Brain Wave Monitoring for Traumatic Brain Injury

(INDICT Trial)

Overseen By Karmen Herzig

Age: 18+

Sex: Any

Trial Phase: Phase 2

Sponsor: University of Cincinnati

Disqualifiers: Non-survivable injury, Pregnancy, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Prior Safety Data This treatment has passed at least one previous human trial

Approved in 3 Jurisdictions This treatment is already approved in other countries

Compensation: Varies

Number of Visits: Unknown

Duration: Up to 2 weeks

72 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial explores a new method for managing severe traumatic brain injuries by monitoring brain waves in real time. Researchers are testing whether using this brain wave data to guide treatment, known as the Treatment Algorithm, can control harmful brain activity and improve care. Participants may receive either this new experimental care or standard ICU care. Individuals who have undergone emergency brain surgery within 72 hours of a traumatic brain injury and meet other specific criteria may qualify for this trial. As a Phase 2 trial, this research measures the treatment's effectiveness in an initial, smaller group, offering participants a chance to contribute to significant advancements in care.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that this protocol is safe for traumatic brain injury patients?

Research has shown that using electrocorticography (ECoG) to monitor brain activity in people with traumatic brain injury (TBI) carries some risks. Studies indicate that over 25% of TBI patients might experience negative effects, such as seizures and blood vessel spasms. However, researchers are still studying the specific role of ECoG in guiding treatment.

Regarding the ketamine treatment in this trial, past studies have shown mixed results. Some research found that ketamine can lower pressure inside the skull, which benefits brain injury treatment. It was not linked to worse survival rates or increased disability, even in severely injured patients. However, concerns about raising this pressure have traditionally led to ketamine being avoided for TBI.

Since this study is in Phase 2, researchers are still assessing the safety of these treatments. This phase typically tests how well people tolerate the treatment and gathers more safety information. Prospective participants should know that while some evidence supports safety, more research is needed to confirm these findings. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Brain Wave Monitoring for Traumatic Brain Injury trial because it explores a novel approach to managing traumatic brain injuries by using real-time brain wave data to guide treatment. Unlike standard ICU care, which follows general guidelines, this method uses a customized algorithm to monitor specific brain activity, known as spreading depolarizations (SDs), to adjust treatment. This targeted approach could lead to more precise interventions, potentially reducing secondary brain injuries and improving patient outcomes. By focusing on SD suppression through a tier-based protocol, this trial could offer a more dynamic and responsive treatment strategy compared to current practices.

What evidence suggests that this trial's treatments could be effective for traumatic brain injury?

Research has shown that monitoring brain activity, particularly patterns called spreading depolarizations (SDs), can aid in managing severe traumatic brain injury (TBI). In this trial, participants in the SD-Guided Care arm will have their ECoG data reviewed in real-time to guide treatment decisions. Previous studies using electrocorticography (ECoG) demonstrated its ability to predict recovery by detecting these patterns, assisting doctors in determining the best treatment.

Additionally, the SD-Guided Care arm will incorporate ketamine into the treatment algorithm. Studies have shown that ketamine can significantly reduce intracranial pressure in TBI patients. Although ketamine was once avoided due to safety concerns, recent research indicates it does not adversely affect the brain's pressure and blood flow.

Together, these methods offer a promising approach to managing severe TBI in the SD-Guided Care arm of this trial. ^{5 6 7 8 9}

Are You a Good Fit for This Trial?

This trial is for individuals who need emergency surgery (craniotomy) to treat severe traumatic brain injury within 72 hours after the injury. It's not for those with non-survivable injuries, those who've had a certain type of skull surgery due to swelling, are in another TBI study, or are pregnant.

Inclusion Criteria

I need urgent brain surgery within 72 hours after a head injury.

Exclusion Criteria

I had surgery to relieve pressure inside my skull due to a severe brain injury.

Pregnancy

Co-enrollment in another therapeutic TBI trial

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Treatment

Participants undergo intensive care with real-time electrocorticographic monitoring to guide therapy for spreading depolarization suppression

Up to 2 weeks

Continuous monitoring during intensive care

Follow-up

Participants are monitored for safety and effectiveness after treatment

6 months

Periodic assessments

What Are the Treatments Tested in This Trial?

Interventions

• Full-band Electrocorticography
• Treatment Algorithm

Trial Overview

The INDICT study tests if monitoring brain activity with electrocorticography can help guide intensive care treatments aimed at stopping spreading depolarizations—a harmful pattern seen after brain injuries—in patients post-surgery.

How Is the Trial Designed?

Group I: SD-Guided Care Experimental Treatment 2 Interventions

In this arm, ECoG data will be reviewed for SDs in real-time using the bedside clinical CNS monitor. As a secondary measure, recognition of SDs will be facilitated by custom software on a laptop that receives data from the CNS monitor. Data on SD occurrence will be used to guide treatment in a tier-based therapeutic escalation and de-escalation protocol with the goal of SD suppression. Therapies to be used among the tiers include adjusted targets for MAP, CPP, PaCO2, plasma glucose, temperature, as well as ketamine pharmacotherapy. Changes between tiers are determined by the success or failure of SD suppression at the given treatment level.

Group II: Standard ICU Care Active Control 1 Intervention

Management in the Standard ICU Care arm will follow published national guidelines consisting of common ICU-based targets for physiologic intervention that are thought to mitigate the development of secondary brain injuries. Continuous ECoG monitoring will be performed for seizure monitoring, but information on the course of SDs in these patients will not be used to guide care. To enforce blinding to SD-related ECoG data, the ECoG bedside software will be locked with password protection to prevent displays with frequency filtering and time/amplitude scales that are necessary to identify SDs.

Treatment Algorithm is already approved in United States, European Union, Canada for the following indications:

Approved in United States as Ketalar for:

• Anesthesia
• Pain management
• Sedation

Approved in European Union as Ketalar for:

• Anesthesia
• Pain management
• Sedation

Approved in Canada as Ketalar for:

• Anesthesia
• Pain management
• Sedation

Who Is Running the Clinical Trial?

University of Cincinnati

Lead Sponsor

Trials

442

Recruited

639,000+

University of New Mexico

Collaborator

Trials

393

Recruited

3,526,000+

University of Pennsylvania

Collaborator

Trials

2,118

Recruited

45,270,000+

Published Research Related to This Trial

The paper highlights the limitations of traditional Fast Fourier Transforms (FFTs) in analyzing EEG signals, particularly issues with resolution and leakage effects, and introduces an auto-regressive (AR) modeling approach to improve spectral estimation.

It also presents advanced algorithms, including adaptive AR parameter estimation and wavelet-based time-frequency representation, which are particularly effective for analyzing transient or rapidly changing neurological signals, as demonstrated through EEG data from animals experiencing hypoxic asphyxic brain injury.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Spectral analysis methods for neurological signals. Muthuswamy, J., Thakor, NV.[2019]

A new algorithm has been developed to effectively detect and track rhythmic patterns in EEG signals, which is crucial for monitoring brain activity in patients.

The algorithm successfully tracked the alpha rhythm in critically ill patients sedated with midazolam, indicating its potential utility in clinical settings for assessing brain function.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Tracking rhythm in long-term EEG recordings using empirical mode calculation. Lipping, T., Anier, A., Ratsep, I., et al.[2020]

Current management of traumatic brain injury (TBI) focuses on preventing and treating secondary brain damage rather than relying solely on pharmacological agents, which have shown limited success in clinical settings.

Recent studies indicate that using multimodal monitoring techniques to guide TBI treatment can lead to better patient outcomes by allowing for personalized care based on individual patient needs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Physiological monitoring of the severe traumatic brain injury patient in the intensive care unit. Le Roux, P.[2022]

Long-term scalp EEG monitoring in 60 patients with acute severe traumatic brain injury (TBI) provides valuable insights into prognosis, with specific EEG features indicating a higher risk of unfavorable outcomes, such as background rhythm slowing and absence of reactivity.

The study found that certain EEG patterns, like rhythmic and periodic patterns, are strongly associated with non-convulsive status epilepticus (NCSE), suggesting that EEG monitoring can help in diagnosing this condition, although NCSE itself does not necessarily predict a poor outcome.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Long-term EEG monitoring in patients with acute traumatic brain injury]. Sinkin, MV., Talypov, AE., Yakovlev, AA., et al.[2021]

Multimodal monitoring tools, both invasive and noninvasive, are essential for managing critically ill patients with traumatic brain injury, as they help prevent secondary brain injury.

Over the past 20 years, there has been significant advancement in monitoring techniques, including intracranial pressure, blood flow, metabolism, and oxygenation, which are crucial for understanding and managing brain injury.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Advances in cerebral monitoring for the patient with traumatic brain injury. Mahdavi, Z., Pierre-Louis, N., Ho, TT., et al.[2017]

The management of head injury focuses on preventing secondary brain damage by addressing issues like raised intracranial pressure and ensuring adequate blood flow to the brain, which is crucial for improving patient outcomes.

Despite advancements in understanding the mechanisms of brain injury and the development of neuroprotective agents, there is still a lack of strong evidence supporting many treatment methods, highlighting the need for improved guidelines and monitoring techniques in clinical practice.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Current recommendations for neurotrauma. Maas, AI., Dearden, M., Servadei, F., et al.[2019]

The new depth of anesthesia (DoA) monitoring index effectively tracks the transition from consciousness to unconsciousness during anesthesia induction in real time, indicating its potential for improving patient safety.

The method enhances raw EEG data by removing noise and adjusting window lengths, which may lead to more accurate and reliable monitoring of anesthesia depth compared to traditional methods.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Measuring and reflecting depth of anesthesia using wavelet and power spectral density. Nguyen-Ky, T., Wen, PP., Li, Y., et al.[2011]

The QEEG algorithm demonstrated high sensitivity (92.45%) and specificity (90.00%) in distinguishing patients with traumatic brain injury (TBI) who required a CT scan from those who did not, based on EEG data from 105 patients.

The TBI discriminant index, which showed significant differences between CT+ patients (mean index of 80.4) and controls (24.5), could enhance triage decisions in the Emergency Department by indicating when a CT scan is necessary for patients with altered mental status.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Use of brain electrical activity to quantify traumatic brain injury in the emergency department. Naunheim, RS., Treaster, M., English, J., et al.[2019]

A mathematical analysis of 80 electroencephalograms (EEGs) from 20 patients with severe brain injuries revealed significant disturbances in the frequency spectrum, which can aid in diagnosis during acute care.

The study introduced an adaptive filtration system to assess spectral density, enhancing the ability to identify specific EEG patterns that are crucial for differentiating types of brain injuries.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Spectral analysis of the EEG in patients with cerebral contusions and traumatic intracranial hematomas]. Pishel', IaV., Khobta, VD., Kozhukhar', LS.[2006]

Citations

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pmc.ncbi.nlm.nih.gov

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In this study, we establish the feasibility of automated SD detection through noninvasive scalp electroencephalography (EEG) for patients with severe TBI.

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Continuous Electroencephalography after Moderate to ...

Sleep Features on Continuous Electroencephalography Predict Rehabilitation Outcomes After Severe Traumatic Brain Injury. The Journal of head trauma ...

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Prolonged negative cortical DC shift of SD recorded by ECoG in patients with subarachnoid hemorrhage points to the inverse hemodynamic response ...

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Predicting traumatic brain injury outcomes using a posterior ...

A posterior dominant rhythm on electroencephalography is strongly associated with positive outcomes and to develop a novel machine learning–based model.

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Prognostic Value of Electroencephalography in Critically Ill ...

Still, the EEG features described and their potential additional value in outcome prediction after TBI merit further investigation. Open in ...

6.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC5788886/

Detecting Cortical Spreading Depolarization with Full Band ...

The primary outcome measure for patients with traumatic brain injury was functional outcome as expressed by Extended Glasgow Outcome Scale at ...

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annaly-nevrologii.com

annaly-nevrologii.com/pathID/article/view/686

Electrocorticography in patients with severe traumatic brain ...

The frequency of adverse outcomes in patients with severe traumatic brain injury (TBI) exceeds 25%. Epileptic seizures and vasospasm, in the absence of ...

8.

sciencedirect.com

sciencedirect.com/science/article/pii/S2213158223000396

Early EEG monitoring predicts clinical outcome in patients ...

A total of hundred-seven patients with moderate to severe traumatic brain injury were included. Three patients were excluded due to lack of GOSE outcome scores ...

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nature.com

nature.com/articles/s43856-023-00344-3

Noninvasive and reliable automated detection of spreading ...

Increasing evidence shows that SDs are associated with poor clinical outcomes in traumatic brain injuries (TBIs), strokes, and hemorrhages4,5,6, ...