践的多个标准和建议。ExploreASL经过反复优化和测试，在各种临床人群中使用不同的脉冲序列分析了超过10，000个ASL扫描，产生了四个处理模块：Import、Structural、ASL和Population分别执行数据管理、结构和ASL图像处理和质量控制任务，并最终为单个受试者和组水平的统计分析准备结果。我们说明了ExploreASL处理结果从三个队列：围产期HIV感染的儿童，健康的成年人，老年人在神经退行性疾病的风险。我们展示了在不同中心使用不同操作系统和MATLAB版本处理时每个队列的再现性，以及其对灰质脑血流定量的影响。ExploreASL促进了图像处理和质量控制的标准化，允许合并队列，这可能会增加统计功效并发现组间灌注差异。最终，这种工作流程可能会推动ASL在临床研究、试验和实践中更广泛地采用。
Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners.The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice.ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow.ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.