基于模型的帕金森病闭环深部脑刺激效果指标研究

Research on Effect Index of Closed-loop Deep Brain Stimulation in Parkinson’s Disease Based on Model

随着人口老龄化的加重,多发于中老年人的帕金森病(PD)将给社会带来沉重的压力。然而基于模型的闭环深部脑刺激(DBS)治疗PD的研究中刺激效果评估指标单一且不直观,因此该文提出统一帕金森病评分量表(UPDRS)类估计(SUE)。丘脑底核β频带(13~35 Hz)的异常振荡已被证明与PD运动障碍密切相关,该文首先验证了β频带在刺激与未刺激状态下的功率变化对计算模型与闭环深部脑刺激(DBS)算法的可行性。然后统计分析了β爆发在时域的分布情况,并根据时间长度将β爆发二分类为长爆发与短爆发。由于临床上采用统一帕金森病评分量表(UPDRS)对PD的治疗效果进行评价,所以将β爆发的时域特性与UPDRS评分进行对比,并结合β爆发的二分类结果提出了估计刺激疗效的指标SUE。实验结果表明SUE与β爆发的持续时间有较强的相关性,能很好地模拟UPDRS在刺激状态与未刺激状态下的变化,为今后基于模型的闭环DBS研究奠定了基础。

With the continuous improvement of the aging population, Parkinson’s Disease(PD) that is more prevalent in middle-aged and elderly people will put heavy burden on society. However, the stimulation effect evaluation index of model-based Deep Brain Stimulation(DBS) for PD is single and not intuitive. Therefore, a new index the Similar to Unified Parkinson Disease Rating Scale(UPDRS) Estimates(SUE) is proposed. The feasibility of the computational model and the closed-loop DBS algorithm is firstly verified according to the power changes of the β band(13~35 Hz). The distribution of β bursts in time domain is statistically analyzed,and is dichotomized into long and short bursts, then SUE is proposed. The experimental results show that SUE has a strong correlation with the duration of β bursts, the change of UPDRS under stimulated state and unstimulated state is well simulated, and a foundation for the future model-based closed-loop DBS research is laid.