Magnetic Source Imaging/Magnetoencephalography
Number: 0279
Table Of Contents
PolicyApplicable CPT / HCPCS / ICD-10 Codes
Background
References
Policy
Scope of Policy
This Clinical Policy Bulletin addresses magnetic source imaging and magnetoencephalography.
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Medical Necessity
Aetna considers magnetic source imaging (MSI) or magnetoencephalography (MEG) medically necessary for pre-surgical evaluation in persons with intractable focal epilepsy to identify and localize areas of epileptiform activity, when discordance or continuing questions arise from among other techniques designed to localize a focus.
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Experimental and Investigational
- Aetna considers magnetic source imaging (MSI) or magnetoencephalography (MEG) experimental and investigational when used as a stand-alone test or as the first order of test after clinical and routine electroencephalographic (EEG) diagnosis of epilepsy because its effectiveness for these indications has not been established.
- Aetna considers MSI or MEG experimental and investigational for the following indications (not an all-inclusive list) because its effectiveness for these indications has not been established:
- As biomarkers of chronic pain
- As correlates of suicidal ideation and suicide attempt history in individuals with treatment-resistant major depression
- Characterization of the effects of deep brain stimulation
- Diagnosis, quantification, and monitoring of neurocognitive problems following aneurysmal subarachnoid hemorrhage
- Differentiation of post-traumatic stress disorder and traumatic brain injury
- Evaluation of alcohol dependence
- Evaluation of Alzheimer's disease
- Evaluation of attention-deficit hyperactivity disorder
- Evaluation of autism
- Evaluation of bipolar disorder
- Evaluation of brain tumors
- Evaluation of bulimia nervosa
- Evaluation of cognitive and mental disorders
- Evaluation of developmental dyslexia
- Evaluation of fibromyalgia
- Evaluation of Huntington's disease
- Evaluation of learning disorders
- Evaluation of major depressive disorder
- Evaluation of memory and language decline following epilepsy surgery
- Evaluation of migraines
- Evaluation of multiple sclerosis / multiple sclerosis-related pain
- Evaluation of Parkinson's disease
- Evaluation of prosopagnosia
- Evaluation of schizophrenia
- Evaluation of social phobia
- Evaluation of stroke rehabilitation
- Evaluation of traumatic brain injury
- Fetal neurological assessment
- Planning for cerebellar aneurysm clipping
- Prediction of upper limb sensorimotor recovery after stroke
- Staging of emerging psychosis.
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Aetna considers the use of electro-magnetic source imaging experimental and investigational for pre-surgical evaluation in persons with intractable epilepsy because the effectiveness of this approach has not been established.
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Related Policies
Background
Magnetic source imaging (MSI) or magnetoencephalography (MEG) is a non-invasive functional imaging technique in which the weak magnetic forces associated with the electrical activity of the brain are monitored externally on the scalp, i.e., MSI differs from a standard electroencephalography (EEG) in that it records the magnetic fields instead of the electrical activity. The principal advantage of MSI is that while the measurement of electrical activities is affected by surrounding brain structures, the magnetic fields are not. Thus, when coupled to magnetic resonance imaging (MRI), MSI allows a high-resolution functional/anatomical image.
American College of Radiology Appropriateness Criteria (Smirniotopolous, et al., 2011) concluded that MEG may be appropriate (appropriateness rating of 6 out of 10) for evaluating surgical candidates with medically refractory epilepsy. The Appropriatness Criteria state that MEG is complementary to EEG and may provide confirmatory information for the ictal onset zone (IOZ) localization for potential lesions seen on MRI. MEG provides better spatial resolution (2-3 mm) as compared to EEG (7-10 mm). MEG can also guide the placement of iEEG grids; and in certain patients, it may help distinguish among multiple potential seizure foci. The ACR criteria judged MEG/MSI as usually not appropriate for evaluating new onset seizures.
An assessment conducted by the BlueCross BlueShield Technology Evaluation Center (2003) concluded that there is insufficient evidence to render conclusions regarding the effect of MSI/MEG on health outcomes for either pre-surgical localization of seizure origin or pre-surgical functional mapping. An assessment of MEG from the Ontario Ministry of Health and Long Term Care Medical Advisory Secretariat (2006) found that studies are generally of poor quality, and were graded of low or very-low quality of evidence. Specifically with regard to the use of MEG in epilepsy, the assessment stated that it is unclear whether MEG has similar accuracy in localizing seizure foci as intracranial EEG.
Pataraia et al (2005) studied the functional organization of the inter-ictal spike complex in 30 patients with mesial temporal lobe epilepsy (MTLE) using combined MEG/EEG recordings. Spikes could be recorded in 14 patients (47 %) during the 2- to 3-hr MEG/EEG recording session. The MEG and EEG spikes were subjected to separate dipole analyses; the MEG spike dipole localizations were superimposed on MRI scans. All spike dipoles could be localized to the temporal lobe with a clear preponderance in the medial region. Based on dipole orientations in MEG, patients could be classified into 2 groups:- patients with anterior medial vertical (AMV) dipoles, suggesting epileptic activity in the mediobasal temporal lobe, and
- patients with anterior medial horizontal (AMH) dipoles, indicating involvement of the temporal pole and the anterior parts of the lateral temporal lobe.
Papanicolaou et al (2005) predicted the replacement of the more invasive procedure with MEG in the near future for temporal lobe epilepsy cases, subsequent to the optimization of the conditions under which pre-operative MEG is performed. Furthermore, in a review on management of intractable epilepsy in infancy and childhood, Wirrell et al (2006) stated that “MEG has proven to be useful in mapping sensory cortex and may also be useful to define eloquent cortex. The author stated that in a recent study (Stefan et al, 2003), magnetic source imaging proved most useful in the localization of extra-temporal foci. The usefulness of MEG in pediatric epilepsy surgery planning remains to be determined”. Available evidence lacks systematic comparisons to other diagnostic techniques. Furthermore, there are no data specifically documenting how MSI/MEG might alter surgical management (i.e., changing the surgical approach or reducing the time needed for intra-operative mapping).
Knowlton et al (2006) stated that non-invasive brain imaging tests can potentially supplement or even replace the use of intra-cranial EEG (ICEEG) in pre-surgical epilepsy evaluation. These investigators prospectively examined the agreement between MSI and ICEEG localization in epilepsy surgery candidates. Patients completing video monitoring with scalp EEG who had intractable partial epilepsy based on ictal electro-clinico-anatomical features were screened. A total of 49 enrolled patients (mean age of 27 years; ranging from 1 to 61 years) completed MSI and ICEEG studies. Decisions about ICEEG and surgery were made at a consensus conference where MSI could only influence ICEEG coverage by indicating supplemental coverage to that already planned by an original hypothesis. The positive predictive value of MSI for seizure localization was 82 to 90 %, depending on whether computed against ICEEG alone or in combination with surgical outcome. The kappa score of agreement for MSI with ICEEG was 0.2744 (p < 0.01). These researchers found that MSI yields localizing information with a high positive predictive value in epilepsy surgery candidates who typically require ICEEG. This finding suggested that enough clinical validity exists for MSI to potentially replace ICEEG for seizure localization. Moreover, the authors stated that future studies must ascertain if certain MSI results are more predictive of accurate epilepsy localization, and if so, what other criteria are sufficient to preclude the need for further confirmation by ICEEG. This type of weighting will have to be measured in the context of all other epilepsy localization test. Furthermore, how discordant results from multiple non-invasive tests should be handled in a single surgical decision-making score, either toward or away from surgical resection, will have to be determined from greater outcome evidence.
Sutherling et al (2008) reported on preliminary results of an ongoing, long-term clinical study in epilepsy, where MSI changed surgical decisions. The investigators determined whether MSI changed the surgical decision in a prospective, blinded, crossover-controlled, single-treatment, observational case series. Sixty-nine sequential patients diagnosed with partial epilepsy of suspected neocortical origin had video-EEG and imaging. All met criteria for intracranial EEG (ICEEG). At a surgical conference, a decision was made before and after presentation of MSI. Cases where MSI altered the decision were noted. The investigators found that MSI gave non-redundant information in 23 patients (33 %). Magnetic source imaging added ICEEG electrodes in 9 (13 %) and changed the surgical decision in another 14 (20 %). Based on MSI, 16 patients (23 %) were scheduled for different ICEEG coverage. Twenty-eight have gone to ICEEG, 29 to resection, and 14 to vagal nerve stimulation, including 17 where MSI changed the decision. Additional electrodes in 4 patients covered the correct: hemisphere in 3, lobe in 3, and sublobar ictal onset zone in 1. Magnetic source imaging avoided contralateral electrodes in 2, who both localized on ICEEG; it added information to ICEEG in 1. The investigators concluded that MSI provided non-redundant information in 33 % of patients. In those who have undergone surgery to date, MSI added useful information that changed treatment in 6 (9 %), without increasing complications. The investigators stated that MSI had benefited 21 % who have gone to surgery.
In a cohort study of epilepsy surgery candidates not sufficiently localized with non-invasive studies, Knowlton et al (2008) evaluated the predictive and prognostic value of MSI, PET, and ictal SPECT as compared with intracranial electroencephalography (ICEEG) localization in epilepsy surgery. Of 160 patients enrolled over 4 years, 77 completed ICEEG seizure monitoring. Sensitivity, specificity, and predictive values relative to ICEEG were computed for each modality. Seizures were not captured in 5 patients. Of the 72 diagnostic ICEEG studies, seizure localization results were 74 % localized, 10 % multi-focal, and 17 % non-localized. Sixty-one percent were localized to neocortical regions. Depending on patient subgroup pairs, sensitivity ranged from 58 to 64 % (MSI), 22 to 40 % (PET), and 39 to 48 % (SPECT); specificity ranges were 79 to 88 % (MSI), 53 to 63 % (PET), and 44 to 50 % (SPECT). Gains in diagnostic yield were seen only with the combination of MSI and PET or MSI and ictal SPECT. Localization concordance with ICEEG was greatest with MSI, but a significant difference was demonstrated only between MSI and PET. The investigators found that conclusively positive MSI has a high predictive value for seizures localized with ICEEG, and that diagnostic gain may be achieved with addition of either PET or ictal SPECT to MSI. The investigators noted that diagnostic values for imaging tests are lower than "true values" because of the limitations of ICEEG as a gold standard.
In a separate paper, Knowlton et al (2008) examined the outcomes of cohort subjects with epilepsy who subsequently underwent surgical resection. Of 160 patients enrolled, 62 completed ICEEG and subsequent surgical resection; 61 % resulted in an Engel I seizure-free outcome at a minimum of 1-year follow-up (mean = 3.4 years). Sensitivity, specificity, and predictive values were computed for each modality. Multi-variate logistical regression was used to identify prediction of surgical outcome by imaging test. The investigators reported that MSI sensitivity for a conclusively localized study was 55 % with a positive predictive value of 78 %. Eliminating non-diagnostic MSI cases (no spikes captured during recording) yielded a corrected negative predictive value of 64 %. With available comparison subgroups FDG-PET and ictal SPECT values were similar to MSI. The odds ratio (adjusted for epilepsy and MRI classification) for MSI prediction of seizure-free outcome was 4.4 (p = 0.01). In cases with both PET and MSI, the adjusted odds ratio for PET was 7.1 (p <0.01) and for MSI was 6.4 (p = 0.01). In the cases with all 3 tests (n = 27), ictal SPECT had the highest odds ratio (OR) of 9.1 (p = 0.05). The investigators concluded that MSI, FDG-PET, and ictal SPECT each have clinical value in predicting seizure-free surgical outcome in epilepsy surgery candidates who typically require ICEEG.
Rampp and Stefan (2007) stated that while MEG systems are still expensive and complex, the technique's characteristics offer promising possibilities for the investigation of epilepsy patients (e.g., for focus localization and pre-surgical functional mapping).
Lam et al (2008) conducted a systematic evidence review of evidence of the effectiveness of MEG in the pre-surgical evaluation of localization-related epilepsies. The investigators identified studies correlating surgical outcome (seizure freedom) with MEG source localization and resection area. The investigators found these studies of MEG reported wide ranging sensitivities (range of 0.20 to 1.0), specificities (0.06 to 1.00), positive likelihood ratios (0.67 to 2.0), and negative likelihood ratios (0.40 to 2.13). Based upon the results of their systematic review of the literature, the investigators concluded that "there is insufficient evidence in the current literature to support the relationship between the use of MEG in surgical planning and seizure-free outcome after epilepsy surgery." The investigators stated that additional studies are needed.
In a review on interictal electromagnetic source imaging in focal epilepsy, Leijten and Huiskamp (2008) noted that whether MEG is superior to EEG is still unresolved, because fair comparisons are lacking. Clinical studies have not yet adopted all technical possibilities. Localization accuracy seems high, but studies lack uniformity regarding methods, goals and outcome parameters. Therefore, the final place of electromagnetic source imaging in the pre-surgical work-up is still to be determined. The diagnostic potential is probably highest in extra-temporal epilepsies, and lowest in mesial temporal lobe epilepsy. The authors concluded that electromagnetic source imaging has evolved technically and can provide valuable localization information in the pre-surgical evaluation of patients with epilepsy. However, standardization of the technique is required before further clinical studies can better establish its role in pre-surgical evaluation of focal epilepsy.
A BlueCross BlueShield Association's technology assessment on MEG and MSI for the purpose of pre-surgical localization of epileptic lesions (2009) that "[t]he argument that MEG improves the diagnostic yield of IC-EEG is often made, but it is difficult to identify studies that can support this argument. Studies that compare IC-EEG to MEG do not inform this particular question. On the other hand, given the gravity of this particular situation, there are some possible arguments to be made on behalf of MEG. Given that current decision-making regarding who should receive surgery and what type of surgery is done with some uncertainty and lack of a true reference standard, an additional piece of information that is known to correlate with seizure focus could be arguably of some value in making difficult decisions. The diagnostic test is easy to perform and non-invasive. Also, IC-EEG and surgery are extremely invasive procedures that do not always provide diagnostic information. Information from MEG might influence a patient’s decision to undergo the risks of further testing or surgery if the outcome can be slightly better estimated. However, given that one possible outcome of use of MEG may result in avoidance of tests and procedures that may benefit the patient, it is not possible to rule out harm from use of the test. The net effect of the use of MEG on patient outcomes for this indication remains to be determined".
Magnetoencephalography can not replace, but may guide the placement of intracranial EEG and, in some patients, avoid an unnecessary intracranial EEG (AAN, 2009). Magnetoencephalography is not the first order of test after clinical and routine EEG diagnosis of epilepsy. It is one of several advanced pre-surgical investigative technologies. The need for MEG is much lower than surface EEG and anatomical imaging studies (AAN, 2009). Magnetoencephalography is not a stand-alone test. To realize its optimum clinical potential a comprehensive team evaluation, such as that available in comprehensive epilepsy centers, is necessary. The team usually comprises a neurologist with expertise in epilepsy, a neurosurgeon, MEG-physicists, psychologists, nurses and staff experienced in treatment of seizure disorders.
Although the literature contains some information regarding the clinical use of MSI in the pre-surgical mapping of eloquent cortex in patients with intra-cranial tumors or arterio-venous malformations, there is insufficient scientific evidence regarding its effectiveness for this indication. Critical outcomes are lacking, such as comparison of MSI with intra-operative methods and whether the use of MSI would change the management of patients such that clinical outcomes are improved.
Language and memory functions may reside in both or one hemisphere in patients with epilepsy. Determination of laterality is important to preserve as much language and memory functions as feasible during resective surgery. The intracarotid amobarbital test (Wada test) has long been used for language and memory localization. It has both merits and shortcomings when compared with newer tests. It is invasive, uncomfortable and carries certain morbidity. Several alternatives such as neuropsychological testing, functional MRI (fMRI), MEG, behavioral testing and SPECT-PET are available. Each has certain advantages and disadvantages.
There is limited evidence for the use of MEG as a substitute or supplement to the Wada test to identify the eloquent cortex for removal of brain tumors or arterio-venous malformations. Pelletier et al (2007) compared all the Wada alternatives in a comprehensive review. Magnetoencephalography, while requiring patient co-operation, had the advantage of being a non-invasive direct measure with excellent temporal resolution. Pelletier et al (2007) reported that the high concordance between the findings of the Wada test and neuroimaging techniques, especially fMRI, MEG, functional transcranial Doppler and possibly near infrared spectroscopy, is encouraging and holds promise that the Wada procedure will be eventually replaced by these non-invasive techniques. Pelletier et al (2007) concluded, however, that these methods still need to be refined, and certain incongruities between the Wada procedure and these techniques have to be addressed. For instance, fMRI provides little information regarding right hemisphere participation in language processing in patients with bilateral speech representation. Magnetoencephalography has the disadvantage that it is limited to the evaluation of receptive language. Furthermore, to obtain conclusive and reliable activation patterns, both fMRI and MEG require that the patient remain motionless in the scanner and comply with the test instructions. This restricts the application of these imaging techniques in young children and special populations. Pelletier et al (2007) stated that these neuroimaging techniques vary with regard to their spatial and temporal resolution. Functional MRI has good spatial resolution and relatively poor temporal resolution. The reverse is true for MEG. Furthermore, different techniques target different functions. The authors suggested that a multi-modal approach, combining several techniques, is therefore the safest way to provide the surgeon with reliable information.
There is additional evidence for the use of MEG to localize the eloquent cortex in resections for nonepilepsy lesions. Grover et al (2007) reported on a retrospective study where visual evoked cortical magnetic field (VEF) waveforms were recorded from both hemifields in 21 patients with temporo-parieto-occipital mass lesions to identify preserved visual pathways. Fifteen patients had visual symptoms pre-operatively. Magnetoencephalography VEF responses were detected, using single equivalent current dipole, in 17 of 21 patients studied. Displaced or abnormal responses were seen in 15 patients with disruption of pathway in 1 patient. Three of 21 patients had alterations in the surgical approach or the planned resection based on the MEG findings. The investigators concluded that the surgical outcome for these 3 patients suggested that the MEG study may have played a useful role in pre-surgical planning.
Korjenova et al (2006) prospectively evaluated MEG and fMRI imaging, as compared with intra-operative cortical mapping, to localize the central sulcus. Fifteen patients (6 men, 9 women; age range of 25 to 58 years) with a lesion near the primary sensorimotor cortex (13 gliomas, 1 cavernous hemangioma, and 1 meningioma) were examined. Magnetoencephalography and fMRI localizations were compared with intra-operative cortical mappings. Magnetoencephalography depicted the central sulcus correctly in all 15 patients, as verified at intra-operative mapping. The fMRI localization results agreed with the intra-operative mappings in 11 patients. The investigators concluded that, although both MEG and fMRI can provide useful information for neurosurgical planning, in the present study, MEG proved to be superior for locating the central sulcus.
There is also insufficient evidence to support the use of MSI/MEG for other indications including the diagnosis and treatment of various neurological conditions/diseases such as Alzheimer's disease, autism, cognitive and mental disorders, learning disabilities, developmental dyslexia, multiple sclerosis, Parkinson's disease, schizophrenia, stroke rehabilitation, and traumatic brain injury. Currently, there are reliable data from well-designed clinical studies that report the test performance (sensitivity, specificity, positive and negative predictive values) and clinical utility of MSI/MEG for these indications.
Haddad and colleagues (2011) stated that the fetal brain remains inaccessible to neurophysiological studies. Magnetoencephalography is being assessed to fill this gap. These researchers performed 40 fetal MEG (fMEG) recordings with gestational ages (GA) ranging from 30 to 37weeks. The data from each recording were divided into 15 second epochs, which in turn were classified as continuous (CO), discontinuous (DC), or artifact. The fetal behavioral state, quiet or active sleep, was determined using previously defined criteria based on fetal movements and heart rate variability. These investigators studied the correlation between the fetal state, the GA and the percentage of CO and DC epochs. They also analyzed the spectral edge frequency (SEF) and studied its relation with state and GA. They found that the odds of a DC epoch decreased by 6 % per week as the GA increased (p = 0.0036). This decrease was mainly generated by changes during quiet sleep, which showed 52 % DC epochs before a 35-week GA versus 38 % after 35 weeks (p = 0.0006). Active sleep did not show a significant change in DC epochs with GA. When both states were compared for MEG patterns within each GA group (before and after 35 weeks), the early group was found to have more DC epochs in quiet sleep (54 %) compared to active sleep (42 %) (p = 0.036). No significant difference in DC epochs between the 2 states was noted in the late GA group. Analysis of SEF showed a significant difference (p = 0.0014) before and after a 35-week GA, with higher SEF noted at late GA. However, when both quiet and active sleep states were compared within each GA group, the SEF did not show a significant difference. The authors concluded that fMEG shows reproducible variations in gross features and frequency content, depending on GA and behavioral state. They stated that fetal MEG is a promising tool to investigate fetal brain physiology and maturation.
Xiang et al (2013) quantitatively evaluated cortical dysfunction in pediatric migraine; a total of 31 adolescents with acute migraine and age- and gender-matched controls were studied using a MEG system at a sampling rate of 6,000 Hz. Neuro-magnetic brain activation was elicited by a finger-tapping task. The spectral and spatial signatures of MEG data in 5 to 2,884 Hz were analyzed using Morlet wavelet and beam-formers. Compared with controls, 31 migraine subjects during their headache attack phases (ictal) showed significantly prolonged latencies of neuro-magnetic activation in 5 to 30 Hz, increased spectral power in 100 to 200 Hz, and a higher likelihood of neuro-magnetic activation in the supplementary motor area, the occipital and ipsilateral sensorimotor cortices, in 2,200 to 2,800 Hz. Of the 31 migraine subjects, 16 migraine subjects during their headache-free phases (inter-ictal) showed that there were no significant differences between inter-ictal and control MEG data except that inter-ictal spectral power in 100 to 200 Hz was significantly decreased. The results demonstrated that migraine subjects had significantly aberrant ictal brain activation, which can normalize inter-ictally. The spread of abnormal ictal brain activation in both low- and high-frequency ranges triggered by movements may play a key role in the cascade of migraine attacks. The authors concluded that this was the first study focusing on the spectral and spatial signatures of cortical dysfunction in adolescents with migraine using MEG signals in a frequency range of 5 to 2,884 Hz. Moreover, they stated that this methodology analyzing aberrant brain activation may be important for developing new therapeutic interventions for migraine in the future.
Furthermore, UpToDate reviews on “Pathophysiology, clinical features, and diagnosis of migraine in children” (Cruse, 2014) and “Pathophysiology, clinical manifestations, and diagnosis of migraine in adults” (Cutrer et al, 2014) do not mention the use of magnetic source imaging or magnetoencephalography.
da Costa et al (2015) stated that awareness to neurocognitive issues after mild traumatic brain injury (mTBI) is increasing, but currently no imaging markers are available for mTBI. Advanced structural imaging recently showed microstructural tissue changes and axonal injury, mild but likely sufficient to lead to functional deficits. Magnetoencephalography has high temporal and spatial resolution, combining structural and electrophysiological information, and can be used to examine brain activation patterns of regions involved with specific tasks. In this study, a total of 16 adults with mTBI and 16 matched controls were submitted to neuropsychological testing (Wechsler Abbreviated Scale of Intelligence (WASI); Conners; Alcohol Use Disorders Identification Test (AUDIT); Generalized Anxiety Disorder Seven-item Scale (GAD-7); Patient Health Questionnaire (PHQ-9); Symptom Checklist and Symptom Severity Score (SCAT2)) and MEG while tested for mental flexibility (Intra-Extra Dimensional set-shifting tasks). Three-dimensional maps were generated using synthetic aperture magnetometry beam-forming analyses to identify differences in regional activation and activation times. Reaction times and accuracy between groups were compared using 2 × 2 mixed analysis of variance. While accuracy was similar, patients with mTBI reaction time was delayed and sequence of activation of brain regions disorganized, with involvement of extra regions such as the occipital lobes, not used by controls. Examination of activation time showed significant delays in the right insula and left posterior parietal cortex in patients with mTBI. The authors concluded that patients with mTBI showed significant delays in the activation of important areas involved in executive function. In addition, more regions of the brain are involved in an apparent compensatory effort. They stated that these findings suggested that MEG can detect subtle neural changes associated with cognitive dysfunction and thus, may eventually be useful for capturing and tracking the onset and course of cognitive symptoms associated with mTBI.
Wang et al (2014a) examined the right and left hemispheric auditory sensory gating of the M50 (pre-attentive processing) and M100 (early attentive processing) in patients diagnosed with bipolar I disorder by using MEG. Whole-head MEG data were acquired during the standard paired-click paradigm in 20 bipolar I disorder patients and 20 healthy controls. The M50 and the M100 responses were investigated, and dipole source localizations were also investigated. Sensory gating was determined by measuring the strength of the M50 and the M100 response to the second click divided by that of the first click (S2/S1). In every subject, M50 and M100 dipolar sources were localized to the left and right posterior portion of superior temporal gyrus (STG). Bipolar I disorder patients showed bilateral gating deficits in M50 and M100. The bilateral M50 S2 source strengths were significantly higher in the bipolar I disorder group compared to the control group. The authors concluded that these findings suggested that bipolar I disorder patients have auditory gating deficits at both pre-attentive and early attentive levels, which might be related to STG structural abnormality. The main drawbacks of this study were- small sample size (n = 20 patients) and
- patients were taking a wide range of medications that could not be controlled for;
Wang et al (2014b) investigated the M100 and M200 auditory responses in patients with schizophrenia and bipolar disorder and compared them with healthy controls by means of MEG. Whole-head MEG data were acquired during an auditory oddball paradigm in 24 schizophrenia patients, 26 bipolar I disorder patients, and 31 healthy controls. The strengths and latencies of M100 and M200 in both hemispheres and the dipole source localizations were investigated from the standard stimuli. The M100 and M200 dipolar sources were localized to the left and right posterior portion of the STG in all the subjects. An asymmetric pattern of M100 and M200 auditory response with more anterior sources in the right STG was observed in the healthy controls. However, both the schizophrenia and bipolar disorder patients showed a symmetric M100 and M200 source pattern. When compared with the healthy control group, both patient groups showed significantly reduced M100 and M200 source strength in both hemispheres. The authors concluded that these findings suggested that early auditory information processing deficits may be similar in schizophrenia and bipolar disorder and may be related to abnormalities of the STG. The main drawback of this study was its small sample size (n = 24 for schizophrenia, and n = 26 for bipolar disorder; and there may be overlapping of bipolar patients in these 2 studies (Wang et al, 2014a and 2014b).
Feuerriegel et al (2015) evaluated evidence for configural and affective face processing abnormalities as measured by the N170 and Vertex Positive Potential (VPP) event-related potential components, and analogous M170 MEG component, in neurological and psychiatric disorders. A total of 1,251 unique articles were identified using PsychINFO and PubMed databases; 67 studies were selected for review, which employed various tasks to measure the N170, M170 or VPP; the 13 neurological/psychiatric conditions were attention-deficit hyperactivity disorder (ADHD), alcohol dependence, Alzheimer's disease, autism spectrum disorders (ASDs), bipolar disorder, bulimia nervosa, fibromyalgia, Huntington's disease, major depressive disorder, Parkinson's disease, prosopagnosia, schizophrenia and social phobia. Smaller N170 and VPP amplitudes to faces compared to healthy controls were consistently reported in schizophrenia but not in ASDs. In schizophrenia, N170 and VPP measures were not correlated with clinical symptoms. Findings from other disorders were highly inconsistent; however, reported group differences were almost always smaller amplitudes or slower latencies to emotional faces in disordered groups regardless of diagnosis. The authors concluded that these findings suggested that N170/VPP abnormalities index non-specific facial affect processing dysfunction in these neurological and psychiatric conditions, reflecting social impairments being broadly characteristic of these groups. They noted that the N170 and analogous components hold promise as diagnostic and treatment monitoring biomarkers for social dysfunction.
Alhourani and associates (2016) stated that mTBI leads to long-term cognitive sequelae in a significant portion of patients. Disruption of normal neural communication across functional brain networks may explain the deficits in memory and attention observed following mTBI. These investigators used MEG to examine functional connectivity during a resting state in a group of mTBI subjects (n = 9) compared with age-matched control subjects (n = 15). They adopted a data-driven, exploratory analysis in source space using phase locking value across different frequency bands. They observed a significant reduction in functional connectivity in band-specific networks in mTBI compared with control subjects. These networks spanned multiple cortical regions involved in the default mode network (DMN). The DMN is thought to sub-serve memory and attention during periods when an individual is not engaged in a specific task, and its disruption may lead to cognitive deficits after mTBI. These researchers further applied graph theoretical analysis on the functional connectivity matrices. They stated that these findings suggested reduced local efficiency in different brain regions in mTBI patients. The authors concluded that MEG can be a potential tool to investigate and detect network alterations in patients with mTBI. They stated that the value of MEG to reveal potential neurophysiological biomarkers for mTBI patients warrants further exploration.
Diagnosis, Quantification, and Monitoring of Neurocognitive Problems Following Aneurysmal Subarachnoid Hemorrhage
de Costa and colleagues (2016) stated that among good outcome survivors of aneurysmal subarachnoid hemorrhage (aSAH), only 23 % have normal neurocognitive performance, despite imaging that is often normal. These researchers examined the use of MEG after endovascular treatment of ruptured aneurysms. Good outcome aSAH patients treated with coiling and matched controls were recruited. Clinical assessments and resting-state MEG and anatomical MRI images were obtained. Brain space was normalized to standard Montreal Neurological Institute (MNI) brain. Areas of interest were identified with Automated Anatomical Labeling (AAL) and "electrodes" reconstructed using vector beamformer. Spectral power density estimates for each location was averaged across the brain to derive mean signal power. Virtual-sensor data closest to the coil was assessed for signal quality. A total of 13 aSAH patients and 13 matched controls were recruited. Mean age was 54.5 years (SD = 9.9) for controls and 56.8 years (SD = 11.8) for aSAH. The majority of aneurysms (62 %) were in the midline. Mean time from aSAH to MEG was 18.8 months (2.4 to 67.5; SD = 19). Data quality was comparable in both groups, including the virtual-sensors close to the coil mass. Mean signal power showed no significant spectral alterations in the aSAH group. The authors concluded that MEG is feasible in aSAH patients after endovascular treatment. They stated that these findings suggested that the signal quality and strength was good, and the presence of coils did not interfere with testing. They stated that considering the common neurocognitive complaints of aSAH survivors, MEG could be developed to diagnose, quantify, and monitor neurocognitive problems after aSAH.
The main drawbacks of this study were:- this was a small (n = 13 for aSAH) feasibility study,
- the study sample had a high percentage of midline aneurysms, and this may influence neurocognitive sequela, and
- MEG signal characteristics were evaluated in the same seed locations for aSAH and matched controls, thus, the only differences were the previous hemorrhage and the presence of the coils.
Balart-Sanchez and colleagues (2021) noted that cognitive reserve (CR) is the capacity to adapt to (future) brain damage without any or only minimal clinical symptoms; however, the underlying neuroplastic mechanisms remain unclear. Electrocorticography (ECOG), electroencephalography (EEG), and magnetoencephalography (MEG) may help elucidate the brain mechanisms underlying CR, as CR is thought to be related to efficient utilization of remaining brain resources. In a systematic review, these investigators examined the findings on neural correlates of CR estimates using ECOG, EEG, and MEG. They assessed studies that were published from the first standardized definition of CR; 11 EEG and 5 MEG cross-sectional studies met the inclusion criteria. They concerned original research, analyzed (M)EEG in humans, used a validated CR estimate, and related (M)EEG to CR. Quality assessment was performed using an adapted form of the Newcastle-Ottawa scale. No ECOG study met the inclusion criteria. A total of 1,383 subjects from heterogeneous patient, young and older healthy groups were divided into 3 categories by (M)EEG methodology: 8 (M)EEG studies employed event-related fields or potentials, 6 studies analyzed brain oscillations at rest (of which 1 also analyzed a cognitive task), and 3 studies analyzed brain connectivity. Various CR estimates were used; and all studies compared different (M)EEG measures and CR estimates. Several associations between (M)EEG measures and CR estimates were observed. The authors concluded that the findings of the current review support that (M)EEG measures are related to CR estimates, especially in healthy individuals. The presence and character of this relationship is highly variable and depends on the population and task that were studied and on the analysis technique that was used. It should also be noted that some of these relationships were reflected in differences in (M)EEG measures between groups with high or low estimated CR, without establishing a direct relationship such as a correlation or in a predictive model, between (M)EEG measures and CR estimates. These researchers stated that it remains unclear why such a relationship was only found in one patient study using EEG oscillations. To elucidate this issue and avoid the variability in populations and tasks that was encountered in this review, a sufficiently powered study in neurologically afflicted patients that compares the correlation between different (M)EEG measures and different CR estimates, within this one group, might help.
Differentiation of Post-Traumatic Stress Disorder and Traumatic Brain Injury
Rowland and colleagues (2017) evaluated alterations in whole-brain resting-state networks associated with post-traumatic stress disorder (PTSD) and mTBI. Networks were constructed from locations of peak statistical power on an individual basis from MEG source series data by applying the weighted phase lag index and surrogate data thresholding procedures. Networks representing activity in the alpha bandwidth as well as wideband activity (DC-80 Hz) were created. Statistical comparisons were adjusted for age and education level. Alpha network results demonstrate reductions in network structure associated with PTSD, but no differences associated with mTBI. Wideband network results demonstrated a shift in connectivity from the alpha to theta bandwidth in both PTSD and mTBI. In addition, contrasting alterations in network structure were noted, with increased randomness associated with PTSD and increased structure associated with mTBI. The authors concluded that these findings demonstrated the potential of the analysis of MEG resting-state networks to differentiate 2 highly co-morbid conditions.
Allen and colleagues (2021) stated that the global incidence of TBI is rising, with at least 80 % being classified as mild. These mild injuries are not visible on routine clinical imaging. The potential clinical role of a specific imaging biomarker be it diagnostic, prognostic or directing and monitoring progress of personalized treatment and rehabilitation has driven the exploration of several new neuroimaging modalities. In a systematic review, these researchers examined the evidence for MEG to provide an imaging biomarker in mild TBI (mTBI). They searched Embase, Medline, trial registers, PsycINFO, Cochrane Library and conference abstracts and identified 37 papers describing MEG changes in mTBI eligible for inclusion. Since meta-analysis was not possible, based on the heterogeneity of reported outcomes, these investigators provided a narrative synthesis of results. The 2 most promising MEG biomarkers were excess resting state low-frequency power, and widespread connectivity changes in all frequency bands. These may represent biomarkers with potential for diagnostic application, which reflect time sensitive changes, or may be capable of offering clinically relevant prognostic information. Furthermore, the rich data that MEG produced were well-suited to new methods of machine learning analysis, which is now being actively examine. The authors concluded that MEG revealed several promising biomarkers, in the absence of structural abnormalities demonstrable with either computerized tomography (CT) or MRI. This review has not identified sufficient evidence to support routine clinical use of MEG in mTBI currently; however, verifying MEG's potential would help meet an urgent clinical need within civilian, sports and military medicine.
Neuroimaging Correlates of Syndromal Anxiety Following Traumatic Brain Injury
Jahed and colleagues (2022) noted that TBI can precipitate new-onset psychiatric symptoms or worsen existing psychiatric conditions. To elucidate specific mechanisms for this interaction, neuroimaging is often used to study both psychiatric conditions and TBI. In a systematic review, these researchers examined the existing literature of neuroimaging findings among patients with anxiety following TBI. They carried out a Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) compliant literature search via PubMed (Medline), PsychINFO, Embase, and Scopus databases before May 2019. These investigators included studies that defined TBI, measured syndromic anxiety as a primary outcome, and analyzed the relationship between neuroimaging findings and anxiety symptoms. A total of 5,982 articles were retrieved from the systematic search, of which 65 studied anxiety and 13 met eligibility criteria. These studies were published between 2004 and 2017, collectively analyzing 764 subjects comprised of 470 patients with TBI and 294 non-TBI controls. Imaging modalities used included MRI, functional MRI (fMRI), diffusion tensor imaging (DTI), EEG, magnetic resonance spectrometry (MRS), and MEG; 8 of 13 studies presented at least 1 significant finding and together reflect a complex set of changes that lead to anxiety in the setting of TBI. The left cingulate gyrus in particular was found to be significant in 2 studies using different imaging modalities; 2 studies also revealed perturbances in functional connectivity within the default mode network. The authors concluded that this was the first systemic review of neuroimaging changes associated with anxiety following TBI, which implicated multiple brain structures and circuits, such as the default mode network. They stated that future research with consistent, rigorous measurements of TBI and syndromic anxiety, as well as attention to control groups, previous TBIs, and time interval between TBI and neuroimaging, are needed. By understanding neuroimaging correlates of psychiatric symptoms, this work could inform future post-TBI screening and surveillance, preventative efforts, and early interventions to improve neuropsychiatric outcomes.
Characterization of the Effects of Deep Brain Stimulation
Harmsen and colleagues (2018) stated deep brain stimulation (DBS) is an important form of neuromodulation that is being applied to patients with motor, mood, or cognitive circuit disorders. Despite the efficacy and widespread use of DBS, the precise mechanisms by which it works remain unknown. Over the past 10 years, MEG has become an important functional neuroimaging technique used to study DBS. These investigators summarized the literature related to the use of MEG to characterize the effects of DBS. Peer-reviewed literature on DBS-MEG was obtained by searching the publicly accessible literature databases available on PubMed. The abstracts of all reports were scanned and publications which combined DBS-MEG in human subjects were selected for review. A total of 32 publications met the selection criteria, and included studies which applied DBS for Parkinson's disease, dystonia, chronic pain, phantom limb pain, cluster headache, and epilepsy; DBS-MEG studies provided valuable insights into network connectivity, pathological coupling, and the modulatory effects of DBS. The authors concluded that as DBS-MEG research continues to develop, one can expect to gain a better understanding of diverse pathophysiological networks and their response to DBS. This knowledge will improve treatment efficacy, reduce side-effects, reveal optimal surgical targets, and advance the development of closed-loop neuromodulation.
Gopalakrishnan and associates (2018) noted that post-stroke pain syndrome (PSPS) is an intractable disorder characterized by hemiparesis associated with unrelenting chronic pain. While traditional analgesia have largely failed, integrative approaches targeting affective-cognitive spheres have started to show promise. Recently, these researchers demonstrated that DBS of the ventral striatal area significantly improved the affective sphere of pain in PSPS patients. These researchers examined if electrophysiological correlates of pain anticipation were modulated by DBS that could serve as signatures of treatment effects. They recorded event-related fields (ERFs) of pain anticipation using MEG in 10 PSPS patients pre-operatively and post-operatively in DBS OFF- and ON-states. Simple visual cues evoked anticipation as patients awaited a painful stimulus (PS) or non-painful stimulus (NPS) to the non-affected or affected extremity. Pre-operatively, ERFs showed no difference between PS and NPS anticipation to the affected extremity, possibly due to loss of salience in a network saturated by pain experience; DBS significantly modulated the early N1, consistent with improvements in affective networks involving restoration of salience and discrimination capacity. Additionally, DBS suppressed the posterior P2 (aberrant anticipatory anxiety) while enhancing the anterior N1 (cognitive and emotional regulation) in responders. The authors concluded that DBS-induced changes in ERFs could potentially serve as signatures for clinical outcomes.
Magnetoencephalography for Prediction of Upper Limb Sensorimotor Recovery after Stroke
Tedesco Triccas and colleagues (2019) noted that predicting sensorimotor upper limb outcome receives continued attention in stroke. Neurophysiological measures by EEG and MEG could increase the accuracy of predicting sensorimotor upper limb recovery. In a systematic review, these investigators summarized the current evidence for EEG/MEG-based measures to index neural activity after stroke and the relationship between abnormal neural activity and sensorimotor upper limb impairment. Relevant papers from databases Embase, CINHAL, Medline and PubMed were identified. Methodological quality of selected studies was assessed with the Modified Downs and Black form. Data collected was reported descriptively. A total of 17 papers were included; 13 used EEG and 4 used MEG applications. Findings showed that: (a) the presence of somatosensory evoked potentials (SSEPs) in the acute stage are related to better outcome of upper limb motor impairment from 10 weeks to 6 months post-stroke; (b) an inter-hemispheric imbalance of cortical oscillatory signals associated with upper limb impairment; and (c) predictive models including beta oscillatory cortical signal factors with cortico-spinal integrity and clinical measures could enhance upper limb motor prognosis. The combination of neurological biomarkers with clinical measures resulted in higher statistical power than using neurological biomarkers alone when predicting motor recovery in stroke. The authors concluded that this was the first review to explore different types of EEG and MEG measures in relation to sensorimotor upper limb impairments after stroke. Presence of SSEPs were related to better outcome of upper limb motor impairment post stroke in the sub-acute and chronic stages. An imbalance of cortical oscillatory signals between the ipsilesional and contralesional hemispheres with movement of the affected upper limb was identified. An increase in beta activity in contralesional hemisphere correlated with poorer upper limb motor outcome in the chronic stage. Additionally, predictive models with beta oscillatory cortical signal factors with corticospinal integrity and motor clinical measures could predict upper limb motor recovery. These researchers stated that future research should explore EEG or MEG measurements in the acute stage of stroke with a larger sample of stroke participants with stratification for location of stroke and upper limb motor and somatosensory severity. This could provide accurate biomarkers of recovery leading to better stratification of patients for clinical trials and inform evidence-based practice.
The authors stated that this review had 2 main drawbacks. First, it was essential to include evidence from high-quality studies and thus, only 17 from 47 full-text papers were included. This resulted in prohibiting sub-group analyses of different types, stages and locations of stroke, highlighting the need for additional high-quality studies to evaluate the potential clinical utility of EEG and MEG measures to inform stroke rehabilitation. Second, an unusual number of 25 % of the sample were women included in this review compared to the expected 50 %; thus, gender bias could have influenced the results.
MSI / MEG for Evaluation of Memory and Language Decline Following Epilepsy Surgery
In a systematic review, Schmid and colleagues (2018) examined the diagnostic accuracy of fMRI, Wada test, MEG, and functional transcranial Doppler sonography (fTCD) for memory and language decline following epilepsy surgery. The literature search was conducted using PubMed, Embase, and CENTRAL. The diagnostic accuracy was expressed in terms of sensitivity and specificity for post-operative language or memory decline, as determined by pre- and post-operative neuropsychological assessments. If 2 or more estimates of sensitivity or specificity were extracted from a study, 2 meta-analyses were conducted, using the maximum ("best case") and the minimum ("worst case") of the extracted estimates, respectively. A total of 28 papers were eligible for data extraction and further analysis. All tests for heterogeneity were highly significant, indicating large between-study variability (p < 0.001). For memory outcomes, meta-analyses were conducted for Wada tests (n = 17) using both memory and language laterality quotients. In the best case, meta-analyses yielded a sensitivity estimate of 0.79 (95 % CI: 0.67 to 0.92) and a specificity estimate of 0.65 (95 % CI: 0.47 to 0.83). For the worst case, meta-analyses yielded a sensitivity estimate of 0.65 (95 % CI: 0.48 to 0.82) and a specificity estimate of 0.46 (95 % CI: 0.28 to 0.65). The overall quality of evidence, which was assessed using Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology, was rated as very low. Meta-analyses concerning diagnostic accuracy of fMRI, fTCD, and MEG were not feasible due to small numbers of studies (fMRI, n = 4; fTCD, n = 1; MEG, n = 0). This also applied to studies concerning language outcomes (Wada test, n = 6; fMRI, n = 2; fTCD, n = 1; MEG, n = 0). The authors concluded that meta-analyses could only be conducted in a few sub-groups for the Wada test with low-quality evidence. These researchers stated that more evidence from high-quality studies and improved data reporting are needed. Moreover, the large between-study heterogeneity underlined the necessity for more homogeneous and thus comparable studies in future research.
MSI / MEG for Evaluation of Multiple Sclerosis and Multiple Sclerosis-Related Pain
Kim and colleagues (2019) noted that chronic pain is a common occurrence in multiple sclerosis (MS) that severely affects quality of life (QOL), but the underlying brain mechanisms related to these symptoms are unknown. Previous EEG studies have demonstrated a role of alpha-band and beta-band power in pain processing. However, how and where these brain signals change in MS-related chronic pain is unknown. These researchers employed resting state MEG to examine regional spectral power in the dynamic pain connectome-including areas of the ascending nociceptive pathway, default mode network (DMN), and the salience network (SN)-in patients with chronic MS pain and in healthy controls. Each patient was evaluated for pain, neuropathic pain (NP), and pain interference with activities of daily living (ADL). These investigators found that patients with MS exhibited an increase of alpha-band power and a decrease of beta-band power, most prominently in the thalamus and the posterior insula of the ascending nociceptive pathway and in the right temporo-parietal junction of the SN. In addition, patients with mixed-NP exhibited slowing of alpha peak power within the thalamus and the posterior insula, and in the posterior cingulate cortex of the DMN. Finally, pain interference scores in patients with mixed-NP were strongly correlated with alpha and beta peak power in the thalamus and posterior insula. The authors concluded that these novel findings revealed brain mechanisms of MS-related pain in the ascending nociceptive pathway, SN, and DMN, and that these spectral abnormalities reflect the impact of pain on QOL measures. These preliminary findings need to be further investigated.
In a systematic review, Khan and colleagues (2021) examined the evidence on the use of MEG in patients with MS. These researchers identified MEG studies performed in MS using Embase, Medline, Cochrane, TRIP and Psychinfo databases. They included original research articles with a cohort of minimum of 5 MS patients and quantifying of at least 1 MEG parameter. These investigators used a modified version of the JBI (mJBI) for case-control studies to evaluate risk of bias. They identified 30 studies from 13 centers entailing at least 433 MS patients and 347 controls. These researchers found evidence that MEG showed perturbed activity (most commonly reduced power modulations), reduced connectivity and association with altered clinical function in patients with MS. Specific replicated findings were decreased motor induced responses in the beta band, diminished increase of gamma power after visual stimulation, increased latency and reduced connectivity for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive measures in individuals with MS. Overall studies were of moderate quality (mean mJBI score of 6.7). The authors found evidence for the use of MEG in patients with MS; event-related designs are of particular value and showed replicability between centers. At this stage, it is unclear if these changes were specific to MS or are also observable in other diseases. These investigators stated that further studies should look to examine cognitive control in more depth using in-task designs and undertake longitudinal studies to examine if these changes have prognostic value.
The authors stated that this review had several drawbacks. First, the use of a wide variety of parameters made direct comparison between studies difficult. Second, these investigators noted the possibility of publication bias in this review -- 6 records showed pre-registration of studies, but none of these have as yet been published or were included in this review. Conversely none of the included studies included reference to pre-planned analyses. It was likely that there was a skew to publish positive findings in the studies included. Third, because of the heterogeneity of study designs and analyses, these researchers did not independently screen studies, rather reviewers screened and extracted data with mutual consultation. Finally, these investigators unable to examine if these changes were specific to MS. One study using a data driven approach showed changes in connectivity (using correlations between all sensors) were specific to MS rather than other states after using a Canonical Discriminant Function; however, no other study used disease controls other than healthy controls. The authors also noted some overlap in their findings with other conditions -- attenuations in Post Movement Beta Rebound amplitude have been shown in schizophrenia and schizotypal disorder, while disruption in alpha connectivity is also shown in Alzheimer’s disease; thus, these researchers were unable to specifically determine whether these findings were specific to MS or evidence of a more general brain deficit. Studies which compared different clinical groups with different diagnoses would need to be undertaken to examine if these findings are specific to MS.
Electro-Magnetic Source Imaging in Pre-Surgical Workup of Patients with Epilepsy
In a prospective study, Duez and colleagues (2019) determined the diagnostic accuracy and clinical utility of electro-magnetic source imaging (EMSI) in pre-surgical evaluation of patients with epilepsy. These researchers prospectively recorded MEG simultaneously with EEG and performed EMSI, comprising electric source imaging, MSI, and analysis of combined MEG-EEG datasets, using 2 different software packages. As reference standard for irritative zone (IZ) and seizure onset zone (SOZ), these investigators used intra-cranial recordings (ICRs) and for localization accuracy, outcome 1 year after operation. These investigators included 141 consecutive patients; EMSI showed localized epileptiform discharges in 94 patients (67 %). Most of the epileptiform discharge clusters (72 %) were identified by both modalities, 15 % only by EEG, and 14 % only by MEG. Agreement was substantial between inverse solutions and moderate between software packages; EMSI provided new information that changed the management plan in 34 % of the patients, and these changes were useful in 80 %. Depending on the method, EMSI had a concordance of 53 % to 89 % with IZ and 35 % to 73 % with SOZ. Localization accuracy of EMSI was between 44 % and 57 %, which was not significantly different from MRI (49 % to 76 %) and PET (54 % to 85%). Combined EMSI achieved significantly higher OR compared to electric source imaging and MSI. The authors concluded that EMSI had accuracy similar to established imaging methods and provided clinically useful, new information in 34 % of the patients. The evidence provided by this study was categorized as Class IV, because implantation of intra-cranial electrodes was not blinded to the results of the EMSI and less than 80 % of the patients had been implanted or operated. Since locations shown by EMSI need to be implanted for validation, it was technically impossible to do this blinded to the EMSI. Furthermore, typically less than 50 % of the patients entering pre-surgical evaluation were implanted or operated. Thus, it was practically impossible to achieve a higher class of evidence for diagnostic studies in pre-surgical evaluation of patients with epilepsy.
The authors stated that this study had several drawbacks. First, almost all patients in whom EMSI was part of the clinical workup consented to the study (normal MRI or discordant MRI, EEG, and semiology). However, this was not the case for patients whose decision regarding operation was reached based on concordant MRI, EEG, and semiology and where EMSI was not part of the clinical workup. Thus, more complex cases might be over-represented in this study. Second, all patients were undergoing a pre-surgical evaluation in the Danish national epilepsy surgery program, and all MEG-EEG were recorded and analyzed at Aarhus University Hospital. Although these researchers addressed the variability introduced by 2 different software packages and analyzers, this study was single-centered. Third, perfect reference standard lacks for pre-surgical evaluation. Because of spatial sampling problems, ICRs can be misleading. However, using resection site and post-operative outcome as reference standard has its drawbacks too: despite correct localization of IZ and SOZ, patients might not become seizure-free, since IZ and SOZ do not necessarily coincide with the epileptogenic zone. Thus, these investigators opted for using both datasets as reference standard, and they emphasized the intrinsic limitations of both approaches.
Staging of Emerging Psychosis
Grent-'t-Jong and colleagues (2020) stated that psychotic disorders are characterized by impairments in neural oscillations, but the nature of the deficit, the trajectory across illness stages, and the functional relevance remain unclear. In a cross-sectional study, these researchers examined if changes in spectral power, phase locking, and functional connectivity in visual cortex are present during emerging psychosis and whether these abnormalities are associated with clinical outcomes. Subjects meeting clinical high-risk criteria for psychosis, subjects with 1st-episode psychosis, subjects with affective disorders and substance abuse, and a group of control subjects were recruited. Participants underwent measurements with MEG and MRI. Data analysis was performed between 2018 and 2019. Magnetoencephalographical activity was examined in the 1- to 90-Hz frequency range in combination with source reconstruction during a visual grating task. Event-related fields, power modulation, intertrial phase consistency, and connectivity measures in visual and frontal cortices were associated with neuropsychological scores, psychosocial functioning, and clinical symptoms as well as persistence of sub-threshold psychotic symptoms at 12 months. The study participants included those meeting clinical high-risk criteria for psychosis (n = 119; mean [SD] age, 22 [4.4] years; 32 men), 26 patients with 1st-episode psychosis (mean [SD] age, 24 [4.2] years; 16 men), 38 participants with affective disorders and substance abuse (mean [SD] age, 23 [4.7] years; 11 men), and 49 control participants (mean age [SD], 23 [3.6] years; 16 men). Clinical high-risk participants and patients with 1st-episode psychosis were characterized by reduced phase consistency of β/γ-band oscillations in visual cortex (d = 0.63/d = 0.93). Moreover, the 1st-episode psychosis group was also characterized by reduced occipital γ-band power (d = 1.14) and altered visual cortex connectivity (d = 0.74-0.84). Impaired fronto-occipital connectivity was present in both clinical high-risk participants (d = 0.54) and patients with 1st-episode psychosis (d = 0.84). More importantly, reductions in intertrial phase coherence predicted persistence of sub-threshold psychosis in clinical high-risk participants (receiver operating characteristic area under curve = 0.728; 95 % confidence interval [CI]: 0.612 to 0.841; p = 0.001). The authors concluded that high-frequency oscillations are impaired in the visual cortex during emerging psychosis and may be linked to behavioral and clinical impairments. Impaired phase consistency of γ-band oscillations was also associated with the persistence of subthreshold psychosis, suggesting that magnetoencephalographical measured neural oscillations could constitute a biomarker for clinical staging of emerging psychosis.
Furthermore, UpToDate reviews on “First episode psychosis” (2021), and “Brief psychotic disorder” (Mojtabai, 2021) do not mention magnetoencephalography as a management option.
Biomarkers of Chronic Pain
Zebhauser et al (2022) noted that reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state EEG is broadly available, easy to use, and cost-effective; thus, it is appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. In a systematic review, these investigators examined quantitative resting-state EEG and MEG studies in adult patients with different types of chronic pain. They excluded populations with severe psychiatric or neurologic co-morbidity. Risk of bias was evaluated using a modified Newcastle-Ottawa Scale. Semi-quantitative data synthesis was carried out using modified albatross plots. These researchers included 76 studies after searching Medline, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and Embase. For cross-sectional studies that could serve to develop diagnostic biomarkers, these investigators found higher theta and beta power in patients with chronic pain than in healthy subjects. For longitudinal studies that could yield monitoring and/or predictive biomarkers, these investigators found no clear associations of pain relief with MEG/EEG measures. Similarly, descriptive studies that could yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with MEG/EEG measures. Risk of bias was high in many studies and domains. The authors concluded that this systematic review synthesized evidence on how resting-state MEG/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might aid in guiding future MEG/EEG studies on the development of pain biomarkers. Moreover, these researchers stated that to proceed and better examine the potential of MEG/EEG as biomarkers of pain, large-scale studies that differentiate biomarker types, evaluate biomarker specificity, examine brain network connectivity, adhere to highest standards of transparency/reproducibility, and explore the potential of composite biomarkers are most promising.
The authors stated that this review had several drawbacks. Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy to use, and cost efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. Therefore, we conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting-state EEG and magnetoencephalography (MEG) studies in adult patients with different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semiquantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and EMBASE. For cross-sectional studies that can serve to develop diagnostic biomarkers, we found higher theta and beta power in patients with chronic pain than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Similarly, descriptive studies that can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, this systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might help to guide future M/EEG studies on the development of pain biomarkers.
Correlates of Suicidal Ideation and Suicide Attempt History in Patients with Treatment-Resistant Major Depression
Gilbert et al (2022) examined MEG correlates of suicidal ideation (SI) and suicide attempt history in patients with treatment-resistant major depression (TRD) at baseline and following subanesthetic-dose ketamine infusion. A total of 29 drug-free TRD patients (12 suicide attempters/17 non-attempters) participated in a cross-over randomized trial of ketamine. MEG data were collected during an attentional dot probe task with emotional face stimuli at baseline and several hours post-ketamine infusion. Synthetic aperture magnetometry was used to project source power in the theta, alpha, beta, and gamma frequencies for angry-neutral, happy-neutral, and neutral-neutral face pairings during a 1-second peri-stimulus period. Mixed models were used to test for clinical, behavioral, and electrophysiological effects of group, emotion, session, and SI score. Ketamine significantly reduced SI and depression across the sample. Post-ketamine, attempters had improved accuracy and non-attempters had reduced accuracy on the task. SI was positively associated with gamma power in regions of the frontal and parietal cortices across groups. In an extended amygdala-hippocampal region, attempters differed significantly in their emotional reactivity to angry versus happy faces as indexed by theta power differences, irrespective of drug. Ketamine significantly reduced the association between alpha power and SI for angry compared with happy faces in a fronto-insular/anterior cingulate region important for regulating sensory attentiveness. The authors concluded that the findings of this trial highlighted key differences in band-limited power between attempters and non-attempters and reinforced previous findings that ketamine had distinct response properties in patients with a suicide history. These researchers noted that the drawbacks of tis study included a small sample size of suicide attempters (n = 12).
Planning for Cerebellar Aneurysm Clipping
An UpToDate review on “Unruptured intracranial aneurysms” (Singer et al, 2023) does not mention magnetic source imaging/magnetoencephalography as a management option.
References
The above policy is based on the following references:
- Agirre-Arrizubieta Z, Thai NJ, Valentín A, et al. The value of magnetoencephalography to guide electrode implantation in epilepsy. Brain Topogr. 2014;27(1):197-207.
- Alberstone CD, Skirboll SL, Benzel EC, et al. Magnetic source imaging and brain surgery: Presurgical and intraoperative planning in 26 patients. J Neurosurg. 2000;92(1):79-90.
- Alhourani A, Wozny TA, Krishnaswamy D, et al. Magnetoencephalography-based identification of functional connectivity network disruption following mild traumatic brain injury. J Neurophysiol. 2016;116(4):1840-1847.
- Allen CM, Halsey L, Topcu G, et al. Magnetoencephalography abnormalities in adult mild traumatic brain injury: A systematic review. Neuroimage Clin. 2021;31:102697.
- American Academy of Neurology Professional Association (AANPA). Magnetoencephalography (MEG) Policy. Recommended by the AANPA Medical Economics and Management Committee. Approved by the AANPA Board of Directors on May 8, 2009. St. Paul, MN: AANPA; 2009.
- American Academy of Neurology. Assessment: Magnetoencephalography (MEG). Report of the Therapeutic and Technology Assessment Subcommittee of the American Academy of Neurology. Neurology. 1992;42:1-4.
- Amyot F, Arciniegas DB, Brazaitis MP, et al. A review of the effectiveness of neuroimaging modalities for the detection of traumatic brain injury. J Neurotrauma. 2015;32(22):1693-1721.
- Bagic A, Funke ME, Ebersole J; ACMEGS Position Statement Committee. American Clinical MEG Society (ACMEGS) position statement: The value of magnetoencephalography (MEG)/magnetic source imaging (MSI) in noninvasive presurgical evaluation of patients with medically intractable localization-related epilepsy. J Clin Neurophysiol. 2009;26(4):290-293.
- Balart-Sanchez SA, Bittencourt-Villalpando M, van der Naalt J, Maurits NM. Electroencephalography, magnetoencephalography, and cognitive reserve: A systematic review. Arch Clin Neuropsychol. 2021;36(7):1374-1391.
- Barkley GL. Controversies in neurophysiology. MEG is superior to EEG in localization of interictal epileptiform activity: Pro. Clin Neurophysiol. 2004;115(5):1001-1009.
- Baumgartner C. Controversies in clinical neurophysiology. MEG is superior to EEG in the localization of interictal epileptiform activity: Con. Clin Neurophysiol. 2004;115(5):1010-1020.
- Billingsley-Marshall RL, Simos PG, Papanicolaou AC. Reliability and validity of functional neuroimaging techniques for identifying language-critical areas in children and adults. Dev Neuropsychol. 2004;26(2):541-563.
- BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Magnetoencephalography and magnetic source imaging: Presurgical localization of epileptic lesions and presurgical functional mapping. TEC Assessment Program. Chicago, IL: BCBSA; August 2003;18(6).
- BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Special report: MEG and MSI for the purpose of presurgical localization of epileptic lesions -- A challenge for technology evaluation. TEC Assessment Program. Chicago, IL: BCBSA; January 2009;23(8).
- Blumenfeld LD, Clementz BA. Response to the first stimulus determines reduced auditory evoked response suppression in schizophrenia: Single trials analysis using MEG. Clin Neurophysiol. 2001;112(9):1650-1659.
- Bowen JM, Snead OC III, Hopkins RB, et al. Diagnostic evaluation of infants, children and adolescents with epilepsy for surgery candidacy and the role of magnetoencephalography (MEG). Report No. FEEAP-M0013a-REP. Hamilton, ON: Programs for Assessment of Technology in Health, St. Joseph’s Healthcare Hamilton/McMaster University; October 2011.
- Cimon K, Spry C. Magnetoencephalography (MEG) for seizure disorders in children: Clinical effectiveness. Health Technology Inquiry Service (HTIS). Ottawa, ON: Canadian Agency for Drugs and Technologies in Health (CADTH); September 2, 2009.
- Clark M, Spry C. Magnetoencephalography for neurocognitive disorders: Clinical effectiveness. Health Technology Inquiry Service (HTIS). Ottawa, ON: Canadian Agency for Drugs and Technologies in Health (CADTH); September 2, 2009.
- Corabian P, Hailey D. Functional diagnostic imaging in epilepsy. Technology Assessment Report. Pub. No. HTA10. Edmonton, AB: Alberta Heritage Foundation for Medical Research; August 1998.
- Criado JR, Amo C, Quint P, et al. Using magnetoencephalography to study patterns of brain magnetic activity in Alzheimer's disease. Am J Alzheimers Dis Other Demen. 2006;21(6):416-423.
- Cruse RP. Pathophysiology, clinical features, and diagnosis of migraine in children. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed January 2014.
- Cutrer FM, Bajwa ZH, Sabahat A. Pathophysiology, clinical manifestations, and diagnosis of migraine in adults. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed January 2014.
- da Costa L, Dunkley BT, Bethune A, et al. Feasibility of magnetoencephalography after endovascular treatment of ruptured intracranial aneurysms. Front Neurol. 2016;7:163.
- da Costa L, Robertson A, Bethune A, et al. Delayed and disorganised brain activation detected with magnetoencephalography after mild traumatic brain injury. J Neurol Neurosurg Psychiatry. 2015;86(9):1008-1115.
- Das S, Zomorrodi R, Mirjalili M, et al. Machine learning approaches for electroencephalography and magnetoencephalography analyses in autism spectrum disorder: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry. 2023;123:110705.
- Duez L, Tankisi H, Hansen PO, et al. Electromagnetic source imaging in presurgical workup of patients with epilepsy: A prospective study. Neurology. 2019;92(6):e576-e586.
- Ebersole JS. Magnetoencephalography/magnetic source imaging in the assessment of patients with epilepsy. Epilepsia. 1997;38(Suppl 4):S1-S5.
- Falco-Walter J, Owen C, Sharma M, et al. Magnetoencephalography and new imaging modalities in epilepsy. Neurotherapeutics. 2017;14(1):4-10.
- Feichtinger M, Holl A, Korner E, Schrottner O, et al. Future aspects of the presurgical evaluation in epilepsy. Acta Neurochir Suppl. 2002;84:17-26.
- Feuerriegel D, Churches O, Hofmann J, Keage HA. The N170 and face perception in psychiatric and neurological disorders: A systematic review. Clin Neurophysiol. 2015;126(6):1141-1158.
- Filipek PA, Accardo PJ, Ashwal S, et al. American Academy of Neurology. Practice parameter: Screening and diagnosis of autism. Report of the Quality Standards Subcommittee of the American Academy of Neurology and the Child Neurology Society. Neurology. 2000;55(4):468-479.
- Funke M, Constantino T, Van Orman C, Rodin E. Magnetoencephalography and magnetic source imaging in epilepsy. Clin EEG Neurosci. 2009;40(4):271-280.
- Gallen CC, et al. Intracranial neurosurgery guided by functional imaging. Surg Neurol. 1994;42:523-530.
- Gallen CC, et al. Magnetic source imaging of abnormal low-frequency magnetic activity in presurgical evaluation of epilepsy. Epilepsia. 1997;38(4):452-460.
- Gallen CC, et al. Presurgical localization of functional cortex using magnetic source imaging. J Neurosurg. 1995;82(6):988-994.
- Gallen CC, Sobel DF, Lewine JD, et al. Neuromagnetic mapping of brain function. Radiology. 1993;187:863-867.
- Gilbert JR, Gerner JL, Burton CR, et al. Magnetoencephalography biomarkers of suicide attempt history and antidepressant response to ketamine in treatment-resistant major depression. J Affect Disord. 2022;312:188-197.
- Gopalakrishnan R, Burgess RC, Malone DA, et al. Deep brain stimulation of the ventral striatal area for post-stroke pain syndrome: A magnetoencephalography study. J Neurophysiol. 2018;119(6):2118-2128.
- Grent-'t-Jong T, Gajwani R, Gross J, et al. Association of magnetoencephalographically measured high-frequency oscillations in visual cortex with circuit dysfunctions in local and large-scale networks during emerging psychosis. JAMA Psychiatry. 2020;77(8):852-862.
- Grover KM, Bowyer SM, Rock J, et al. Retrospective review of MEG visual evoked hemifield responses prior to resection of temporo-parieto-occipital lesions. J Neurooncol. 2006;77(2):161-166.
- Haddad N, Govindan RB, Vairavan S, et al. Correlation between fetal brain activity patterns and behavioral states: An exploratory fetal magnetoencephalography study. Exp Neurol. 2011;228(2):200-205.
- Harmsen IE, Rowland NC, Wennberg RA, Lozano AM. Characterizing the effects of deep brain stimulation with magnetoencephalography: A review. Brain Stimul. 2018 2018;11(3):481-491.
- Inoue T, Shimizu H, Nakasato N, et al. Accuracy and limitation of functional magnetic resonance imaging for identification of the central sulcus: Comparison with magnetoencephalography in patients with brain tumors. Neuroimage. 1999;10(6):738-748.
- Jahed S, Daneshvari NO, Liang AL, et al. Neuroimaging correlates of syndromal anxiety following traumatic brain injury: A systematic review of the literature. J Acad Consult Liaison Psychiatry. 2022;63(2):119-132.
- Kadenhead K. First episode psychosis. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed January 2021.
- Khan H, Sami MB, Litvak V. The utility of magnetoencephalography in multiple sclerosis - A systematic review. Neuroimage Clin. 2021;32:102814.
- Kim JA, Bosma RL, Hemington KS, et al. Neuropathic pain and pain interference are linked to alpha-band slowing and reduced beta-band magnetoencephalography activity within the dynamic pain connectome in patients with multiple sclerosis. Pain. 2019;160(1):187-197.
- Knowlton RC, Elgavish RA, Howell J, et al. Magnetic source imaging versus intracranial electroencephalogram in epilepsy surgery: A prospective study. Ann Neurol. 2006;59(5):835-842.
- Knowlton RC, Elgavish RA, Bartolucci A, et al. Functional imaging: II. Prediction of epilepsy surgery outcome. Ann Neurol. 2008;64(1):35-41.
- Knowlton RC, Elgavish RA, Limdi N, et al. Functional imaging: I. Relative predictive value of intracranial electroencephalography. Ann Neurol. 2008;64(1):25-34.
- Knowlton RC, Shih J. Magnetoencephalography in epilepsy. Epilepsia. 2004;45 Suppl 4:61-71.
- Knowlton RC. Can magnetoencephalography aid epilepsy surgery? Epilepsy Curr. 2008;8(1):1-5.
- Ko DY, et al. Source localization determined by magnetoencephalography and electroencephalography in temporal lobe epilepsy: Comparison with electrocorticography: Technical case report. Neurosurgery. 1998;42(2):414-421.
- Korvenoja A, Kirveskari E, Aronen HJ, et al. Sensorimotor cortex localization: Comparison of magnetoencephalography, functional MR imaging, and intraoperative cortical mapping. Radiology. 2006;241(1):213-222.
- Kuzniecky RI, Knowlton RC. Neuroimaging of epilepsy. Semin Neurol. 2002;22(3):279-288.
- Lajiness-O'Neill R, Brennan JR, Moran JE, et al. Patterns of altered neural synchrony in the default mode network in autism spectrum disorder revealed with magnetoencephalography (MEG): Relationship to clinical symptomatology. Autism Res. 2018;11(3):434-449.
- Lau M, Yam D, Burneo JG. A systematic review on MEG and its use in the presurgical evaluation of localization-related epilepsy. Epilepsy Res. 2008;79(2-3):97-104.
- Leijten FS, Huiskamp G. Interictal electromagnetic source imaging in focal epilepsy: Practices, results and recommendations. Curr Opin Neurol. 2008;21(4):437-445.
- Lopes da Silva FH. What is magnetoencephalography and why it is relevant to neurosurgery? Adv Tech Stand Neurosurg. 2005;30:51-67.
- Lowery CL, Govindan RB, Preissl H, et al. Fetal neurological assessment using noninvasive magnetoencephalography. Clin Perinatol. 2009;36(3):701-709.
- Mojtabai R. Brief psychotic disorder. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed January 2021.
- Ontario Ministry of Health, Medical Advisory Secretariat (MAS). Functional brain imaging. Health Technology Policy Assessment. Toronto, ON: MAS; December 2006.
- Orrison WW, et al. Noninvasive preoperative cortical localization by magnetic source imaging. AJNR. 1992;13:1124-1128.
- Papanicolaou AC, Pataraia E, Billingsley-Marshall R, et al. Toward the substitution of invasive electroencephalography in epilepsy surgery. J Clin Neurophysiol. 2005;22(4):231-237.
- Parra J, Kalitzin SN, da Silva FH. Magnetoencephalography: An investigational tool or a routine clinical technique? Epilepsy Behav. 2004;5(3):277-285.
- Pataraia E, Lindinger G, Deecke L, et al. Combined MEG/EEG analysis of the interictal spike complex in mesial temporal lobe epilepsy. Neuroimage. 2005;24(3):607-614.
- Pelletier I, Sauerwein HC, Lepore F, et al. Non-invasive alternatives to the Wada test in the presurgical evaluation of language and memory functions in epilepsy patients. Epileptic Disord. 2007;9(2):111-126.
- Poza J, Hornero R, Abásolo D, et al. Evaluation of spectral ratio measures from spontaneous MEG recordings in patients with Alzheimer's disease. Comput Methods Programs Biomed. 2008;90(2):137-147.
- Rampp S, Stefan H. Magnetoencephalography in presurgical epilepsy diagnosis. Expert Rev Med Devices. 2007;4(3):335-347.
- Reite M, Teale R, Rohas DC. Magnetoencephalography: Applications in psychiatry. Biol Psychiatry. 1999;45(12):1553-1563.
- Rosenow F, Luders H. Presurgical evaluation of epilepsy. Brain. 2001;124(Pt 9):1683-1700.
- Rowland JA , Stapleton-Kotloski JR, Alberto GE, et al. Contrasting effects of posttraumatic stress disorder and mild traumatic brain injury on the whole-brain Resting-state network: A magnetoencephalography study. Brain Connect. 2017;7(1):45-57.
- Schmid E, Thomschewski A, Taylor A, et al; E-PILEPSY consortium. Diagnostic accuracy of functional magnetic resonance imaging, Wada test, magnetoencephalography, and functional transcranial Doppler sonography for memory and language outcome after epilepsy surgery: A systematic review. Epilepsia. 2018;59(12):2305-2317.
- Siekmeier PJ, Stufflebeam SM. Patterns of spontaneous magnetoencephalographic activity in patients with schizophrenia. J Clin Neurophysiol. 2010;27(3):179-190.
- Singer RJ, Ogilvy CS, Rordorf G. Unruptured intracranial aneurysms. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed January 2023.
- Smirniotopoulos JG, Wippold FJ II, Cornelius RS, et al; Expert Panel on Neurologic Imaging. ACR Appropriateness Criteria seizures and epilepsy. [online publication]. Reston, VA: American College of Radiology (ACR); 2011.
- Sobel DF, Aung M, Otsubo H, et al. Magnetoencephalography in children with Landau-Kleffner syndrome and acquired epileptic aphasia. Am J Neuroradiol. 2000;21(2):301-307.
- Sharma P, Seeck M, Beniczky S. Accuracy of interictal and ictal electric and magnetic source imaging: A systematic review and meta-analysis. Front Neurol. 2019;10:1250.
- Stam CJ. Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders. J Neurol Sci. 2010;289(1-2):128-134.
- Stefan H, Hummel C, Scheler G, et al. Magnetic brain source imaging of focal epileptic activity: A synopsis of 455 cases. Brain. 2003;126(Pt 11):2396-2405.
- Sutherling WW, Mamelak AN, Thyerlei D, et al. Influence of magnetic source imaging for planning intracranial EEG in epilepsy. Neurology. 2008;71(13):990-996.
- Tamilia E, AlHilani M, Tanaka N, et al. Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy. Clin Neurophysiol. 2019;130(4):491-504.
- Tedesco Triccas L, Meyer S, Mantini D, et al. A systematic review investigating the relationship of electroencephalography and magnetoencephalography measurements with sensorimotor upper limb impairments after stroke. J Neurosci Methods. 2019;311:318-330.
- van Straaten EC, de Waal H, Lansbergen MM, et al. Magnetoencephalography for the detection of intervention effects of a specific nutrient combination in patients with mild Alzheimer's disease: Results from an exploratory double-blind, randomized, controlled study. Front Neurol. 2016;7:161.
- Wang Y, Feng Y, Jia Y, et al. Auditory M50 and M100 sensory gating deficits in bipolar disorder: A MEG study. J Affect Disord. 2014a;152-154:131-138.
- Wang Y, Jia Y, Feng Y, et al. Overlapping auditory M100 and M200 abnormalities in schizophrenia and bipolar disorder: A MEG study. Schizophr Res. 2014b;160(1-3):201-207.
- Wirrell E, Whiting S, Farrell K. Management of intractable epilepsy in infancy and childhood. Adv Neurol. 2006;97:463-491.
- Xiang J, deGrauw X, Korostenskaja M, et al. Altered cortical activation in adolescents with acute migraine: A magnetoencephalography study. J Pain. 2013;14(12):1553-1563.
- Yang TT, et al. Noninvasive somatosensory homunculus mapping in humans by using a large-array biomagnetometer. Proc Natl Acad Sci. 1993;90:3098-3102.
- Zappasodi F, Tecchio F, Pizzella V, et al. Detection of fetal auditory evoked responses by means of magnetoencephalography. Brain Res. 2001;917(2):167-173.
- Zebhauser PT, Hohn VD, Ploner M. Resting-state electroencephalography and magnetoencephalography as biomarkers of chronic pain: A systematic review. Pain. 2022 Nov 28. [Online ahead of print].