Optimization and validation of multi-echo, multi-contrast SAGE acquisition in fMRI

Elizabeth Keeling, Maurizio Bergamino, Sudarshan Ragunathan, C. Quarles, Allen T. Newton, Ashley M. Stokes
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Abstract

Abstract The purpose of this study was to optimize and validate a multi-contrast, multi-echo fMRI method using a combined spin- and gradient-echo (SAGE) acquisition. It was hypothesized that SAGE-based blood oxygen level-dependent (BOLD) functional MRI (fMRI) will improve sensitivity and spatial specificity while reducing signal dropout. SAGE-fMRI data were acquired with five echoes (2 gradient-echoes, 2 asymmetric spin-echoes, and 1 spin-echo) across 12 protocols with varying acceleration factors, and temporal SNR (tSNR) was assessed. The optimized protocol was then implemented in working memory and vision tasks in 15 healthy subjects. Task-based analysis was performed using individual echoes, quantitative dynamic relaxation times T2* and T2, and echo time-dependent weighted combinations of dynamic signals. These methods were compared to determine the optimal analysis method for SAGE-fMRI. Implementation of a multiband factor of 2 and sensitivity encoding (SENSE) factor of 2.5 yielded adequate spatiotemporal resolution while minimizing artifacts and loss in tSNR. Higher BOLD contrast-to-noise ratio (CNR) and tSNR were observed for SAGE-fMRI relative to single-echo fMRI, especially in regions with large susceptibility effects and for T2-dominant analyses. Using a working memory task, the extent of activation was highest with T2*-weighting, while smaller clusters were observed with quantitative T2* and T2. SAGE-fMRI couples the high BOLD sensitivity from multi-gradient-echo acquisitions with improved spatial localization from spin-echo acquisitions, providing two contrasts for analysis. SAGE-fMRI provides substantial advantages, including improving CNR and tSNR for more accurate analysis.
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多回波、多对比 SAGE 采集在 fMRI 中的优化与验证
摘要 本研究的目的是利用自旋和梯度回波联合采集(SAGE)优化和验证多对比、多回波 fMRI 方法。根据假设,基于 SAGE 的血氧水平依赖性(BOLD)功能磁共振成像(fMRI)将提高灵敏度和空间特异性,同时减少信号丢失。在 12 种不同加速因子的方案中,用五次回波(2 次梯度回波、2 次非对称自旋回波和 1 次自旋回波)采集了 SAGE-fMRI 数据,并评估了时间 SNR(tSNR)。然后在 15 名健康受试者的工作记忆和视觉任务中实施了优化方案。使用单个回波、定量动态弛豫时间 T2* 和 T2 以及回波时间相关的动态信号加权组合进行了基于任务的分析。通过比较这些方法,确定了 SAGE-fMRI 的最佳分析方法。采用 2 的多波段因子和 2.5 的灵敏度编码(SENSE)因子可获得足够的时空分辨率,同时最大限度地减少伪影和 tSNR 损失。与单回波 fMRI 相比,SAGE-fMRI 的 BOLD 对比度-噪声比(CNR)和 tSNR 都更高,尤其是在具有较大易感性效应的区域和 T2 优势分析中。通过工作记忆任务,T2*加权的激活程度最高,而定量 T2* 和 T2 则观察到较小的集群。SAGE-fMRI 将多梯度回波采集的高 BOLD 敏感性与自旋回波采集的更好空间定位相结合,为分析提供了两种对比。SAGE-fMRI 具有很大的优势,包括提高了 CNR 和 tSNR,使分析更加准确。
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