Evaluation of a personalized functional near infra-red optical tomography workflow using maximum entropy on the mean,Human Brain Mapping

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Evaluation of a personalized functional near infra-red optical tomography workflow using maximum entropy on the mean
Human Brain Mapping ( IF 3.5 ) Pub Date : 2021-08-03 , DOI: 10.1002/hbm.25566
Zhengchen Cai ₁ , Makoto Uji ₁ , Ümit Aydin _{1,

2} , Giovanni Pellegrino _{3,

4} , Amanda Spilkin ₁ , Édouard Delaire ₁ , Chifaou Abdallah _{3,

4} , Jean-Marc Lina _{5,

6} , Christophe Grova _{1,

3,

4,

6}

Affiliation

In the present study, we proposed and evaluated a workflow of personalized near infra-red optical tomography (NIROT) using functional near-infrared spectroscopy (fNIRS) for spatiotemporal imaging of cortical hemodynamic fluctuations. The proposed workflow from fNIRS data acquisition to local 3D reconstruction consists of: (a) the personalized optimal montage maximizing fNIRS channel sensitivity to a predefined targeted brain region; (b) the optimized fNIRS data acquisition involving installation of optodes and digitalization of their positions using a neuronavigation system; and (c) the 3D local reconstruction using maximum entropy on the mean (MEM) to accurately estimate the location and spatial extent of fNIRS hemodynamic fluctuations along the cortical surface. The workflow was evaluated on finger-tapping fNIRS data acquired from 10 healthy subjects for whom we estimated the reconstructed NIROT spatiotemporal images and compared with functional magnetic resonance imaging (fMRI) results from the same individuals. Using the fMRI activation maps as our reference, we quantitatively compared the performance of two NIROT approaches, the MEM framework and the conventional minimum norm estimation (MNE) method. Quantitative comparisons were performed at both single subject and group-level. Overall, our results suggested that MEM provided better spatial accuracy than MNE, while both methods offered similar temporal accuracy when reconstructing oxygenated (HbO) and deoxygenated hemoglobin (HbR) concentration changes evoked by finger-tapping. Our proposed complete workflow was made available in the brainstorm fNIRS processing plugin—NIRSTORM, thus providing the opportunity for other researchers to further apply it to other tasks and on larger populations.

中文翻译：

使用平均值最大熵评估个性化功能近红外光学断层扫描工作流程

在本研究中，我们提出并评估了使用功能性近红外光谱（fNIRS）进行皮质血流动力学波动时空成像的个性化近红外光学断层扫描（NIROT）的工作流程。所提出的从 fNIRS 数据采集到局部 3D 重建的工作流程包括：（a）个性化最佳蒙太奇最大化 fNIRS 通道对预定义目标大脑区域的敏感性； (b) 优化的 fNIRS 数据采集，涉及安装光极并使用神经导航系统对其位置进行数字化； (c) 使用平均最大熵 (MEM) 进行 3D 局部重建，以准确估计 fNIRS 血流动力学波动沿皮质表面的位置和空间范围。该工作流程根据从 10 名健康受试者采集的手指敲击 fNIRS 数据进行了评估，我们为这些受试者估计了重建的 NIROT 时空图像，并将其与同一个人的功能磁共振成像 (fMRI) 结果进行了比较。使用 fMRI 激活图作为参考，我们定量比较了两种 NIROT 方法、MEM 框架和传统的最小范数估计 (MNE) 方法的性能。在单个受试者和群体水平上进行定量比较。总体而言，我们的结果表明，MEM 比 MNE 提供更好的空间精度，而两种方法在重建手指敲击引起的含氧 (HbO) 和脱氧血红蛋白 (HbR) 浓度变化时提供相似的时间精度。我们提出的完整工作流程已在集思广益 fNIRS 处理插件 NIRSTORM 中提供，从而为其他研究人员提供了将其进一步应用于其他任务和更大人群的机会。

更新日期：2021-09-19

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