CRCNS: US-Spain Research Proposal: Computational Modeling of PNS Stimulation

CRCNS：美国-西班牙研究提案：PNS 刺激的计算模型

基本信息

批准号：
10163843
负责人：
GIANLUCA LAZZI
金额：
$ 28.28万
依托单位：
UNIVERSITY OF SOUTHERN CALIFORNIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10163843
关键词：
3-Dimensional Acute Address Anatomy Axon Charge Chronic Communities Computer Assisted Computer Models Computer software Computing Methodologies Coupled Development Dissection Drug or chemical Tissue Distribution Effectiveness Electrodes Electromagnetic Fields Electromagnetics Engineering Frequencies Generations Geometry Goals Histologic Histology Human body Implant International Link Magnetism Methods Modeling Nerve Nerve Fibers Neurons Pattern Peripheral Peripheral Nerves Phase Property Rattus Rehabilitation device Research Proposals Resolution Safety Sampling Software Framework Spain Structure System Time Tissue Model Tissues Vagus nerve structure Validation axon injury base computational platform computer framework computerized tools density design dielectric property electric impedance improved in vivo multi-scale modeling reconstruction relating to nervous system response safety assessment sciatic nerve three-dimensional modeling tool

项目摘要

The goal of the proposed effort is to develop and make available to the scientific community a modular, integrated, multiscale computational modeling framework that will allow the user to design safe and effective peripheral neurostimulators. The multiscale computational framework is based on the seamless integration of multiple computational modules/platforms particularly suited for integration: (a) a multi- resolution, frequency-domain, large-scale electromagnetic field modeling platform based upon our Admittance/Impedance Method (AM/IM) for the prediction of fields and currents induced in the neural tissue by arbitrary neurostimulators; (b) micron-resolution computational models of the bulk electrical and magnetic properties of axons and their excitation in peripheral nerve models of mammalians using NEURON software, coupled in space and time to the Admittance/Impedance Method; (c) a computational tool for the estimation of direct, electrically or magnetically-induced, tissue and neural damage due to arbitrary, user-defined, peripheral neurostimulators and waveforms and for the estimation of activity- based early axonal damage (EAD) based on correlation with experimentally observed damage in chronically implanted neurostimulators. The development of the proposed modules will provide the most complete predictive software framework available to assess acute and activity-based safety of peripheral neurostimulators due to parameters including electrode geometric::al features, charge density, charge per phase, frequency of stimulation and thermal increase. To the best of our knowledge, there is no computational method readily available that addresses both the effectiveness of the neurostimulator (modeling of the excitation in peripheral nerve models due to arbitrary electrode geometries and waveforms) and the safety of the neurostimulator both at the large-scale (electromagnetic tissue models of the human body based on high-resolution, dielectric properties- based, discretized computational models) and at micron-resolution (neural level). The proposed effort will consists of a) generation of computational models of peripheral nerves; b) development of the computational modules and platform; and c) experimental verification of the predictive capabilities of the computational models and platform.

拟议的努力的目的是开发并为科学界提供一个模块化，集成的多尺度计算建模框架，该框架将允许用户设计安全和有效的周围神经刺激剂。多尺度计算框架基于无缝多个计算模块/平台的集成特别适合集成：（a）基于我们的分辨率，频域，大规模电磁场建模平台用于预测神经诱导的田间和电流的入学/阻抗法（AM/IM）通过任意神经刺激剂组织；（b）散装电气和的微分辨率计算模型使用轴突的磁性特性及其在哺乳动物的外周神经模型中使用神经元软件，在空间和时间上耦合到入学/阻抗方法；（c）计算用于估计直接，电或磁引起的，组织和神经损伤的工具任意，用户定义的，周围神经刺激器和波形，以估计活动基于与实验观察到的损害相关的早期轴突损伤（EAD）长期植入神经刺激剂。拟议模块的开发将提供最多的完整的预测软件框架可用于评估周围的急性和基于活动的安全性由于参数包括电极几何:: Al特征，电荷密度，充电相位，刺激的频率和热增加。据我们所知，没有任何计算方法容易解决神经刺激剂的有效性（由于任意而导致的外周神经模型中激发的建模电极几何和波形）和神经刺激器的安全性都在大尺度上（基于高分辨率，介电性能的人体电磁组织模型，离散的计算模型）和微分辨率（神经级）。拟议的努力将由a）外周神经的计算模型组成； b）发展计算模块和平台； c）实验验证的预测能力计算模型和平台。