Approximately 3 million individuals suffer from traumatic brain injury (TBI) annually, with over 50,000 expected to die as a result of their injury. In these most severe cases, patients are typically admitted to the intensive care unit (ICU) for continuous monitoring and treatment of their injury. Standard monitoring includes implantation of an intracranial pressure (ICP) sensor, arterial blood pressure (ABP) monitoring, and occasional imaging studies (typically with CT). The objective of these monitoring strategies is to detect evolving pathology in a timely manner so that treatment can be provided to these patients prior to their injury escalating to a point at which treatment becomes ineffective. Unfortunately, these strategies are limited in their ability to detect worsening conditions. Spiking ICP represents a global measure of worsening status, however it provides no localizing information and typically reaches levels of concern (>20 mmHg) much later than is clinically desired. ABP sensing coupled with ICP represents a surrogate measure of cerebral perfusion pressure, but is difficult to accurately gauge. Occasional image studies provide exquisite intracranial details, but are difficult to administer in heavily instrumented ICU patients and are only acquired occasionally, often after injury has begun to progress. We propose to overcome the limitations of current monitoring strategies by developing a small form- factor, real-time continuous monitor, able to spatially map evolving intracranial trauma. Specifically, we propose to use an adapted form of electrical impedance spectroscopy for this purpose. Our novel approach leverages both scalp and intracranial electrodes to map dynamic intracranial impedance changes associated with fluid and tissue alterations resulting from trauma. We have demonstrated in a pilot animal study that this type of modality is capable of detecting intracranial changes due to mass effect, hematoma, and brain death. During this program we will take the significant step of developing this technology for commercial deployment and demonstrating proof of feasibility in an animal model using intraoperative CT scanning. Because this system is being designed to minimally augment an already existing clinical protocol (designed to interface with a heavily instrument patient in the ICU), is relatively inexpensive (<$10k for an electrical impedance acquisition system), and is potentially able to detect evolving intracranial injury prior to current clinically-accepted technologies, this technology has the potential of being easily translated to and accepted by the clinic for the benefit of continuously monitoring patients following TBI. We expect that by the end of this program we will be in a position to submit a Phase II application that will focus on optimizing our technology and conducting a larger sample size animal model trial to demonstrate efficacy of our intracranial impedance mapping technique.

Public Health Relevance

Current clinical practices using continuous intracranial pressure (ICP) monitoring along with CT images acquired every few hours to monitor patients with TBI unfortunately do not provide clinicians with early enough warning to adequately treat evolving injury. Bioimpedance sensing is a method by which intracranial pathology can be safely and continuously monitored in patients with TBI. We have demonstrated that bioimpedance signatures are related to this evolving TBI pathology; we aim to take the significant step of designing a marketable impedance-sensing device that can be used in the intensive care unit (ICU) and demonstrating feasibility of device deployment in a novel animal model.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Small Business Technology Transfer (STTR) Grants - Phase I (R41)
Project #
1R41NS100313-01
Application #
9255913
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Fertig, Stephanie
Project Start
2017-01-01
Project End
2018-12-31
Budget Start
2017-01-01
Budget End
2018-12-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Rytek Medical, Inc.
Department
Type
DUNS #
078304657
City
Lebanon
State
NH
Country
United States
Zip Code
03766