Stimulation of novel spinal respiratory circuit to restore breathing in ventilator-dependent patients with SCI.

刺激新型脊髓呼吸回路以恢复依赖呼吸机的 SCI 患者的呼吸。

• 批准号: 10451685
• 负责人: Daniel Lu
• 金额: $ 127.64万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10451685
• 关键词: Acute; Air; Algorithms; Area; Behavior; Behavioral; Brain Stem; Breathing; Cause of Death; Cervical; Cervical spinal cord injury; Cervical spine; Cessation of life; Chronic; Clinical; Communication; Complex; Dangerousness; Data; Dorsal; Dose; Electric Stimulation; Electrodes; Electrophysiology (science); Enrollment; Goals; Hand; Impaired health; Implant; Location; Lung; Mechanical ventilation; Mechanics; Morbidity - disease rate; Motor output; Muscle function; Neurologic; Neurostimulation procedures of spinal cord tissue; Operative Surgical Procedures; Output; Pain; Pathway interactions; Patient Selection; Patients; Pattern; Physiological; Pump; Quality of life; Recovery; Recovery of Function; Rehabilitation therapy; Research; Residual state; Respiration; Respiratory Failure; Respiratory Muscles; Respiratory physiology; Risk; Sensory; Site; Spinal; Spinal Cord; Spinal cord injury; Spinal cord injury patients; System; Testing; Therapeutic; Thinking; Training; Upper Extremity; Ventilator; Vertebral column; Weaning; cost; density; early phase clinical trial; functional gain; high risk; improved; injured; millisecond; mortality; muscle strength; nervous system disorder; neural circuit; neural network; neuromechanism; neuroregulation; novel; partial response; respiratory; response; restoration; safety and feasibility; safety assessment; ventilation

PROJECT SUMMARY/ABSTRACT Respiratory failure after spinal cord injury (SCI) impairs the health of the injured patients, and respiratory failure is the leading cause of death in patients with SCI. Treatment of respiratory failure consists of mechanical ventilation, in which a mechanical pump is used to facilitate air exchange with the lungs. Mechanical ventilation is invasive, costly, limiting, and carries with it a high risk of complications and death. Mechanical ventilation provides an unvarying pattern of ventilation that is not responsive to physiological demands; it does not recapitulate normal breathing. Normal breathing is a complex behavior under both voluntary and involuntary neural control; it is responsive (in milliseconds or less) to the physiological state of the patient. Restoration of fully integrated, naturalistic breathing would represent a significant advance in the treatment of respiratory failure following SCI. The main hurdle to accessing the neural network for breathing for therapeutic purposes is that the neural mechanisms controlling respiration reside deep in the brainstem, which is dangerous to access surgically. Recently, we elucidated a novel breathing pathway in the spinal cord that can be modulated by electrical stimulation of the cervical spine, an area that is surgically accessible. We have compiled significant data that stimulating the cervical spine can restore or augment breathing. Clinically approved epidural spinal cord stimulators exist to treat pain, and these stimulators can also be used to stimulate the cervical spine to restore respiratory function. The main objective of this project is to provide proof of the concept that cervical epidural stimulation can improve respiratory function in ventilator-dependent patients with SCI and define the stimulation parameters that most effectively restore more normal breathing. The deliverables for this 5-year project include establishing the safety and feasibility of epidural stimulation for respiratory rehabilitation in SCI and providing an algorithm to select the optimum stimulation variables to augment respiratory activity in each patient (e.g., stimulation site, dose, and timing). If successful, we anticipate using epidural stimulation to partially or completely wean each patient with SCI off mechanical ventilation, which would have immediate benefits — increased independence, improved quality of life, and decreased costs and risks associated with mechanical ventilation. Conventional thinking is that once the spinal cord is injured, little or no functional recovery is possible. This dire sense of irrreversibility is at odds with our research in spinal cord neuromodulation, which has shown that substantial recovery of voluntary hand and upper extremity function can result from epidural spinal cord stimulation. A similar neurmodulatory strategy may be used to augment or restore respiratory function in patients with SCI. If successful, this neuromodulatory strategy to restore respiratory function may usher in a new era of respiratory neurorehabiltitation for SCI, and potentially other neurological disorders, and transform our understanding of neural circuits governing respiration and the plasticity of injured states of the spine.

项目概要/摘要 脊髓损伤（SCI）后的呼吸衰竭会损害受伤患者的健康，并且呼吸衰竭 是 SCI 患者死亡的主要原因。呼吸衰竭的治疗包括机械治疗 通气，其中使用机械泵促进与肺部的空气交换。机械通气 它是侵入性的、昂贵的、限制性的，并且伴随着并发症和死亡的高风险。机械通气 提供对生理需求不敏感的不变的通气模式；它没有 重述正常呼吸。正常呼吸是有意识和无意识下的复杂行为 神经控制；它对患者的生理状态做出响应（以毫秒或更短的时间）。恢复 完全整合的自然呼吸将代表呼吸衰竭治疗的重大进步 继SCI。访问神经网络进行呼吸治疗的主要障碍是 控制呼吸的神经机制位于脑干深处，通过手术进入是危险的。 最近，我们阐明了脊髓中的一种新型呼吸通路，可以通过电调节 刺激颈椎，这是一个可以通过手术到达的区域。我们编制了重要数据 刺激颈椎可以恢复或增强呼吸。临床批准的硬膜外脊髓 刺激器的存在是为了治疗疼痛，这些刺激器也可以用来刺激颈椎恢复 呼吸功能。该项目的主要目标是证明颈椎硬膜外麻醉这一概念 刺激可以改善依赖呼吸机的 SCI 患者的呼吸功能并定义刺激 最有效恢复正常呼吸的参数。这个为期 5 年的项目的可交付成果包括 建立硬膜外刺激用于 SCI 呼吸康复的安全性和可行性，并提供 选择最佳刺激变量以增强每位患者呼吸活动的算法（例如， 刺激部位、剂量和时间）。如果成功，我们预计使用硬膜外刺激来部分或完全 让每位 SCI 患者脱离机械通气，这将带来立竿见影的好处——增加 独立，提高生活质量，并降低与机械通气相关的成本和风险。 传统的想法是，一旦脊髓受伤，功能恢复的可能性很小或根本不可能。这可怕的 不可逆性的感觉与我们对脊髓神经调节的研究不一致，该研究表明 硬膜外脊髓可以使手和上肢功能得到实质性恢复 刺激。类似的神经调节策略可用于增强或恢复患者的呼吸功能 与SCI。如果成功，这种恢复呼吸功能的神经调节策略可能会开创一个新时代 SCI 和潜在的其他神经系统疾病的呼吸神经康复，并改变我们的 了解控制呼吸的神经回路和脊柱受伤状态的可塑性。

项目成果

Cervical Epidural Electrical Stimulation Increases Respiratory Activity through Somatostatin-Expressing Neurons in the Dorsal Cervical Spinal Cord in Rats.

• DOI: 10.1523/jneurosci.1958-21.2022
• 发表时间: 2023-01-18
• 期刊: JOURNAL OF NEUROSCIENCE
• 影响因子: 5.3
• 作者: Galer, Erika L.;Huang, Ruyi;Madhavan, Meghna;Wang, Emily;Zhou, Yan;Leiter, James C.;Lu, Daniel C.
• 通讯作者: Lu, Daniel C.

Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration.

• DOI: 10.1038/s41598-021-82694-3
• 发表时间: 2021-02-17
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Huang R;Nikooyan AA;Xu B;Joseph MS;Damavandi HG;von Trotha N;Li L;Bhattarai A;Zadeh D;Seo Y;Liu X;Truong PA;Koo EH;Leiter JC;Lu DC
• 通讯作者: Lu DC