Multimodal Monitoring of Cerebral Autoregulation After Pediatric Brain Injury

Traumatic Brain Injury Clinical Trial

Official title:

Multimodal Monitoring of Cerebral Autoregulation After Pediatric Brain Injury

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04242602
• Other study ID #: STU042018-056
• Status: Recruiting
• Phase: N/A
• Start date: November 6, 2018
• Est. completion date: January 2025

Study information

• Verified date: February 2024
• Source: University of Texas Southwestern Medical Center
• Contact: Danyal Thaver
• Phone: 2144567592
• Email: danyal.thaver[@]utsouthwestern.edu
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Various methods have been studied to evaluate autoregulation. However, there is currently no universally accepted technique to assess integrity of the cerebral autoregulation neurovascular system. In the last decade, significant progress has been achieved in developing methods to assess cerebral autoregulation by quantifying cross-correlation between spontaneous oscillations in CBF or oxygenation and similar oscillations in arterial blood pressure.

In this study the investigators will analyze the relationship between spontaneous fluctuations in mean arterial blood pressure and cerebral blood flow velocity or cerebral regional oxygenation to investigate two novel methods for measuring cerebral autoregulation, Transfer Function Analysis and Wavelet Coherence after acute pediatric brain injury.

Description:

A. Background and Purpose

Acute neurologic injury (ANI) is an important and common cause of mortality and morbidity in pediatrics such as traumatic brain injury (TBI), stoke and hypoxic-ischemic encephalopathy (HIE). Advances have been made in the intensive care management of children with ANI improving mortality rates but survivors are often left with long-term neurologic and neuropsychological disabilities. It is estimated that as many as 50-60% of children who sustain a severe TBI will suffer from some long-term neurologic sequela such as cognitive, behavioral, psychiatric and psychological defects despite modern advanced care. Survivors of ANI may also sustain a reduction in their quality of life and ability to participate in daily activities and their long-term care can results in a considerable socioeconomic burden. The brain is a highly metabolic organ representing 2% of the total body weight but consuming 20% of the oxygen. The dependence of the brain on a high rate of aerobic cellular metabolism necessitates a continuous supply of oxygen and glucose. However, this large energy requirement also means that brain cells are particularly vulnerable to injury when nutrients are deprived even for very short periods. The delivery of cerebral energy nutrients is a highly controlled process maintained through an intricately balanced cerebrovascular system, which regulates cerebral blood flow (CBF) at a constant rate to meet tissue demand. In the simplest model CBF is proportional to the pressure differential across the cerebrovascular system and is inversely proportional to the cerebral vascular resistance (CVR). The driving pressure differential or cerebral perfusion pressure (CPP) represents the vascular pressure difference across the brain tissue, expressed as the mean arterial pressure (MAP) minus the intracranial pressure (ICP).

In normal physiologic states CBF is largely independent of CPP over a wide range of pressure by altering CVR, a process known as cerebral autoregulation (CA). Cerebral autoregulation is controlled by the complex interplay of neurogenic, metabolic and myogenic mechanisms. During CA arterioles in the brain dilate (decreasing resistance) or constrict (increasing resistance) maintaining an adequate CBF to meet tissue metabolic demands (Figure 1). After ANI the endogenous autoregulatory mechanisms may be impaired predisposing vulnerable tissue to ischemia or vasogenic edema. In the normal state CA maintains a constant CBF over a wide rage of perfusion pressures but with loss of CA CBF becomes linear with perfusion pressure such that any reduction in CPP or MAP will cause a corresponding fall in blood flow. After severe TBI, cardiac arrest or spontaneous intracranial hemorrhage, children may suffer from a combination of cerebral and systemic pathophysiologic alterations such as hypotension, shock, cerebral edema, increased intracranial pressure, acute blood loss anemia and respiratory failure. Therefore, the biologic system of CA is a clinically important mechanism that functions to protect against cerebral hypoperfusion or hyperperfusion during the pathophysiologic changes that occur commonly in neurocritical illness where patients may have rapid changes in blood pressure, intracranial pressure or systemic oxygen delivery.

Cerebral blood flow is not directly measured at the bedside in clinical practice hence either CPP (if ICP is measured) or MAP is used to target an age-based goal in clinical practice. However, there are several limitations with this approach, 1) the optimal MAP/CPP threshold is unknown in children across age groups, 2) the optimal MAP/CPP value is very likely to not only be reflected by age-based target but be highly dependent on individual patient and injury-type factors and 3) due to this uncertainty there exists wide clinical variability is what value medical providers choose to target MAP/CPP after ANI. Moreover, since autoregulation is a continuous spectrum dependent on the adaptive response of CVR to regulate flow, disturbances may change over time and may also differ in the same patient with varying degrees of physiological derangement. Since CBF is not measured in clinical practice the actual ability of the patient to maintain an adequate CBF at a given MAP/CPP is assumed but not known. Relying on perfusion pressure alone fails to account for alterations in CA that occur after brain injury hindering the clinician's ability to determine if CBF is adequate to meet metabolic needs at a given MAP/CPP

There are emerging studies supporting the theory that impaired CA is an important factor in ANI. In adults impairments in CA are associated with a worse outcome and have been demonstrated to occur after a wide-spectrum of neurologic injuries, including TBI, HIE, subarachnoid hemorrhage and stroke.

Similar reports of poor outcomes after pediatric TBI and neonatal and pediatric HIE with have been found impaired in patients with impaired CA. However, significant knowledge gaps still exist in our current understanding of how to measure CA, which patients are at risk for impaired CA, if alterations in CA are associated with worse long-term functional outcomes and importantly how can the investigators use data from the patient's CA status to optimize our ICU management to improve outcomes. Current management options for children after severe TBI and intracranial hemorrhage may include the use of an invasive ICP monitor and arterial line to measure arterial blood pressure (ABP) and CPP continuously but these devices by themselves do not provide information about the status of the cerebrovascular system. Our study aims to utilizing two novel non-invasive methods of assessing dynamic autoregulation to describe the incidence and temporal profile of CA disturbances during the acute phase after ANI in children incorporating clinical data provided by the patient's current existing monitoring devices. The investigators also aim to examine the association between impaired CA and short and long-term functional neurologic outcome. This research proposal attempts to address some of our knowledge gaps in determination of CA disturbances and optimal MAP/CPP targets for children after ANI. The investigators hope this study will increase our understanding of CA impairments that occur after ANI and data gained from this study will lead to clinically useful tools incorporating CA assessment at the bedside to improve care for pediatric neurocritical care patients.

Methods of Assessing Dynamic Cerebral Autoregulation Various methods have been previously studied to evaluate CA and currently there is no universally accepted method to assess the integrity of the cerebral autoregulation neurovascular system. Measurements of CA have been described in terms of a static or dynamic process. Static CA relates to the net change in CBF following the manipulation of ABP under steady state conditions typically with drugs that either increase or decrease blood pressure. In this method if CBF remained constant with changes in ABP, autoregulation is deemed to be intact. Dynamic CA describes the fast mechanisms that permit restoration of blood flow after rapid changes in ABP, which typically occur over longer periods of time. Traditional methods to study of CA use techniques such as vasopressor administration, squat maneuver, carotid compression and deflation of thigh cuffs to induce large fluctuation in blood pressure to measure the CBF response. However, these maneuvers rely on patient cooperation and may be unsuitable in cases of neurocritical illness. In the last decade, advances have been made in developing new methods to assess the dynamic cerebral autoregulation (dCA) response by quantifying cross-correlation between spontaneous oscillations in MAP and CPP and the corresponding oscillations in CBF or oxygenation as opposed to experimental induced changes. While spontaneous oscillations in ABP and CBFv have been known to occur for many years, the function of these oscillations remain unknown. They are believed to originate as autonomic responses generated in the brainstem and peripheral baroreceptors. The cerebral arterioles response to changes in ABP may not be rapid enough to counteract high frequency changes hence fluctuations at these frequencies are passed along unmodified to cerebral circulation. In contrast, slower frequency oscillations (0.02 Hz to 0.2 Hz can be counteracted by cerebral arterioles to maintain constant flow. It is at these low frequency or slow waves periods that CA is believed to function as system to changes in ABP. Transfer function analysis and wavelet coherence analysis are mathematical models allowing simultaneous analysis of CA input and outputs over a wide range of physiologically relevant CA oscillatory frequencies. Measurements are interpreted based on the concept that dCA will work to minimize the effect of spontaneous oscillations in MAP on CBFv. Without a functional CA response each spontaneous oscillation in MAP would be associated with a similar oscillation in CBFv in terms of magnitude, duration and frequency. The investigators will combine two non-invasive techniques to investigate the temporal dCA relationship after ANI using spontaneous fluctuations of the patient's MAP or CPP as the input and CBFv or brain regional oxygenation as the output. Importantly, the two methods the investigators will be investigating utilize spontaneous fluctuations of a patient's physiologic waveforms. This eliminates the requirement for an experimental manipulation of blood pressure, which may introduce some risk to the patient. In the first method a 30-minute transcranial doppler (TCD) sonographic examination will be performed to analyze the transfer function analysis (TFA) of spontaneous oscillations of MAP/CPP and CBFv on days 1-10 after injury. In the second method, the investigators will examine dCA changes that occur continuously over the first 7-10 days of injury using a non-stationary model of wavelet coherence analysis between MAP/CPP and cerebral tissue oxygen saturation. In both models the investigators will be using MAP/CPP values measured from an indwelling arterial line placed as part of standard medical care.

Transfer Function Analysis (TFA) Transfer function analysis is a mathematical model to describe the spontaneous fluctuations in MAP and cerebral blood flow velocity (CBFv) which can analyze both static and dynamic components of CA. In the time-domain mean values of ABP and CBFv are obtained for each cardiac cycle and the spectral analysis algorithm Fast Fourier Transform is used to obtain spectral estimates in the frequency domain used to calculate coherence, gain and phase to describe the efficiency and latency of the CA frequency response across very low (VLF: 0.02-0.07 Hz), low (LF: 0.07-0.20 Hz), and high (HF: 0.20-0.50 Hz) frequency ranges. The analysis is based on the assumption that autoregulation functions in a "stationary" linear system with MAP considered the input and CBFv as the output. The analysis will be performed during a period of patient stability where no acute interventions will be made. Data acquisition settings and subsequent analysis for TFA will be in accordance with the white paper from the international cerebral autoregulation research network. A control group of patients will be enrolled as part of this study with arterial lines but without neurologic injury and have CBFv and TFA performed to serve as the comparison group.

Wavelet Coherence Analysis (WCA) Near-infrared spectroscopy (NIRS) is a non-invasive light emitting electrode method to measure regional tissue oxygenation. Probes sensitive to light absorption by oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (Hb) can be placed directly on the skin of the forehead to measure cerebral tissue oxygen saturation (SctO2) or the differential hemoglobin concentration (HbD = HbO2 - Hb). The SctO2 has been used as a non-invasive method to measure changes in regional cerebral perfusion or blood flow to assess CA. Spontaneous oscillations in CBF can therefore be estimated by changes in SctO2 values over time and analyzed against changes in MAP. Previous studies have used a linear correlation coefficient to analyze the relationship between SctO2 and MAP in adult and pediatric studies to assess dCA after cardiac surgery, subarachnoid hemorrhage and TBI. These prior analytical methods are based on the assumption of obtaining measurements in a stationary system, in other words the neurovascular and systemic hemodynamics do not change over time. In reality the investigators know that blood pressure and cerebral factors such as ICP and blood pressure are non-stationary, changing frequently, particularly in the early hours and days after critical illness. Wavelet coherence analysis assumes a non-stationary system and may be able to better characterize dCA disturbances in a continuous moving system during the real-time physiological changes that occur at the extremes of system stress not testable by previous methods. Wavelet coherence analysis can also be used to quantify the dynamic relationship between MAP and SctO2 across much longer time frames compared to TCD based analysis. Similar to TFA, wavelet coherence uses phase, gain and coherence to determine a relationship between the two waveforms values MAP/CPP and SctO2. Using NIRS-based SctO2 to measure changes in CBF has the advantages of being a stable sensor not subject to movement disturbances, a non-invasive routine monitor in the critical care unit and a method that requires no specialized training and is suitable for long-term continuous monitoring. A control group of patients will be enrolled as part of this study without neurologic injury but with arterial lines and NIRS monitoring to serve as the comparison group by having wavelet coherence analysis performed of MAP and SctO2 for 72 hours.

B. Study Aims

Aim 1: Utilize transfer function analysis to analyze the cerebral autoregulation gain and phase values across very low (VLF: 0.02-0.07 Hz), low (LF: 0.07-0.20 Hz), and high (HF: 0.20-0.50 Hz) frequency ranges of MAP/CPP and CBFv after acute brain injury on post-injury days 1-10.

Aim 2: Utilize wavelet coherence analysis to analyze the coherence values of continuously measured MAP/CPP and regional cerebral oxygenation saturation across time and period domains during post-injury days 1-10 days in brain injured patients.

Aim 3: Assess the functional outcome of between patients who demonstrate disturbed cerebral autoregulation using hospital discharge, 3 and 6 months post-injury neurologic measurements.

C. Study Design

C.1 Concise Project Summary In this study, the investigators will use two non-invasive methods to investigate temporal changes in dynamic CA by performing cross-correlation analysis of spontaneous fluctuations in MAP/CPP with cerebral blood flow velocity and cerebral regional oxygenation domains to examine CA disturbances after acute pediatric acute neurologic injury. In the first method, the investigators will uses transfer function analysis of MAP/CPP and TCD-based CBFv waveforms to measure CA components gain and phase on post injury days 1, 2, 3, 5, 7 and 10. This model assumes a stationary system as is performed for 30 minutes during a period of patient stability. In the second method, the investigators will utilize wavelet coherence analysis of MAP/CPP and NIRS-based tissue oxygen saturation (StO2) and to measure the continuous and dynamic CA changes occurring over a wide range of patient physiologic variables during the first 7-10 days after injury. This model allows for measurement of CA assuming a non-stationary system which more accurately reflects the actual pathophysiological and biologic disturbances that occurs in patients during the first days after neurocritical injury. For comparison with normal CA values, the investigators will use a control group of patients without any neurologic injury who are already intubated and sedated per standard of care. The study and control group will have arterial lines placed as part of their standard care to measure MAP for study analysis. The primary analyses will be conducted using two mathematical models of spontaneous oscillations in physiologic waveforms using continuous MAP/CPP as the CA input, and CBFv (TFA) or cerebral regional oxygenation (wavelet coherence) as the CA output. The investigators will also measure the impact that CA has on functional outcomes by measuring pediatric neurologic functional and disability scales at hospital discharge, 3, 6 and 12 months. Advancing our knowledge of the temporal changes that occur in CA during the initial critical phases of brain injury will lead to a better understanding of how the brain regulates flow after injury preventing secondary ischemia and help to develop patient-specific physiologic targets for MAP or CPP to optimize CBF accounting for the heterogeneity and individual differences in patients improving neurologic outcomes.

C.2 Description of Infrastructure All study patients will be enrolled at Children's Medical Center Dallas. Data collection will be through both paper case report forms, review of the electronic medical record and direct subject data download from the bedside Phillips Intellivue monitor. Dr. Miles (PI) is an Assistant Professor of Pediatrics at UTSW Medical Center and has been an attending in the pediatric intensive care unit (PICU) since 2005. Dr. Miles will provide direct supervision for the research study and has experience in both TCD techniques and conducting clinical trials in the PICU. Dr. Miles currently has the following research equipment obtained for this study, 1) specialized portable workstation with personal computer, display and DWL transcranial doppler device for measurement of CBF velocities and simultaneous download of MAP and CBFv with Medicollector software, 2) additional PC and smaller workstation for continuous NIRS data for continuous Phillips monitor data capture with Medicollector software and 3) two specially designed sets of pediatric headpieces with portable TCD probes for measurement of 30 minute continuous TCD waveform. Wavelet coherence analysis of CA will be carried out in collaboration with Dr. Fenghua Tian Ph.D, a faculty member in the Department of Bioengineering at University of Texas at Arlington. Dr. Tian's research expertise includes the use of NIRS and noninvasive methods to measure CA and several publications using wavelet coherence investigating CA in neonates after HIE and children receiving extracorporeal support. Dr. Tian will also provide statistical analytical support. Transfer function analysis of CA will be carried out in collaboration with Dr. Sushmita Purkayastha, Assistant Professor in the Department of Applied Physiology and Health Management at Southern Methodist University. Dr. Purkayastha laboratory examines the link between clinical symptoms of mild traumatic brain injury and cerebral blood flow regulation. She is currently using similar methods of TFA to study changes in CA after concussion in college athletes and has published results in patients with stroke and white matter abnormalities. Laurence Ryan Ph.D. will provide computer-engineering support and statistical analysis creating a custom MatLab (Mathowrks, Natick, MA) software code for signal processing of waveform CBFv and MAP data into TFA frequency plots.

C.3 Study Measures The study measures for aim 1 will be mean estimates of transfer function gain (cm/s/mmHg), phase (radians) and coherence for very low (VLF: 0.02-0.07 Hz), low (LF: 0.07-0.20 Hz), and high (HF: 0.20-0.50 Hz) frequency ranges calculated from MAP and CBFv spontaneous oscillations. Study measures for aim 2 study measures include calculation of squared cross-wavelet coherence (R2) ranging from 0-1 which represents the significance of correlations in spontaneous oscillations in MAP and SctO2 values during the first 7-10 days of injury. In this model an R2 value of 1 represent impaired autoregulation correlation where changes in MAP are significantly correlated with changes in cerebral oxygenation. A non-significant value would indicate spontaneous fluctuations in SctO2 are largely unconnected to changes in MAP. A squared cross-wavelet coherence threshold value of > 0.7 will be used for significance and will be plotted across patient monitoring time (X axis) and frequency or period (Y axis). In this model much lower frequency oscillations are being measured than for TFA for analysis ranging from 30 minutes to 256 minutes. The percentage of total monitoring time with significant cross-wavelet MAP and SctO2 coherence will be measured for each patient.

C.4 Study Timeline Study activities will continue for a 3-year period or when a target enrollment of 35 subjects has been reached. Based on historical numbers of annual admission for severe TBI, stroke and HIE mechanisms in the PICU the investigators would anticipate reaching the study target within the study time frame with an consent refusal/missed eligibility rate of 20-40%. Given the non-invasive and observational nature of the study the investigators hope the consent rate will be high for this study. Including children with various types of acute neurologic injury should also contribute to reaching the target enrollment within the study time frame. Neurologic follow-up will continue for 12 months after hospital discharge from the last patient enrolled.

D. Study Procedures

D1. Transcranial Doppler Sonography Study team personnel will perform transcranial doppler (TCD) sonography on post-injury days 1, 2, 3, 5, 7 and 10 to insonate the right and left middle cerebral artery mean, peak and diastolic flow velocities (cm/sec) via the temporal bone window. TCD uses ultrasound waves to measure the speed of moving blood in intracranial blood vessels. Since the blood flow velocity and vessel signal acquisition is very sensitive to probe movement, for continuous monitoring purposes a fixed probe device pediatric headpiece (LAM-Rack or Elastic Headband, DWL, Germany) will be used. This headpiece uses either a fixed metal frame or soft silicone straps to secure the TCD probes to the surface of the skull after the vessel signal is obtained. The headpiece has soft foam attachments and should not cause discomfort. Head circumference will be measured and using the standard 10 mm left and right of midline the middle cerebral artery/anterior cerebral artery (MCA/ACA) bifurcation will be identified first by a hand held probe where optimal insonation position will first be marked in the optimal position with a sharpie felt pen on the skin. This will allow for quicker and more consistent placement with the fixed headpiece for subsequent measurements. The investigators will use the mid MCA or most optimal signal for each patient but the same depth of MCA vessel will be used for repeated measurements. This procedure requires 20-30 minutes of continuous TCD measurements and the co-existing MAP waveform from an indwelling invasive arterial line connected to Phillips Intellivue patient care monitor. Readings will be collected during a period of patient stability where no acute medical interventions or ventilator changes are being made. Arterial blood pressure readings will be measured from an invasive arterial pressure transducer already placed for clinical monitoring of blood pressure. TCD measurements will be performed on a dedicated TCD machine (Doppler-BoxTM, Compumedics DWL, Germany) installed with QL imaging software and analogue TCD signal output capabilities. A specially designed portable computer cart style workstation consisting of the Doppler-Box, PC laptop and desktop computer, and 22-inch monitor is dedicated for use in research studies can be easily moved into any room in the critical care unit for bedside monitoring. While no adverse events have been reported in over 20 years experience of using TCD in the application of neurosonography, study patients may experience some stimulation with headpiece and probe placement. The investigators will attempt to minimize this as much as possible, if the patients physiological condition does not tolerate even mild movements with headpiece placement the investigators will stop the procedure.

D2. Near Infrared Spectroscopy Cerebral Regional Oximetry Data for wavelet coherence will be collected continuously for the first 7-10 days of admission using the combined NIRS/MAP monitoring devices. Analyzing the changes in SctO2 with fluctuation in MAP/CPP continuously using wavelet coherence over first 7-10 days is important as this will uncover dynamic changes in CA that occur during the actual pathophysiologic disturbances at the margins of target values in neurocritical illness such as during periods of low MAP/CPP or elevated ICP Intracranial pressure (ICP). Cerebral oximetry values will be collected at 1 Hz from a NIRS monitor (Medtronic, INVOS 5100C Cerebral Oximetry, Minneapolis, MN). The NIRS self adhesive single-use sensor will be placed on a clean and dry site on the right/left or bilateral forehead above the eyebrow and inferior to hair line and away from any damaged tissue, sagittal sinus or frontal extra axial hemorrhages underlying the sensor. The skin around the sensor will be inspected twice daily and sensors will be kept away from strong light and moisture. Sensors will be removed if the patient is having an MRI but not if they are having a brain CT. If a patient will have NIRS as part of their standard of medical care the investigators will consent for collection of the SctO2 values that are being used by the clinical team for up to 10 days or as long as the monitor is in place. In patients where NIRS monitoring is not a standard of care device the NIRS sensor and monitor will be provided by the study team and the SctO2 value will be covered on the display during the study procedures. The medical team will be blinded to any TCD and/or SctO2 values if it is collected for the sole purposes of research. The screen is password protected and streaming data will not be available for viewing by the staff or family without a password to unlock the screen saver display.

D3. Neurologic Outcome Assessment Neurologic outcome will be at assessed at hospital discharge, 3, 6 and 12 months post-injury. The 8-point Glasgow Outcome Scale Extended-Pediatrics (GOSEP) will be used for neurologic functional outcome categories. A GOSEP score of 1 = normal, 2 = mild disability, 3 = upper moderate disability, or 4 = lower moderate disability is classified as a favorable outcome. A GOSEP score of 5 = upper severe disability, 6 = lower severe disability, 7 = vegetative state, or 8 = death was classified is an unfavorable outcome. The GOSEP will be conducted by a study member through a 10-minute parent/legal guardian interview over the phone. Neuropsychological outcome will also be measured using the Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT) a validated tool to measure domains of daily activities, mobility, social/cognitive function and responsibility from birth through 18 years. The PEDI-CAT is a computer based program which will be conducted over the phone with the interviewer reading questions and entering deidentified responses into the web based program for analysis and report.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 30
• Est. completion date: January 2025
• Est. primary completion date: January 2025
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 28 Days to 18 Years

Eligibility

Inclusion Criteria:

• Ages 28 days-18 years admitted to the PICU at Children's Medical Center Dallas

• Acute presentation (< 24 hour) onset of neurologic injury

• Acute neurologic injury can be due to any of the following mechanisms:

• Severe accidental or abusive traumatic brain injury

• Severe encephalopathy secondary to cardiac arrest

• Spontaneous intracranial hemorrhage

• Status epilepticus

• Stroke

• Presence of or pending placement of invasive indwelling arterial line for stand medical care

• Any patient with an ICP monitor placed as standard of care

Exclusion Criteria:

• Patients without an arterial line placed as standard of care

• Patients unable to cooperate with wearing a TCD headpiece device

• Expected death within 24-48 hours

• Inability to place NIRS probes or insonate TCD signal due to massive facial or cranial injury

• Receiving an inhalational anesthetic agent

• Hemoglobinopathy, myoglobinemia or and hyperbilirubinemia (due to inaccurate NIRS readings)

Related Conditions & MeSH terms

• Brain Injuries
• Brain Injuries, Traumatic
• Brain Injury, Vascular
• Cerebrovascular Trauma
• Traumatic Brain Injury
• Vascular System Injuries
• Wounds and Injuries

Intervention

Device:
• Transcranial Doppler
Record flow velocity tracing of middle cerebral artery using a transcranial doppler.

Locations

Country	Name	City	State
United States	Children's Medical Center	Dallas	Texas

Sponsors (3)

Lead Sponsor	Collaborator
University of Texas Southwestern Medical Center	Southern Methodist University, The University of Texas at Arlington

Country where clinical trial is conducted

United States, 

References & Publications (22)

Brady KM, Lee JK, Kibler KK, Smielewski P, Czosnyka M, Easley RB, Koehler RC, Shaffner DH. Continuous time-domain analysis of cerebrovascular autoregulation using near-infrared spectroscopy. Stroke. 2007 Oct;38(10):2818-25. doi: 10.1161/STROKEAHA.107.485706. Epub 2007 Aug 30. — View Citation

Brady KM, Mytar JO, Lee JK, Cameron DE, Vricella LA, Thompson WR, Hogue CW, Easley RB. Monitoring cerebral blood flow pressure autoregulation in pediatric patients during cardiac surgery. Stroke. 2010 Sep;41(9):1957-62. doi: 10.1161/STROKEAHA.109.575167. Epub 2010 Jul 22. — View Citation

Claassen JA, Meel-van den Abeelen AS, Simpson DM, Panerai RB; international Cerebral Autoregulation Research Network (CARNet). Transfer function analysis of dynamic cerebral autoregulation: A white paper from the International Cerebral Autoregulation Research Network. J Cereb Blood Flow Metab. 2016 Apr;36(4):665-80. doi: 10.1177/0271678X15626425. Epub 2016 Jan 18. — View Citation

Coronado VG, Xu L, Basavaraju SV, McGuire LC, Wald MM, Faul MD, Guzman BR, Hemphill JD; Centers for Disease Control and Prevention (CDC). Surveillance for traumatic brain injury-related deaths--United States, 1997-2007. MMWR Surveill Summ. 2011 May 6;60(5):1-32. — View Citation

Donnelly J, Budohoski KP, Smielewski P, Czosnyka M. Regulation of the cerebral circulation: bedside assessment and clinical implications. Crit Care. 2016 May 5;20(1):129. doi: 10.1186/s13054-016-1293-6. — View Citation

Friess SH, Kilbaugh TJ, Huh JW. Advanced neuromonitoring and imaging in pediatric traumatic brain injury. Crit Care Res Pract. 2012;2012:361310. doi: 10.1155/2012/361310. Epub 2012 May 21. — View Citation

Kochanek PM, Carney N, Adelson PD, Ashwal S, Bell MJ, Bratton S, Carson S, Chesnut RM, Ghajar J, Goldstein B, Grant GA, Kissoon N, Peterson K, Selden NR, Tasker RC, Tong KA, Vavilala MS, Wainwright MS, Warden CR; American Academy of Pediatrics-Section on Neurological Surgery; American Association of Neurological Surgeons/Congress of Neurological Surgeons; Child Neurology Society; European Society of Pediatric and Neonatal Intensive Care; Neurocritical Care Society; Pediatric Neurocritical Care Research Group; Society of Critical Care Medicine; Paediatric Intensive Care Society UK; Society for Neuroscience in Anesthesiology and Critical Care; World Federation of Pediatric Intensive and Critical Care Societies. Guidelines for the acute medical management of severe traumatic brain injury in infants, children, and adolescents--second edition. Pediatr Crit Care Med. 2012 Jan;13 Suppl 1:S1-82. doi: 10.1097/PCC.0b013e31823f435c. No abstract available. Erratum In: Pediatr Crit Care Med. 2012 Mar;13(2):252. — View Citation

Lovett ME, Maa T, Chung MG, O'Brien NF. Cerebral blood flow velocity and autoregulation in paediatric patients following a global hypoxic-ischaemic insult. Resuscitation. 2018 May;126:191-196. doi: 10.1016/j.resuscitation.2018.02.005. Epub 2018 Feb 13. — View Citation

Otite F, Mink S, Tan CO, Puri A, Zamani AA, Mehregan A, Chou S, Orzell S, Purkayastha S, Du R, Sorond FA. Impaired cerebral autoregulation is associated with vasospasm and delayed cerebral ischemia in subarachnoid hemorrhage. Stroke. 2014 Mar;45(3):677-82. doi: 10.1161/STROKEAHA.113.002630. Epub 2014 Jan 14. — View Citation

Panerai RB. Assessment of cerebral pressure autoregulation in humans--a review of measurement methods. Physiol Meas. 1998 Aug;19(3):305-38. doi: 10.1088/0967-3334/19/3/001. — View Citation

Philip S, Udomphorn Y, Kirkham FJ, Vavilala MS. Cerebrovascular pathophysiology in pediatric traumatic brain injury. J Trauma. 2009 Aug;67(2 Suppl):S128-34. doi: 10.1097/TA.0b013e3181ad32c7. — View Citation

Plaweski S, Tchouda SD, Dumas J, Rossi J, Moreau Gaudry A, Cinquin P, Bosson JL, Merloz P; STIC NAV Per Op group; Computer Assisted Orthopaedic Surgery-France. Evaluation of a computer-assisted navigation system for anterior cruciate ligament reconstruction: prospective non-randomized cohort study versus conventional surgery. Orthop Traumatol Surg Res. 2012 Oct;98(6 Suppl):S91-7. doi: 10.1016/j.otsr.2012.07.001. Epub 2012 Aug 24. — View Citation

Purkayastha S, Fadar O, Mehregan A, Salat DH, Moscufo N, Meier DS, Guttmann CR, Fisher ND, Lipsitz LA, Sorond FA. Impaired cerebrovascular hemodynamics are associated with cerebral white matter damage. J Cereb Blood Flow Metab. 2014 Feb;34(2):228-34. doi: 10.1038/jcbfm.2013.180. Epub 2013 Oct 16. — View Citation

Rivara FP, Koepsell TD, Wang J, Temkin N, Dorsch A, Vavilala MS, Durbin D, Jaffe KM. Disability 3, 12, and 24 months after traumatic brain injury among children and adolescents. Pediatrics. 2011 Nov;128(5):e1129-38. doi: 10.1542/peds.2011-0840. Epub 2011 Oct 24. — View Citation

Rivera-Lara L, Geocadin R, Zorrilla-Vaca A, Healy R, Radzik BR, Palmisano C, Mirski M, Ziai WC, Hogue C. Validation of Near-Infrared Spectroscopy for Monitoring Cerebral Autoregulation in Comatose Patients. Neurocrit Care. 2017 Dec;27(3):362-369. doi: 10.1007/s12028-017-0421-8. — View Citation

Schytz HW, Hansson A, Phillip D, Selb J, Boas DA, Iversen HK, Ashina M. Spontaneous low-frequency oscillations in cerebral vessels: applications in carotid artery disease and ischemic stroke. J Stroke Cerebrovasc Dis. 2010 Nov-Dec;19(6):465-74. doi: 10.1016/j.jstrokecerebrovasdis.2010.06.001. — View Citation

Tian F, Morriss MC, Chalak L, Venkataraman R, Ahn C, Liu H, Raman L. Impairment of cerebral autoregulation in pediatric extracorporeal membrane oxygenation associated with neuroimaging abnormalities. Neurophotonics. 2017 Oct;4(4):041410. doi: 10.1117/1.NPh.4.4.041410. Epub 2017 Aug 19. — View Citation

Tian F, Tarumi T, Liu H, Zhang R, Chalak L. Wavelet coherence analysis of dynamic cerebral autoregulation in neonatal hypoxic-ischemic encephalopathy. Neuroimage Clin. 2016 Jan 25;11:124-132. doi: 10.1016/j.nicl.2016.01.020. eCollection 2016. — View Citation

Trenchard SO, Rust S, Bunton P. A systematic review of psychosocial outcomes within 2 years of paediatric traumatic brain injury in a school-aged population. Brain Inj. 2013;27(11):1217-37. doi: 10.3109/02699052.2013.812240. — View Citation

Tsuji M, Saul JP, du Plessis A, Eichenwald E, Sobh J, Crocker R, Volpe JJ. Cerebral intravascular oxygenation correlates with mean arterial pressure in critically ill premature infants. Pediatrics. 2000 Oct;106(4):625-32. doi: 10.1542/peds.106.4.625. — View Citation

Udomphorn Y, Armstead WM, Vavilala MS. Cerebral blood flow and autoregulation after pediatric traumatic brain injury. Pediatr Neurol. 2008 Apr;38(4):225-34. doi: 10.1016/j.pediatrneurol.2007.09.012. — View Citation

White H, Venkatesh B. Cerebral perfusion pressure in neurotrauma: a review. Anesth Analg. 2008 Sep;107(3):979-88. doi: 10.1213/ane.0b013e31817e7b1a. — View Citation

* Note: There are 22 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Transfer Function Analysis	The transfer function has three components: I. Gain: This measures the magnitude of transmission of MAP oscillations to CBFv. Effectively, a functional dCA system dampens the strength of transmitted oscillations resulting in a lower gain value. A higher gain value is therefore suggestive of impaired autoregulation.; II. Phase is a "time delay" in degrees measured between the two waveforms. Absence of autoregulation would result in both MAP and CBFV changing at the same time. This would be measured as a 0°phase shift. Hence, a non-zero phase shift indicates intact autoregulation and counter-regulation of CBFV in response to changes in MAP.; III. Coherence:This provides a measure of association between the two waves at difference frequencies. Coherence varies between 0 and 1, similar to a correlation coefficient it expresses the fraction of MAP linearly associated with CBFv. Gain, phase, and coherence will be aggregated to get the transfer function analysis.	Day 1 post injury
Primary	Transfer Function Analysis	The transfer function has three components: I. Gain: This measures the magnitude of transmission of MAP oscillations to CBFv. Effectively, a functional dCA system dampens the strength of transmitted oscillations resulting in a lower gain value. A higher gain value is therefore suggestive of impaired autoregulation.; II. Phase is a "time delay" in degrees measured between the two waveforms. Absence of autoregulation would result in both MAP and CBFV changing at the same time. This would be measured as a 0°phase shift. Hence, a non-zero phase shift indicates intact autoregulation and counter-regulation of CBFV in response to changes in MAP.; III. Coherence:This provides a measure of association between the two waves at difference frequencies. Coherence varies between 0 and 1, similar to a correlation coefficient it expresses the fraction of MAP linearly associated with CBFv. Gain, phase, and coherence will be aggregated to get the transfer function analysis.	Day 3 post injury
Primary	Transfer Function Analysis	The transfer function has three components: I. Gain: This measures the magnitude of transmission of MAP oscillations to CBFv. Effectively, a functional dCA system dampens the strength of transmitted oscillations resulting in a lower gain value. A higher gain value is therefore suggestive of impaired autoregulation.; II. Phase is a "time delay" in degrees measured between the two waveforms. Absence of autoregulation would result in both MAP and CBFV changing at the same time. This would be measured as a 0°phase shift. Hence, a non-zero phase shift indicates intact autoregulation and counter-regulation of CBFV in response to changes in MAP.; III. Coherence:This provides a measure of association between the two waves at difference frequencies. Coherence varies between 0 and 1, similar to a correlation coefficient it expresses the fraction of MAP linearly associated with CBFv. Gain, phase, and coherence will be aggregated to get the transfer function analysis.	Day 5 post injury
Primary	Transfer Function Analysis	The transfer function has three components: I. Gain: This measures the magnitude of transmission of MAP oscillations to CBFv. Effectively, a functional dCA system dampens the strength of transmitted oscillations resulting in a lower gain value. A higher gain value is therefore suggestive of impaired autoregulation.; II. Phase is a "time delay" in degrees measured between the two waveforms. Absence of autoregulation would result in both MAP and CBFV changing at the same time. This would be measured as a 0°phase shift. Hence, a non-zero phase shift indicates intact autoregulation and counter-regulation of CBFV in response to changes in MAP.; III. Coherence:This provides a measure of association between the two waves at difference frequencies. Coherence varies between 0 and 1, similar to a correlation coefficient it expresses the fraction of MAP linearly associated with CBFv. Gain, phase, and coherence will be aggregated to get the transfer function analysis.	Day 7 post injury
Primary	Transfer Function Analysis	The transfer function has three components: I. Gain: This measures the magnitude of transmission of MAP oscillations to CBFv. Effectively, a functional dCA system dampens the strength of transmitted oscillations resulting in a lower gain value. A higher gain value is therefore suggestive of impaired autoregulation.; II. Phase is a "time delay" in degrees measured between the two waveforms. Absence of autoregulation would result in both MAP and CBFV changing at the same time. This would be measured as a 0°phase shift. Hence, a non-zero phase shift indicates intact autoregulation and counter-regulation of CBFV in response to changes in MAP.; III. Coherence:This provides a measure of association between the two waves at difference frequencies. Coherence varies between 0 and 1, similar to a correlation coefficient it expresses the fraction of MAP linearly associated with CBFv. Gain, phase, and coherence will be aggregated to get the transfer function analysis.	Day 10 post injury
Primary	Wavelet Coherence Analysis	Wavelet coherence uses phase, gain and coherence to determine a relationship between the two waveforms values MAP/CPP and SctO2.	Day 10 post injury
Primary	Change in Glasgow Outcome Scale Extended-Pediatrics (GOSEP) score	The 8-point Glasgow Outcome Scale Extended-Pediatrics (GOSEP) will be used to assess change in neurologic function from baseline. The GOSEP is composed of 3 parts: eye opening, best motor response, and best verbal response. Eye opening is measure 1-4, the higher the category, the better outcome. Best motor response is measured as 1-6, the higher the score, the better outcome. Best verbal response is measured as 1-5, the higher the score, the better outcome. All 3 categories are summed together to equal a total GOSEP score. The higher the overall score, the better potential outcome.	6 months post discharge.
Primary	Change in Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT) score	Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT) a validated tool to measure domains of daily activities, mobility, social/cognitive function and responsibility from birth through 18 years. It will be used to assess change from baseline.	6 months post discharge.