Neurosurg Focus 33 (6):E9, 2012 Magnetoencephalographic virtual recording: a novel diagnostic tool for concussion MATTHEW TORMENTI, M.D.,1 DONALD KRIEGER, PH.D.,1 AVA M. PUCCIO, R.N., PH.D.,1 MALCOLM R. MCNEIL, PH.D.,2 WALTER SCHNEIDER, PH.D.,3 AND DAVID O. OKONKWO, M.D., PH.D.1 Departments of 1Neurological Surgery, 2Communication Science and Disorders, and 3Psychology, University of Pittsburgh, Pennsylvania Object. Heightened recognition of the prevalence and significance of head injury in sports and in combat veter- ans has brought increased attention to the physiological and behavioral consequences of concussion. Current clinical practice is in part dependent on patient self-report as the basis for medical decisions and treatment. Magnetoen- cephalography (MEG) shows promise in the assessment of the pathophysiological derangements in concussion. The authors have developed a novel MEG-based neuroimaging strategy to provide objective, noninvasive, diagnostic information in neurological disorders. In the current study the authors demonstrate a novel task protocol and then assess MEG virtual recordings obtained during task performance as a diagnostic tool for concussion. Methods. Ten individuals (5 control volunteers and 5 patients with a history of concussion) were enrolled in this pilot study. All participants underwent an MEG evaluation during performance of a language/spatial task. Each individual produced 960 responses to 320 sentence stimuli; 0.3 sec of MEG data from each word presentation and each response were analyzed: the data from each participant were classified using a rule constructed from the data obtained from the other 9 participants. Results. Analysis of response times showed significant differences (p < 10-4) between concussed and normal groups, demonstrating the sensitivity of the task. The MEG measures enabled the correct classification of 8 of 10 individuals as concussed versus nonconcussed (p = 0.055). Analysis of single-trial data classified 70% of trials cor- rectly (p < 10-10). Concussed patients showed increased activation in the occipitoparietal and temporal regions during evaluation. Conclusions. These pilot findings are the first evidence of the utility of MEG virtual recording in diagnosing concussion. With further refinements, MEG virtual recordings may represent a noninvasive test to diagnose concus- sion and monitor its resolution. (http://thejns.org/doi/abs/10.3171/2012.10.FOCUS12282) KEY WORDS • concussion • mild traumatic brain injury • magnetoencephalography HERE is no agreed-upon neuroimaging strategy to Magnetoencephalography shows promise for the diagnose concussion. The diagnosis of concussion, assessment of neurophysiological derangements in neu- which is also called MTBI, is based on patient rological disorders, including TBI. This promise arises Tsymptom self-report and neuropsychological testing as from the noninvasiveness and harmlessness of the meth- the basis for medical decisions and the treatment para- od, its high temporal resolution, and the interpretation of digms. A significant percentage of patients with concus- results as measures of localized neurophysiological func- sion have no abnormal findings on CT or MRI studies tion. These properties have given hope for the develop- of the brain.1 The absence of a formal, objective neuro- ment of reliable functional neuroimaging measures with imaging tool to diagnose concussion reliably is a major which to demonstrate the mechanisms underlying the 3 impediment in the field. neuropsychological consequences of concussion. Resting MEG measures have previously enabled identification of 7,9,10 Abbreviations used in this paper: EP = evoked potential; ERP = approximately 60% of patients with concussions. A event-related potential; MEG = magnetoencephalography; MTBI = recent study6 demonstrated 85% classification accuracy. mild traumatic brain injury. We have developed a novel MEG-based neuroim- Neurosurg Focus / Volume 33 / December 2012 1 Unauthenticated | Downloaded 09/25/21 08:35 AM UTC M. Tormenti et al. aging paradigm to provide objective, noninvasive, diag- given; Fig. 1 shows 2 trials in the sequence. The sentences nostic neurophysiological data. In the current study, we took the form “The blue square is below.” The figures report pilot findings obtained using MEG virtual record- were either a green or blue circle or square that appeared ing as a diagnostic tool to evaluate the ability of MEG to above or below a centered fixation mark. This yielded 8 identify individuals with concussion from healthy control possible sentences and figures. Each word of the sentence volunteers. This was accomplished by asking participants was presented via a self-paced button press with the right to perform a task and evaluating how the magnetoen- index finger. When a test figure did or did not match the cephalographic signature differs in individuals with con- sentence, the participant pressed a button with the index cussion. finger or middle finger, respectively. Each participant was presented with 320 5-word sentences in 8 blocks of 40 tri- als each. Each sentence was followed by 3 test figures, for Methods a grand total of 960 test figures. Each block was preceded Patient Demographic Data by a brief rest, followed by task instructions. For each sentence, a 30-msec pause followed the final word before Under University of Pittsburgh Institutional Review the figure appeared, and a 1000-msec pause followed the Board approval, 10 participants (5 control volunteers and response to the third figure before the first word “The” in 5 patients with recent [< 4 months] concussion) were en- the next sentence appeared. rolled in this pilot study (Table 1). All participants were The pretest instructions included: “Respond as fast as right-handed and were cognitively and neurologically you can without rushing and making mistakes. But if you normal, with no prior admission for head injury. Diagno- think you have made a mistake, don’t worry about it. Just sis of concussion was based on the patient’s history and go on.” The instructions preceding each block of 40 trials either neuropsychological testing (2 patients) or evidence were as follows: “Ready? Comfortable? Press the button of traumatic hemorrhage on head CT scans (3 patients). with your index finger to fetch the words of the sentence. The control group consisted of volunteers from the gen- And use that same button when the object you are shown eral university population. Written informed consent was is as described in the sentence. If not, use the button un- obtained, after which all participants underwent MEG der your middle finger.” evaluation. Either MRI (when available) or CT (1 of 10 volunteers) studies were used for anatomical localization. Response Time Analysis Task Presentation and MEG Recordings Self-paced reading times for each word in the sen- tence and response times to the test figures were analyzed All participants (patients with MTBI and healthy using ANOVA (BMDP4V, Statistical Solutions, Inc). No control volunteers) were assessed using the task sche- significant difference in response time was found be- matized in Fig. 1 with MEG recordings. The MEG re- tween the 2 groups. Each individuals’s response time data cordings were acquired at the University of Pittsburgh were normalized to z-scores (mean 0.0, SD 1.0) prior to Medical Center Brain Mapping Center with a 306-chan- further analysis. The factors for the ANOVA were defined nel sensor array (Neuromag VectorView, Elekta AB) in a as follows. magnetically shielded room (Imdeco). The data sampling The reading times for the 2nd–5th words were de- rate was 1000 Hz, with front-end high- and low-pass filter fined as 4 levels of the “Word” factor. The response settings of 0.1–330 Hz. times for the 3 test figures were defined as 3 levels of the Each trial consisted of a 5-word sentence followed by “Target” factor. The blocks were defined as 8 levels of 3 consecutive test figures to which a rapid response was the “Block” factor. This factor was included to capture TABLE 1: Demographic data in 10 volunteers in whom MEG virtual recording was used to assess concussion* Group & ID No. Age (yrs), Sex Mechanism of Injury Location Initial GCS Score CT/MRI Findings control 123 26, M NA NA NA NA 124 26, F NA NA NA NA 125 32, M NA NA NA NA 126 23, F NA NA NA NA 127 25, F NA NA NA NA concussed 122 24, M struck by a brick rt frontal 15 rt frontal Fx; biconvex epidural hematoma 129 22, F athletic contest NA 15 none 131 16, F athletic contest NA 15 none 135 48, M automobile lt frontal 15 lt frontal Fx; lt frontal epidural hematoma 140 57, M motorcycle NA 15 none * Fx = fracture; GCS = Glasgow Coma Scale; NA = not applicable. 2 Neurosurg Focus / Volume 33 / December 2012 Unauthenticated | Downloaded 09/25/21 08:35 AM UTC Use of MEG virtual recordings in diagnosis of concussion FIG. 1. Single-trial MEG virtual recordings from the locations indicated on the MRI slice obtained while this healthy volunteer performed the language/spatial task schematized in the figure and detailed above. The MEG virtual recordings show task- specific single-trial differences for different cognitive states. The stimulus instants are shown with the black arrows; the manual responses are shown with magenta arrows. The 6 sequential 50-msec time segments preceding each response for which the MEG virtual recordings were computed are shown at the bottom as black/blue bars (word) and blue/black bars (test figure). The lowest tracing (right posterior brain) shows responses for each word presentation, whereas the others do not. The sharp positive- going wave just prior to the motor response for the test figures is seen in all 3 locations, but with different latencies. changes in response time due to learning or fatigue. The a concussed or healthy participant. We used 720 epochs 1st, 2nd, 3rd, and 4th groups of 10 sentences within the from each of 9 participants (6480 epochs total) to con- 8 blocks were defined as 4 levels of the “wBlock” factor.