Levy-Lamdan Ofri, Zifman Noa, Sasson Efrat, Efrati Shai, Hack Dallas C, Tanne David, Dolev Iftach, Fogel Hilla
QuantalX Neuroscience, Beer-Yaacov, Israel.
Sagol Center for Hyperbaric Medicine and Research, Shamir Medical Center, Zerifin, Israel.
Front Neurosci. 2020 Dec 21;14:589107. doi: 10.3389/fnins.2020.589107. eCollection 2020.
The aim of this study was to evaluate brain white matter (WM) fibers connectivity damage in stroke and traumatic brain injury (TBI) subjects by direct electrophysiological imaging (DELPHI) that analyzes transcranial magnetic stimulation (TMS)-evoked potentials (TEPs).
The study included 123 participants, out of which 53 subjects with WM-related pathologies (39 stroke, 14 TBI) and 70 healthy age-related controls. All subjects underwent DELPHI brain network evaluations of TMS-electroencephalogram (EEG)-evoked potentials and diffusion tensor imaging (DTI) scans for quantification of WM microstructure fractional anisotropy (FA).
DELPHI output measures show a significant difference between the healthy and stroke/TBI groups. A multidimensional approach was able to classify healthy from unhealthy with a balanced accuracy of 0.81 ± 0.02 and area under the curve (AUC) of 0.88 ± 0.01. Moreover, a multivariant regression model of DELPHI output measures achieved prediction of WM microstructure changes measured by FA with the highest correlations observed for fibers proximal to the stimulation area, such as frontal corpus callosum ( = 0.7 ± 0.02), anterior internal capsule ( = 0.7 ± 0.02), and fronto-occipital fasciculus ( = 0.65 ± 0.03).
These results indicate that features of TMS-evoked response are correlated to WM microstructure changes observed in pathological conditions, such as stroke and TBI, and that a multidimensional approach combining these features in supervised learning methods serves as a strong indicator for abnormalities and changes in WM integrity.
本研究旨在通过分析经颅磁刺激（TMS）诱发电位（TEP）的直接电生理成像（DELPHI）来评估中风和创伤性脑损伤（TBI）患者的脑白质（WM）纤维连接损伤。
该研究纳入了123名参与者，其中53名患有WM相关病变的患者（39名中风患者，14名TBI患者）以及70名年龄匹配的健康对照者。所有受试者均接受了TMS-脑电图（EEG）诱发电位的DELPHI脑网络评估以及扩散张量成像（DTI）扫描，以量化WM微观结构的分数各向异性（FA）。
DELPHI输出指标显示健康组与中风/TBI组之间存在显著差异。一种多维度方法能够以0.81±0.02的平衡准确率和0.88±0.01的曲线下面积（AUC）将健康者与非健康者区分开来。此外，DELPHI输出指标的多变量回归模型实现了对通过FA测量的WM微观结构变化的预测，对于刺激区域附近的纤维，如额叶胼胝体（= 0.7±0.02）、前内囊（= 0.7±0.02）和额枕束（= 0.65±0.03），观察到的相关性最高。
这些结果表明，TMS诱发反应的特征与在中风和TBI等病理条件下观察到的WM微观结构变化相关，并且在监督学习方法中结合这些特征的多维度方法可作为WM完整性异常和变化的有力指标。
