Carr Sarah J A, Chen Weicong, Fondran Jeremy, Friel Harry, Sanchez-Gonzalez Javier, Zhang Jing, Tatsuoka Curtis
Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
Department of Neurology, Case Western Reserve University, Cleveland, OH, United States.
Front Neurosci. 2021 Nov 4;15:643740. doi: 10.3389/fnins.2021.643740. eCollection 2021.
Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed. Voxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on target statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR). Use of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 min on a 12 min scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters. A systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects.
功能磁共振成像(fMRI)通常需要较长的扫描时间,以确保能够检测到相关的大脑活动。然而,过多的实验可能会导致许多不良影响,比如学习和/或疲劳效应、受试者不适、过多的运动伪影以及对任务持续注意力的丧失。因此,过长时间的实验可能会对信号质量和体素激活的准确检测产生不利影响。在此,我们提出使用一种新颖的统计驱动方法进行实时功能磁共振成像的动态实验,该方法在观察到足够的统计证据来评估与任务相关的激活时会调用提前停止机制。基于一般线性模型(GLM)的体素级序贯概率比检验(SPRT)统计量在12名健康青少年受试者和11名极早产(EPT)青少年受试者的数学1-back任务功能磁共振成像扫描中得以实现。这种方法基于似然比,并允许基于目标统计误差阈值进行系统的提前停止。我们采用两阶段估计方法,在考虑停止之前能够对GLM参数进行准确估计。报告了不同第一阶段长度下的提前停止性能,并将激活结果与完整时长的结果进行比较。最后,使用提前停止和完整时长扫描数据进行组间比较。采用数值并行化以促进在每个重复时间(TR)内完成涉及新扫描的计算。使用SPRT证明了自动提前停止的可行性和效率提升,其激活检测与完整方案相当。大约一半的受试者实现了刺激给药的动态停止,典型的时间节省高达33%(在12分钟的扫描中节省4分钟)。对对照组受试者进行的组分析显示,提前停止扫描和完整时长扫描的活动模式相似。与足月正常对照组相比,EPT组个体在激活的位置和范围上表现出更大的变异性。这在EPT组的结果中很明显,表现为簇的数量更少、体积更小。已实施一种用于实时功能磁共振成像实验提前停止的系统统计方法。这种动态方法有望减轻受试者负担和疲劳效应。