Hanley D, Prichep LS, Badjatia N, Bazarian J, Chiacchierini
R, Curley KC, Garrett J, Jones E, Naunheim R, O'Neil B, O'Neill J, Wright
DW, Huff JS. A Brain Electrical Activity Electroencephalographic-Based Biomarker
of Functional Impairment in Traumatic Brain Injury: A Multi-Site
Validation Trial. J Neurotrauma. 2018 Jan 1;35(1):41-47.
Abstract
The potential clinical utility of a novel quantitative
electroencephalographic (EEG)-based Brain Function Index (BFI) as a measure of
the presence and severity of functional brain injury was studied as part of an
independent prospective validation trial. The BFI was derived using
quantitative EEG (QEEG) features associated with functional brain impairment
reflecting current consensus on the physiology of concussive injury. Seven
hundred and twenty adult patients (18-85 years of age) evaluated within 72 h of
sustaining a closed head injury were enrolled at 11 U.S. emergency departments
(EDs). Glasgow Coma Scale (GCS) score was 15 in 97%. Standard clinical
evaluations were conducted and 5 to 10 min of EEG acquired from frontal
locations. Clinical utility of the BFI was assessed for raw scores and
percentile values. A multinomial logistic regression analysis demonstrated that
the odds ratios (computed against controls) of the mild and moderate
functionally impaired groups were significantly different from the odds ratio
of the computed tomography (CT) positive (CT+, structural injury visible on CT)
group (p = 0.0009 and p = 0.0026, respectively). However, no significant
differences were observed between the odds ratios of the mild and moderately
functionally impaired groups. Analysis of variance (ANOVA) demonstrated
significant differences in BFI among normal (16.8%), mild TBI (mTBI)/concussed
with mild or moderate functional impairment, (61.3%), and CT+ (21.9%) patients
(p < 0.0001). Regression slopes of the odds ratios for likelihood of group
membership suggest a relationship between the BFI and severity of impairment.
Findings support the BFI as a quantitative marker of brain function impairment,
which scaled with severity of functional impairment in mTBI patients. When
integrated into the clinical assessment, the BFI has the potential to aid in
early diagnosis and thereby potential to impact the sequelae of TBI by
providing an objective marker that is available at the point of care,
hand-held, non-invasive, and rapid to obtain.
Courtesy of a colleague
Ayaz SI, Thomas C, Kulek A, Tolomello R, Mika V, Robinson D, Medado P, Pearson
ReplyDeleteC, Prichep LS, O'Neil BJ. Comparison of quantitative EEG to current clinical decision rules for head CT use in acute mild traumatic brain injury in the ED. Am J Emerg Med. 2015 Apr;33(4):493-6.
Abstract
STUDY OBJECTIVE:
We compared the performance of a handheld quantitative electroencephalogram (QEEG) acquisition device to New Orleans Criteria (NOC), Canadian CT Head Rule (CCHR), and National Emergency X-Radiography Utilization Study II (NEXUS II) Rule in predicting intracranial lesions on head computed tomography (CT) in acute mild traumatic brain injury in the emergency department (ED).
METHODS:
Patients between 18 and 80 years of age who presented to the ED with acute blunt head trauma were enrolled in this prospective observational study at 2 urban academic EDs in Detroit, MI. Data were collected for 10 minutes from frontal leads to determine a QEEG discriminant score that could maximally classify intracranial lesions on head CT.
RESULTS:
One hundred fifty-two patients were enrolled from July 2012 to February 2013. A total 17.1% had acute traumatic intracranial lesions on head CT. Quantitative electroencephalogram discriminant score of greater than or equal to 31 was found to be a good cutoff (area under receiver operating characteristic curve = 0.84; 95% confidence interval [CI], 0.76-0.93) to classify patients with positive head CT. The sensitivity of QEEG discriminant score was 92.3 (95% CI, 73.4-98.6), whereas the specificity was 57.1 (95% CI, 48.0-65.8). The sensitivity and specificity of the decision rules were as follows: NOC 96.1 (95% CI, 78.4-99.7) and 15.8 (95% CI, 10.1-23.6); CCHR 46.1 (95% CI, 27.1-66.2) and 86.5 (95% CI, 78.9-91.7); NEXUS II 96.1 (95% CI, 78.4-99.7) and 31.7 (95% CI, 23.9-40.7).
CONCLUSION:
At a sensitivity of greater than 90%, QEEG discriminant score had better specificity than NOC and NEXUS II. Only CCHR had better specificity than QEEG discriminant score but at the cost of low (<50%) sensitivity.
Brooks MA, Bazarian JJ, Prichep LS, Dastidar SG, Talavage TM, Barr W. The Use of an Electrophysiological Brain Function Index in the Evaluation of Concussed Athletes. J Head Trauma Rehabil. 2018 Jan/Feb;33(1):1-6.
ReplyDeleteAbstract
OBJECTIVE:
To evaluate the effectiveness of the electroencephalographic (EEG) Brain Function Index (BFI) for characterizing sports-related concussive injury and recovery.
PARTICIPANTS:
Three hundred fifty-four (354) male contact sport high school and college athletes were prospectively recruited from multiple locations over 6 academic years of play (244 control baseline athletes and 110 athletes with a concussion).
METHODS:
Using 5 to 10 minutes of eyes closed resting EEG collected from frontal and frontotemporal regions, a BFI was computed for all subjects and sessions. Group comparisons were performed to test for the significance of the difference in the BFI score between the controls at baseline and athletes with a concussion at several time points.
RESULTS:
There was no significant difference in BFI between athletes with a concussion at baseline (ie, prior to injury) and controls at baseline (P = .4634). Athletes with a concussion, tested within 72 hours of injury, exhibited significant differences in BFI compared with controls (P = .0036). The significant differences in BFI were no longer observed at 45 days following injury (P = .19).
CONCLUSION:
Controls and athletes with a concussion exhibited equivalent BFI scores at preseason baseline. The concussive injury (measured within 72 hours) significantly affected brain function reflected in the BFI in the athletes with a concussion. The BFI of the athletes with a concussion returned to levels seen in controls by day 45, suggesting recovery. The BFI may provide an important objective marker of concussive injury and recovery.
Prichep LS, Ghosh Dastidar S, Jacquin A, Koppes W, Miller J, Radman T, O'Neil B, Naunheim R, Huff JS. Classification algorithms for the identification of structural injury in TBI using brain electrical activity. Comput Biol Med. 2014
ReplyDeleteOct;53:125-33.
Abstract
BACKGROUND:
There is an urgent need for objective criteria adjunctive to standard clinical assessment of acute Traumatic Brain Injury (TBI). Details of the development of a quantitative index to identify structural brain injury based on brain electrical activity will be described.
METHODS:
Acute closed head injured and normal patients (n=1470) were recruited from 16 US Emergency Departments and evaluated using brain electrical activity (EEG) recorded from forehead electrodes. Patients had high GCS (median=15), and most presented with low suspicion of brain injury. Patients were divided into a CT positive (CT+) group and a group with CT negative findings or where CT scans were not ordered according to standard assessment (CT-/CT_NR). Three different classifier methodologies, Ensemble Harmony, Least Absolute Shrinkage and Selection Operator (LASSO), and Genetic Algorithm (GA), were utilized.
RESULTS:
Similar performance accuracy was obtained for all three methodologies with an average sensitivity/specificity of 97.5%/59.5%, area under the curves (AUC) of 0.90 and average Negative Predictive Validity (NPV)>99%. Sensitivity was highest for CT+ cases with potentially life threatening hematomas, where two of three classifiers were 100%.
CONCLUSION:
Similar performance of these classifiers suggests that the optimal separation of the populations was obtained given the overlap of the underlying distributions of features of brain activity. High sensitivity to CT+ injuries (highest in hematomas) and specificity significantly higher than that obtained using ED guidelines for imaging, supports the enhanced clinical utility of this technology and suggests the potential role in the objective, rapid and more optimal triage of TBI patients.