Opri Enrico, Isbaine Faical, Borgheai Seyyed Bahram, Bence Emily, Deligani Roohollah Jafari, Willie Jon T, Gross Robert E, Au Yong Nicholas, Miocinovic Svjetlana
Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America.
Department of Neurosurgery, Emory University, Atlanta, GA, United States of America.
J Neural Eng. 2025 Aug 29;22(4). doi: 10.1088/1741-2552/adf99f.
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established therapy for Parkinson's disease (PD). Yet, optimizing lead placement and stimulation programming remains challenging. Current techniques rely on imaging and intraoperative microelectrode recordings (MER), while programming relies on trial-and-error clinical testing, which can be time-consuming. DBS-induced local evoked potentials (DLEP), also known as evoked resonant neural activity, have emerged as a potential alternative electrophysiological marker for mapping. However, direct comparisons with traditional spectral features, such as beta-band, high-frequency oscillations (HFOs), and aperiodic component are lacking.We evaluated DLEP across 39 STN DBS leads in 31 subjects with PD undergoing DBS surgery, using both a single-pulse and high-frequency (HF) burst stimulation paradigms. We developed a novel artifact-removal method to enable monopolar DLEP recovery, including estimating the DLEP amplitudes at stimulated contacts, further enhancing spatial sampling of DLEP. We evaluated spectral features and DLEP in respect to imaging-based and MER-based localization, and its predictive power for post-operative programming.DLEP showed great spatial consistency, maximizing within STN with 100% accuracy for single-pulse and 84.62% for burst stimulation, surpassing spectral measures including beta (89.74%) and HFO (82.05%). DLEP better correlated with clinical outcomes (single-pulses= -0.33, HF bursts= -0.26), than spectral measures (beta= -0.25, HFO= 0.05). Furthermore, single-pulses at low-frequencies are sufficient for DLEP-based mapping.We show how DLEP provide higher STN-spatial specificity and correlation with postoperative programming compared to spectral features. To support clinical translation of DLEP, we developed two methods aimed to recover artifact-free DLEP and estimating DLEP amplitudes at stimulating contacts. DLEP appear distinct from beta and HFO activity, yet strongly tied to aperiodic spectral components, suggesting that DLEP amplitude reflects underlying STN excitability. This study highlights that DLEP are a robust and clinically valuable marker for DBS targeting and programming.
丘脑底核(STN)的深部脑刺激(DBS)是帕金森病(PD)的一种既定治疗方法。然而,优化电极植入位置和刺激程序仍然具有挑战性。目前的技术依赖于成像和术中微电极记录(MER),而程序设定则依赖于反复试验的临床测试,这可能很耗时。DBS诱发的局部诱发电位(DLEP),也称为诱发共振神经活动,已成为一种潜在的替代电生理标记物用于图谱绘制。然而,缺乏与传统频谱特征(如β波段、高频振荡(HFO)和非周期性成分)的直接比较。我们使用单脉冲和高频(HF)爆发刺激范式,对31例接受DBS手术的PD患者的39个STN DBS电极进行了DLEP评估。我们开发了一种新颖的伪迹去除方法,以实现单极DLEP恢复,包括估计受刺激触点处的DLEP振幅,进一步增强DLEP的空间采样。我们评估了基于成像和MER定位的频谱特征和DLEP,及其对术后编程的预测能力。DLEP显示出很强的空间一致性,在STN内达到最大值,单脉冲刺激时准确率为100%,爆发刺激时为84.62%,超过了包括β(89.74%)和HFO(82.05%)在内的频谱测量。与频谱测量(β=-0.25,HFO=0.05)相比,DLEP与临床结果的相关性更好(单脉冲=-0.33,HF爆发=-0.26)。此外,低频单脉冲足以用于基于DLEP的图谱绘制。我们展示了与频谱特征相比,DLEP如何提供更高的STN空间特异性以及与术后编程的相关性。为了支持DLEP的临床转化,我们开发了两种方法,旨在恢复无伪迹的DLEP并估计刺激触点处的DLEP振幅。DLEP似乎与β和HFO活动不同,但与非周期性频谱成分密切相关,这表明DLEP振幅反映了潜在的STN兴奋性。这项研究强调,DLEP是DBS靶向和编程的一种强大且具有临床价值的标记物。