Elixmann Inga M, Kwiecien Monika, Goffin Christine, Walter Marian, Misgeld Berno, Kiefer Michael, Steudel Wolf-Ingo, Radermacher Klaus, Leonhardt Steffen
IEEE Trans Biomed Eng. 2014 Sep;61(9):2379-88. doi: 10.1109/TBME.2014.2308927.
Hydrocephalus is characterized by an excessive accumulation of cerebrospinal fluid (CSF). Therapeutically, an artificial pressure relief valve (so-called shunt) is implanted which opens in case of increased intracranial pressure (ICP) and drains CSF into another body compartment. Today, available shunts are of a mechanical nature and drainage depends on the pressure drop across the shunt. According to the latest data, craniospinal compliance is considered to be even more important than mean ICP alone. In addition, ICP is not constant but varies due to several influences. In fact, heartbeat-related ICP waveform patterns depend on volume changes in the cranial vessels during a heartbeat and changes its shape as a function of craniospinal compliance. In this paper, we present an electromechanical shunt approach, which changes the CSF drainage as a function of the current ICP waveform. A series of 12 infusion tests in patients were analyzed and revealed a trend between the compliance and specific features of the ICP waveform. For waveform analysis of patient data, an existing signal processing algorithm was improved (using a Moore machine) and was implemented on a low-power microcontroller within the electromechanical shunt. In a test rig, the ICP waveforms were replicated and the decisions of the ICP analysis algorithm were verified. The proposed control algorithm consists of a cascaded integral controller which determines the target ICP from the measured waveform, and a faster inner-loop integral controller that keeps ICP close to the target pressure. Feedforward control using measurement data of the patient's position was implemented to compensate for changes in hydrostatic pressure during change in position. A model-based design procedure was used to lay out controller parameters in a simple model of the cerebrospinal system. Successful simulation results have been obtained with this new approach by keeping ICP within the target range for a healthy waveform.
脑积水的特征是脑脊液(CSF)过度积聚。在治疗上,会植入一个人工减压阀(即所谓的分流器),当颅内压(ICP)升高时该阀会打开,将脑脊液引流到身体的另一个腔室。如今,现有的分流器是机械性质的,引流取决于分流器两端的压力差。根据最新数据,颅脊髓顺应性被认为比单纯的平均颅内压更为重要。此外,颅内压并非恒定不变,而是受多种因素影响而变化。实际上,与心跳相关的颅内压波形模式取决于心跳期间颅内血管的容积变化,并根据颅脊髓顺应性改变其形状。在本文中,我们提出了一种机电分流方法,该方法可根据当前的颅内压波形改变脑脊液引流。对患者进行的一系列12次输液测试进行了分析,结果揭示了顺应性与颅内压波形特定特征之间的一种趋势。为了对患者数据进行波形分析,对一种现有的信号处理算法进行了改进(使用摩尔机),并在机电分流器内的低功耗微控制器上实现。在一个测试装置中,复制了颅内压波形,并验证了颅内压分析算法的决策。所提出的控制算法由一个级联积分控制器组成,该控制器根据测量到的波形确定目标颅内压,以及一个更快的内环积分控制器,该控制器使颅内压接近目标压力。采用基于患者位置测量数据进行前馈控制,以补偿体位改变时静水压的变化。基于模型的设计程序被用于在脑脊液系统的一个简单模型中设置控制器参数。通过将颅内压保持在健康波形的目标范围内,这种新方法已获得了成功的模拟结果。