Hassanzadeh Elmira, Ailion Alyssa, Hassanzadeh Masoud, Hornak Alena, Peled Noam, Martino Dana, Warfield Simon K, Lan Zhou, Gholipour Taha, Stufflebeam Steven M
From the Department of Radiology (E.H., Z.L.), Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
Department of Neurology (A.A., A.H., D.M.), Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
AJNR Am J Neuroradiol. 2025 Feb 3;46(2):293-301. doi: 10.3174/ajnr.A8438.
The quality of resting-state fMRI (rs-fMRI) under anesthesia is variable and there are no guidelines on optimal image acquisition or anesthesia protocol. We aim to identify the factors that may lead to compromised clinical rs-fMRI under anesthesia.
In this cross-sectional study, we analyzed clinical rs-fMRI data acquired under anesthesia from 2009-2023 at Massachusetts General Hospital. Independent component analysis-driven resting-state networks (RSNs) of each patient were evaluated qualitatively and quantitatively and grouped as robust or weak. Overall networks were evaluated by using the qualitative method, and motor and language networks were evaluated by using the quantitative method. RSN robustness was analyzed in 4 outcome categories: overall, combined motor-language, individual motor, and language networks. Predictor variables included rs-fMRI acquisition parameters, anesthesia medications, underlying brain structural abnormalities, age, and sex. Logistic regression was used to examine the effect of the study variables on RSN robustness.
Sixty-nine patients were identified. With qualitative assessment, 40 had robust and 29 had weak overall RSN. Quantitatively, 45 patients had robust, while 24 had weak motor-language networks. Among all the predictor variables, only sevoflurane significantly contributed to the outcomes, with sevoflurane administration reducing the odds of having robust RSN in overall (OR = 0.2, 95% CI = 0.05-0.79, = .02), motor-language (OR = 0.18, 95% CI = 0.04-0.80, = .02), and individual motor (OR = 0.1, 95% CI = 0.02-0.64, = .02) categories. Individual language network robustness was not associated with the tested predictor variables.
Sevoflurane anesthesia may compromise the visibility of fMRI RSN, particularly impacting motor networks. This finding suggests that the type of anesthesia is a critical factor in rs-fMRI quality. We did not observe the association of the MR acquisition technique or underlying structural abnormality with the RSN robustness.
麻醉状态下静息态功能磁共振成像(rs-fMRI)的质量参差不齐,目前尚无关于最佳图像采集或麻醉方案的指南。我们旨在确定可能导致麻醉状态下临床rs-fMRI质量受损的因素。
在这项横断面研究中,我们分析了2009年至2023年在马萨诸塞州总医院采集的麻醉状态下的临床rs-fMRI数据。对每位患者基于独立成分分析的静息态网络(RSN)进行定性和定量评估,并分为强或弱两类。整体网络采用定性方法评估,运动和语言网络采用定量方法评估。在以下4个结果类别中分析RSN的稳健性:整体、运动-语言联合、个体运动和语言网络。预测变量包括rs-fMRI采集参数、麻醉药物、潜在脑结构异常、年龄和性别。采用逻辑回归分析研究变量对RSN稳健性的影响。
共纳入69例患者。定性评估显示,40例患者的整体RSN强,29例患者的整体RSN弱。定量评估显示,45例患者的运动-语言网络强,24例患者的运动-语言网络弱。在所有预测变量中,只有七氟醚对结果有显著影响,使用七氟醚会降低整体(OR = 0.2,95% CI = 0.05 - 0.79,P = 0.02)、运动-语言联合(OR = 0.18,95% CI = 0.04 - 0.80,P = 0.02)和个体运动(OR = 0.1,95% CI = 0.02 - 0.64,P = 0.02)类别中出现强RSN的几率。个体语言网络的稳健性与所测试的预测变量无关。
七氟醚麻醉可能会损害fMRI RSN的可视性,尤其会影响运动网络。这一发现表明麻醉类型是rs-fMRI质量的关键因素。我们未观察到MR采集技术或潜在结构异常与RSN稳健性之间的关联。