Background

Resting-state functional MRI (rs-fMRI) is a potential alternative to task-based functional MRI (tb-fMRI) for somatomotor network (SMN) identification. Brain networks can also be generated from tb-fMRI by using independent component analysis (ICA).

Purpose

To investigate whether the SMN can be identified by using ICA from a language task without a motor component, the sentence completion functional MRI (sc-fMRI) task, compared with rs-fMRI.

Materials and Methods

The sc-fMRI and rs-fMRI scans in patients who underwent presurgical brain mapping between 2012 and 2016 were analyzed, using the same imaging parameters (other than scanning time) on a 3.0-T MRI scanner. ICA was performed on rs-fMRI and sc-fMRI scans with use of a tool to separate data sets into their spatial and temporal components. Two neuroradiologists independently determined the presence of the dorsal SMN (dSMN) and ventral SMN (vSMN) on each study. Groups were compared by using t tests, and logistic regression was performed to identify predictors of the presence of SMNs.

Results

One hundred patients (mean age, 40.9 years ± 14.8 [standard deviation]; 61 men) were evaluated. The dSMN and vSMN were identified in 86% (86 of 100) and 76% (76 of 100) of rs-fMRI scans and 85% (85 of 100) and 69% (69 of 100) of sc-fMRI scans, respectively. The concordance between rs-fMRI and sc-fMRI for presence of dSMN and vSMN was 75% (75 of 100 patients) and 53% (53 of 100 patients), respectively. In 10 of 14 patients (71%) where rs-fMRI did not show the dSMN, sc-fMRI demonstrated it. This rate was 67% for the vSMN (16 of 24 patients).

Conclusion

In the majority of patients, independent component analysis of sentence completion task functional MRI scans reliably demonstrated the somatomotor network compared with resting-state functional MRI scans. Identifying target networks with a single sentence completion scan could reduce overall functional MRI scanning times by eliminating the need for separate motor tasks.

© RSNA, 2021

Online supplemental material is available for this article.

See also the editorial by Field and Birn in this issue.

中文翻译：

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从基于语言任务的 fMRI 与静息态 fMRI 比较脑损伤患者的躯体运动网络识别

背景

静息态功能性 MRI (rs-fMRI) 是基于任务的功能性 MRI (tb-fMRI) 的潜在替代方案，用于识别体运动网络 (SMN)。大脑网络也可以通过使用独立成分分析 (ICA) 从 tb-fMRI 生成。

目的

为了研究是否可以通过使用 ICA 从没有运动成分的语言任务中识别 SMN，与 rs-fMRI 相比，句子完成功能 MRI (sc-fMRI) 任务。

材料和方法

在 3.0-T MRI 扫描仪上使用相同的成像参数（扫描时间除外）分析了 2012 年至 2016 年间接受术前脑映射的患者的 sc-fMRI 和 rs-fMRI 扫描。ICA 是在 rs-fMRI 和 sc-fMRI 扫描上进行的，使用一种工具将数据集分成它们的空间和时间分量。两名神经放射科医生在每项研究中独立确定背侧 SMN (dSMN) 和腹侧 SMN (vSMN) 的存在。通过使用t检验比较各组，并进行逻辑回归以确定 SMN 存在的预测因素。

结果

评估了 100 名患者（平均年龄，40.9 岁 ± 14.8 [标准差]；61 名男性）。dSMN 和 vSMN 分别在 86% (86 of 100) 和 76% (76 of 100) rs-fMRI 扫描和 85% (85 of 100) 和 69% (69 of 100) sc-fMRI 扫描中被识别. rs-fMRI 和 sc-fMRI 之间存在 dSMN 和 vSMN 的一致性分别为 75%（100 名患者中的 75 名）和 53%（100 名患者中的 53 名）。在 rs-fMRI 未显示 dSMN 的 14 名患者中有 10 名 (71%)，sc-fMRI 显示了它。对于 vSMN（24 名患者中的 16 名），该比率为 67%。

结论

在大多数患者中，与静息状态功能 MRI 扫描相比，句子完成任务功能 MRI 扫描的独立成分分析可靠地证明了躯体运动网络。通过消除单独的运动任务的需要，使用单个句子完成扫描识别目标网络可以减少整体功能性 MRI 扫描时间。

©北美放射学会，2021

本文提供了在线补充材料。

另请参阅 Field 和 Birn 在本期中的社论。