Julius-Maximilians-University Würzburg, Department of Neurology, Germany.
Beth Israel Deaconess Medical Center, Department of Neurology, Harvard Medical School, Boston, MA, USA.
Brain. 2019 May 1;142(5):1386-1398. doi: 10.1093/brain/awz046.
Deep brain stimulation of the internal globus pallidus is a highly effective and established therapy for primary generalized and cervical dystonia, but therapeutic success is compromised by a non-responder rate of up to 25%, even in carefully-selected groups. Variability in electrode placement and inappropriate stimulation settings may account for a large proportion of this outcome variability. Here, we present probabilistic mapping data on a large cohort of patients collected from several European centres to resolve the optimal stimulation volume within the pallidal region. A total of 105 dystonia patients with pallidal deep brain stimulation were enrolled and 87 datasets (43 with cervical dystonia and 44 with generalized dystonia) were included into the subsequent 'normative brain' analysis. The average improvement of dystonia motor score was 50.5 ± 30.9% in cervical and 58.2 ± 48.8% in generalized dystonia, while 19.5% of patients did not respond to treatment (<25% benefit). We defined probabilistic maps of anti-dystonic effects by aggregating individual electrode locations and volumes of tissue activated (VTA) in normative atlas space and ranking voxel-wise for outcome distribution. We found a significant relation between motor outcome and the stimulation volume, but not the electrode location per se. The highest probability of stimulation induced motor benefit was found in a small volume covering the ventroposterior globus pallidus internus and adjacent subpallidal white matter. We then used the aggregated VTA-based outcome maps to rate patient individual VTAs and trained a linear regression model to predict individual outcomes. The prediction model showed robustness between the predicted and observed clinical improvement, with an r2 of 0.294 (P < 0.0001). The predictions deviated on average by 16.9 ± 11.6 % from observed dystonia improvements. For example, if a patient improved by 65%, the model would predict an improvement between 49% and 81%. Results were validated in an independent cohort of 10 dystonia patients, where prediction and observed benefit had a correlation of r2 = 0.52 (P = 0.02) and a mean prediction error of 10.3% (±8.9). These results emphasize the potential of probabilistic outcome brain mapping in refining the optimal therapeutic volume for pallidal neurostimulation and advancing computer-assisted planning and programming of deep brain stimulation.
深部脑刺激内侧苍白球是一种治疗原发性全身性和颈部肌张力障碍的高效且成熟的疗法，但即使在精心挑选的患者中，仍有高达 25%的无应答率，从而影响治疗效果。电极放置的变异性和不适当的刺激设置可能是这种结果变异性的很大一部分原因。在这里，我们展示了来自几个欧洲中心的大量患者的概率映射数据，以解决苍白球区域内的最佳刺激体积问题。共纳入 105 例接受苍白球深部脑刺激的肌张力障碍患者，其中 87 例（43 例为颈部肌张力障碍，44 例为全身性肌张力障碍）纳入后续的“正常脑”分析。颈部肌张力障碍和全身性肌张力障碍患者的平均肌张力障碍运动评分改善分别为 50.5±30.9%和 58.2±48.8%，而 19.5%的患者对治疗无反应（<25%的获益）。我们通过在正常图谱空间中聚合个体电极位置和激活的组织体积（VTA），并对结果分布进行体素级排序，定义了抗肌张力障碍效应的概率图。我们发现运动结果与刺激体积之间存在显著关系，但与电极位置本身无关。在覆盖腹后内侧苍白球 internus 和相邻苍白球下白质的小体积内，发现刺激诱导运动获益的概率最高。然后，我们使用聚合的基于 VTA 的结果图来评估患者个体的 VTA，并训练线性回归模型来预测个体结果。预测模型显示，在预测和观察到的临床改善之间具有稳健性，相关系数 r2 为 0.294（P<0.0001）。预测平均与观察到的肌张力障碍改善相差 16.9±11.6%。例如，如果患者改善了 65%，则模型将预测改善幅度在 49%到 81%之间。在 10 例肌张力障碍患者的独立队列中验证了结果，预测和观察到的益处之间的相关性 r2=0.52（P=0.02），平均预测误差为 10.3%（±8.9）。这些结果强调了概率性结果脑映射在优化苍白球神经刺激的最佳治疗体积以及推进深部脑刺激的计算机辅助规划和编程方面的潜力。
