Medical Policies - Medicine
Topographic Brain Mapping (Quantitative Electroencephalography)
*CAREFULLY CHECK STATE REGULATIONS AND/OR THE MEMBER CONTRACT*
NOTE 1: Refer to policy MED205.040 for Quantitative Electroencephalography as a Diagnostic Aid for Attention- Deficit / Hyperactivity Disorder (ADHD).
Topographic brain mapping (TBM), brain electrical activity mapping (BEAM), and quantitative electroencephalogram (QEEG), may be considered medically necessary when used as an adjunct to traditional electroencephalogram (EEG) when ANY of the following criteria is met:
• Evaluation of epilepsy when ANY of the following criteria is met:
1. The surface or long-term EEG is inconclusive and additional testing for possible epileptic spikes or seizures is needed; or
2. Ambulatory recording is needed to facilitate subsequent visual EEG interpretation; or
3. There is need for topographic voltage and dipole analysis in pre-surgical candidates with intractable epilepsy; OR
• Continuous monitoring in the operating room for the early detection of an acute intracranial complication during cerebrovascular surgery (i.e., intracranial, carotid endarterectomy); OR
• Monitoring for the detection of nonconvulsive seizures in high risk patients in the intensive care unit and operating room; OR
• Evaluation of cerebral vascular disease (CVD), dementia and encephalopathy when ANY of the following criteria is met:
1. Conventional testing has been completed without conclusive results; or
2. The patient is not a candidate for radiologic testing (e.g. computed tomography [CT], magnetic resonance imaging [MRI], cerebral angiography).
NOTE 2: It is recommended that TBM / QEEG be administered and reviewed by physicians highly skilled in clinical TBM interpretation.
Topographic brain mapping (TBM), brain electrical activity mapping (BEAM), and quantitative electroencephalogram (QEEG) are considered experimental, investigational and/or unproven for all other indications* including but not limited to:
• Drug abuse;
• Hypoxic ischemic encephalopathy;
• Learning disability;
• Post-concussion syndrome;
• Predicting response to psychotropic medication;
*NOTE 3: State Legislation may apply. Carefully check for legislative mandates that may apply for each plan.
Topographic Brain Mapping (TBM), also known as brain electrical activity mapping (BEAM), and quantitative electroencephalogram (QEEG) is a visual enhancement of a traditional surface electroencephalogram (EEG). EEG patterns are typically categorized into 4 frequency ranges, delta (<4 Hz), theta (4-7 Hz), alpha (8-12 Hz), and beta (13-25 Hz). The brain mapping process transforms the surface EEG data into a pictorial mapping (i.e., topographic image) of the seizure activity. Enhanced images are then placed on a schematic map of the brain, and the activity data is algorithmically analyzed by the size of the activity spike, the frequency of the discharges and the locality of the spikes. The algorithmic data are then compared to a database of normal patient brainwave activity to determine specific seizure types, focal location of seizure activity, or possible underlying medical conditions. (1)
In 2011, the U.S. Food and Drug Administration (FDA) approved a de novo 510(k) classification (class II, special controls, product code: NCG) for the generic device Neuropsychiatric Interpretive Electroencephalograph Assessment Aid. Per the FDA documentation, a neuropsychiatric interpretive electroencephalograph assessment aid is a device prescribed by a physician that uses a patient’s EEG to provide an interpretation of the patient’s neuropsychiatric condition. In addition to the general controls, approval of these devices is subject to a number of special controls, including the following (2):
• Clinical performance testing must demonstrate the accuracy, precision, and reproducibility of the EEG-based interpretation, including any specified equivocal ones (cutoffs).
• Clinical performance testing must demonstrate the ability of the device to function as an assessment aid for the medical condition for which the device is indicated. Performance measures must demonstrate device performance characteristics per the intended use in the intended use environment. Performance measurements must include sensitivity, specificity, positive predictive value and negative predictive value per the device intended use. Repeatability of measurement must be demonstrated using interclass correlation coefficients and illustrated by qualitative scatter plots.
• The device design must include safeguards to prevent use of the device as a stand-alone diagnostic.
• The labeling must bear all information required for the safe and effective use of the device.
This policy was originally created in 2002 and has been updated regularly with searches of the MEDLINE database. Most recently, the literature was searched through April 31, 2017. Topographic brain mapping is being evaluated in a multitude of medical and psychological conditions. Following is a summary of the key literature to date.
Evidence for the use of topographic brain mapping in the evaluation of patients with alcoholism is insufficient to form conclusions about the impact on health outcomes. There are no randomized controlled trials (RCTS) to support the use of topographic brain mapping in patients with alcoholism. Comparative studies have been completed but they have small sample sizes.
Additional adequately powered RCTs with sufficiently large sample sizes are needed.
In 2016, Arns et al. (3) completed the international Study to Predict Optimized Treatment in Depression (iSPOT-D) study in order to determine whether EEG occipital alpha and frontal alpha asymmetry (FAA) distinguishes patients with major depression disorder (MDD) from controls, predicts antidepressant treatment outcome. In this multi-center, randomized, prospective open-label trial, 1008 MDD participants were randomized to escitalopram, sertraline or venlafaxine-extended release. The study also recruited 336 healthy controls. Treatment response was established after eight weeks and resting EEG was measured at baseline (two minutes’ eyes open and eyes closed). No differences in EEG alpha for occipital and frontal cortex, or for FAA, were found in MDD participants compared to controls. Alpha in the occipital and frontal cortex was not associated with treatment outcome. However, a gender and drug-class interaction effect was found for FAA. Relatively greater right frontal alpha (less cortical activity) in women only was associated with a favorable response to the Selective Serotonin Reuptake Inhibitors escitalopram and sertraline. No such effect was found for venlafaxine-extended release. The study noted
FAA does not differentiate between MDD and controls, but is associated with antidepressant treatment response and remission in a gender and drug-class specific manner. Future studies investigating EEG alpha measures in depression should a-priori stratify by gender.
Some research studies have shown a reproducible difference between groups of patients and normal subjects (e.g. increased frontal alpha in depression). Although progress is being made, these scientific observations are not necessarily directly relevant for clinical diagnosis in individual care situations. (1)
In 2006, Venneman et al. (4) examined pretreatment neurophysiological factors to identify participants at greatest risk during cocaine-dependent treatment. Twenty-five participants were divided into concordant and discordant groups following electroencephalogram (EEG) measures recorded prior to a double-blind, placebo-controlled treatment trial. Three possible outcomes were examined: successful completion, dropout, and removal. Concordant (high perfusion correlate) participants had an 85% rate of successful completion, while discordant participants had a 15% rate of successful completion. Twenty-five percent of dropouts and 50% of participants removed were discordant (low perfusion correlate), while only 25% of those who completed were discordant. Failure to complete the trial was not explained by depression, craving, benzoylecgonine levels or quantitative electroencephalogram (QEEG) power; thus, cordance may help identify attrition risk.
Evidence for the use of topographic brain mapping in patients with drug abuse includes multiple RCTS with small sample sizes. Additional adequately powered RCTs with sufficiently large sample sizes are needed to determine the impact on health outcomes.
Hypoxic Ischemic Encephalopathy
In 2010, Hathi et al. (5) accessed an EEG-based index and Cerebral Health Index in babies (CHI/b), for identification of neonates with high Sarnat scores and abnormal EEG as markers of hypoxic ischemic encephalopathy (HIE) after perinatal asphyxia. This retrospective study used 30 min of EEG data collected from 20 term neonates with HIE and 20 neurologically normal neonates. The HIE diagnosis was made on clinical grounds based on history and examination findings. The maximum-modified clinical Sarnat score was used to grade HIE severity within 72 hours of life. All neonates underwent 2 channel bedside EEG monitoring. A trained electroencephalographer blinded to clinical data visually classified each EEG as normal, mild or severely abnormal. The CHI/b was trained using data from Channel 1 and tested on Channel 2. The CHI/b distinguished among HIE and controls (P<0.02) and among the three visually interpreted EEG categories (P<0.0002). It indicated a sensitivity of 82.4% and specificity of 100% in detecting high grades of neonatal encephalopathy (Sarnat 2 and 3), with an area under the receiver operator characteristic (ROC) curve of 0.912. CHI/b also identified differences between normal verses mildly abnormal (P<0.005), mild verses severely abnormal (P<0.01) and normal verses severe (P<0.002) EEG groups. An ROC curve analysis showed that the optimal ability of CHI/b to discriminate poor outcome was 89.7% (sensitivity: 87.5%; specificity: 82.4%). The study concluded that the CHI/b identified neonates with high Sarnat scores and abnormal EEG. These results support its potential as an objective indicator of neurological injury in infants with HIE.
Neurophysiologic studies of children with learning disorders have shown that poor spellers, children with dyslexia, or hyperactive children have different neurophysiologic responses from those in groups of normal children. Relationships between a patient's EEG patterns and outcome of therapy have been proposed, but still await a controlled verification. This research has been useful for scientific understanding of physical and physiologic differences between children with these disorders and normal children, although the studies vary in the kinds of changes reported and there have been questions raised about reproducibility. Diagnostic tests, including EEG brain mapping, have not been proven useful in establishing the diagnosis or treatment plan for individual children. No independent blinded comparisons have been made with a clinical standard. Many studies do not use an appropriate spectrum of patients for whom the diagnostic tests would be applied in clinical practice. There is no evidence that outcome was changed by the diagnostic testing or by the treatment plans predicated on such testing. Thus, there is no evidence that patients are better off for having had these tests performed. (1)
Chabot et al. (6) conducted a literature review to determine the efficacy of using TBM in children and adolescent psychiatric disorders. Most of the studies focused on children and adolescents with attention or learning problems. The researchers found other possible uses of TBM in determining appropriate medication selection following treatment response, and delineating the underlying cause of specific psychiatric disorders; however, most of this data was obtained from specialized research documents. The authors also concluded that TBM may prove to be a valuable imaging technique that could be used in children with attention and learning problems. They suggested that TBM may be beneficial in differentiating between Attention Deficit Disorder (ADD) and Attention Deficit Hyperactivity Disorder (ADHD) and Learning Disorder (LD), and may be useful in optimizing pharmacological treatment, remediation, or psychological interventions. The overall body of scientific evidence however, is of insufficient quantity and quality to support the use of TBM for these indications.
Several published studies have addressed EEG brain mapping and other QEEG analysis techniques in patients with head injury. Some reports are uncontrolled, unblinded, or retrospective observations, which are difficult to use for assessing clinical utility. Patients with extensive traumatic lesions, obvious on neuroimaging studies, had EEG and QEEG abnormalities. In the one small group of patients with post-concussion syndrome, an increase in 8 to 10 Hz alpha was reported. (7) A subsequent report described reduced alpha in a much larger group of patients after mild head injury. In the latter study, mild head-injury patients were separated from controls using a bayesian statistical discriminant formula weighted toward measurements of coherence and phase relationships as well as posterior alpha and frontotemporal beta activity. The authors replicated their findings with good sensitivity and specificity. Some individuals commented that this technique is predisposed to false-positive “abnormalities" in normal subjects due to mild drowsiness or other problems. Further independent long term studies would be beneficial to determine the effect on health outcomes. (1)
Predicting Response to Psychotropic Medication
In 2005, Crumbley and Associates (8) examined the use of QEEG in predicting response to psychotropic medications. The clinical outcomes of two groups of patients were compared to those with prescribed medication regimens that were concordant with the QEEG predictors, and those whose medication regimens were discordant with the QEEG predictors. Participants included 70 inpatient adolescents who were administered QEEG upon admission. The results indicated no significant difference in clinical outcome between the two groups. The failure of this study to find significant differences in patient outcomes questions the efficacy of QEEG.
In 2014, Fuggetta et al. (9) aimed to evaluate QEEG measures of power spectra as potential biomarkers of the predisposition towards the development of psychosis in schizotypal individuals. The resting-state oscillatory brain dynamics under eyes-closed condition from 16 low schizotypy (LoS) and 16 high schizotypy (HiS) individuals were analyzed for QEEG measures of background rhythm frequency (relative power in δ, θ, low-α, high-α, low-β, high-β and low-γ frequency bands) and the high-temporal cross-correlation of power spectra between low- and high-frequency bands observed by averaging signals from whole-head EEG electrodes. HiS individuals at rest locked the thalamocortical loop in the low-α band at a lower-frequency oscillation and displayed an abnormally high level of neural synchronization. In addition, the high-α band was found to be positively correlated with both the high-β and low-γ bands unlike LoS individuals, indicating widespread thalamocortical resonance in HiS individuals. The increase of regional alpha oscillations in HiS individuals suggests abnormal high-level attention, whereas the pattern of correlation between frequency bands resembles the thalamocortical dysrhythmia phenomenon which underlies the symptomatology of a variety of neuropsychiatric disorders including schizophrenia. These qEEG biomarkers may aid clinicians in identifying HiS individuals with a high-risk of developing psychosis.
In 2015, Kim et al. (10) evaluated the QEEG characteristics of patients with un-medicated schizophrenia (SPR) and to investigate the diagnostic utility of QEEG in assessing such patients during resting conditions. The subjects included 90 patients with schizophrenia and 90 normal controls. Spectral analysis was performed on the absolute power of all the electrodes across 5 frequency bands following artifact removal. The authors conducted a repeated-measures analysis of variance (ANOVA) to examine group differences within the 5 frequency bands across several brain regions and receiver operator characteristic analyses to examine the discrimination ability of each frequency band. Compared with controls, patients with schizophrenia showed increased delta and theta activity and decreased alpha 2 activity, particularly in the frontocentral area. There were no significant differences in the alpha 1 and beta activity. The receiver operator characteristic analysis performed on the delta frequency band generated the best result, with an overall classification accuracy of 62.2%. The results of this study confirmed the characteristics of the QEEG power in un-medicated schizophrenia patients compared with normal controls. These findings suggest that a resting EEG test can be a supportive tool for evaluating patients with schizophrenia.
To date, the evidence is insufficient to draw conclusions about the impact on health outcomes for the use of QEEG for individuals diagnosed with schizophrenia.
In 2007, Ashton et al. (11) studied high frequency localized "hot spots" in temporal lobes of patients with intractable tinnitus. Tinnitus, which is the perception of noise in the absence of an external auditory stimulus, is associated with several conditions. Brain imaging studies indicate increased neuronal excitability and decreased density of benzodiazepine receptors in temporal (auditory) cortex but the source and mechanism of such changes are unknown. Various EEG abnormalities involving temporal lobe and other brain areas have been described but recordings have been limited to standard EEG wave bands up to frequencies of 22Hz. This clinical study of otherwise healthy patients with intractable unilateral tinnitus, using QEEG, identified discrete localized unilateral foci of high frequency activity in the gamma range (>40-80Hz) over the auditory cortex in eight patients experiencing tinnitus during recording. These high frequency "hot spots" were not present in 25 subjects without tinnitus. The results suggest that further EEG investigations should include recordings in the gamma frequency range since such high frequency oscillations are believed to be necessary for perception. Identification of "hot spots" in tinnitus patients would provide a means for monitoring the effects of new treatments. These findings may also provide a model for exploration of more complex phenomena such as verbal and musical hallucinations.
In 2012, ECRI published a Health Technology assessment on QEEG for Mapping Nonpsychiatric (12) and Psychiatric Conditions. (13) Studies were examined that included patients with various medical and psychiatric conditions including but not limited to, cerebrovascular conditions, hypoxic ischemic encephalopathy, ischemic stroke, subarachnoid hemorrhage, patients with substance abuse, depression and schizophrenia. Most studies indicate there may be a future benefit to QEEG testing in patients with neurovascular conditions but recommended additional studies with larger samples.
In 2017, UpToDate (14) researched available literature regarding hypoxic-ischemic brain injury. The summary specified:
• “The clinical value of the electroencephalogram (EEG) is unclear in the assessment of prognosis of anoxic brain injury because investigators have used different classification systems and variable intervals of recordings after resuscitation. Furthermore, the EEG is susceptible to subjective interpretation, the effects of sedative drugs, metabolic disturbances, and sepsis, which can invalidate the results.”
• “Limited evidence suggests that treating subclinical seizures detected on continuous EEG monitoring does not improve outcome in patients with hypoxic-ischemic encephalopathy”.
Practice Guidelines and Position Statements
American Academy of Neurology (AAN)
In 1997, AAN created clinical guidelines (1) for digital EEG, QEEG and brain mapping which were reaffirmed in 2009 and supported by the American Clinical Neurophysiology Society (ACNS). Following is the Key literature to date.
Certain QEEG techniques are considered established as an addition to digital EEG to include:
1. Epilepsy: For screening for possible epileptic spikes or seizures in long-term EEG monitoring or ambulatory recording to facilitate subsequent expert visual EEG interpretation. (Class I and II evidence, Type A recommendation)
2. Operating room (OR) and intensive care unit and (ICU) monitoring: For continuous EEG monitoring by frequency-trending to detect early, acute intracranial complications in the OR or ICU, and for screening for possible epileptic seizures in high-risk ICU patients. (Class II evidence, Type B recommendation)
Certain QEEG techniques are considered possibly useful practice options as an addition to digital EEG in:
1. Epilepsy: For topographic voltage and dipole analysis in presurgical evaluations. (Class II evidence, Type B recommendation). The application of brain mapping is discussed in numerous textbooks and incorporated in several practice parameters in relation to the diagnosis of patients with epilepsy, the quantitative monitoring of patients during cranial surgery, or when monitoring high-risk patients in an ICU. TBM is a useful adjunct to a surface electroencephalogram (EEG) and provides additional detail that can confirm the diagnosis of seizure-like activity, when performed and analyzed by a specially trained diagnostician.
2. Cerebrovascular Disease: Based on Class II and III evidence, QEEG in expert hands may possibly be useful in evaluating certain patients with symptoms of cerebrovascular disease whose neuroimaging and routine EEG studies are not conclusive. (Type B recommendation)
3. Dementia: Routine EEG has long been an established test used in evaluations of dementia and encephalopathy when the diagnosis remains unresolved after initial clinical evaluation. In occasional clinical evaluations, QEEG frequency analysis may be a useful adjunct to interpretation of the routine EEG when used in expert hands. (Class II and III evidence as a possibly useful test, Type B recommendation)
QEEG may possibly be useful in the evaluation of select patients with cerebrovascular disease (CVD), dementia and/or encephalopathy. For most patients, computerized axial tomography (CT) and magnetic resonance imaging (MRI) remains the test of choice for patients with CVD. QEEG has no clear medical indication in the evaluation of patients with CVD when a MRI, CT, and/or routine EEG are available. Patients that may benefit from QEEG include individuals where an EEG is not available in their community, patients who are too ill to travel to a neuroimaging location, and patients whom the neuroimaging tests are nonlocalizing, but substantial clinical suspicion of focal cerebral dysfunction remains. QEEG may possibly be useful in evaluating patients with symptoms of CVD whose neuroimaging and routine EEG studies are not conclusive (Type B recommendation).
Based on current clinical literature, opinions of most experts, and proposed rationales for their use, QEEG remains investigational for clinical use in post-concussion syndrome, mild or moderate head injury, learning disability, attention disorders, schizophrenia, depression, alcoholism, and drug abuse. (Class II and III evidence, Type D recommendation)
Due to the substantial risk of erroneous interpretations, it is unacceptable for any EEG brain mapping or other QEEG techniques to be used clinically by those who are not physicians highly skilled in clinical EEG interpretation. (Strong Class III evidence, Type E recommendation). QEEG should be used only as an adjunct to and in conjunction with traditional EEG interpretation. These tests may be clinically useful only for patients who have been well selected based on their clinical presentation.
QEEG remains investigational for clinical use in post-concussion syndrome, mild-to-moderate head injury, learning disability, attention disorders, schizophrenia, depression, alcoholism, and drug abuse. Clinical studies have demonstrated distinctive forms of brain electrical activity in psychiatric conditions including but not limited to schizophrenia, major depression, and obsessive-compulsive disorder (OCD). However, the clinical significance of these distinctive patterns of brain wave activity is unknown. Thus, the role of QEEG in diagnosis, evaluation of disease progression, and treatment of these conditions has yet to be elucidated.
Summary Of Evidence
There is insufficient evidence in the published, peer reviewed, scientific literature to support the use of Topographic Brain Mapping (TBM) for the following indications: alcoholism, depression, drug/substance abuse, mild or moderate head injury, learning disability, and schizophrenia. TBM is not supported by the AAN guidelines for these conditions.
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Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy. They may not be all-inclusive.
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The following codes may be applicable to this Medical policy and may not be all inclusive.
95812, 95813, 95816, 95819, 95955, 95957, 95961, 95962
ICD-9 Diagnosis Codes
Refer to the ICD-9-CM manual
ICD-9 Procedure Codes
Refer to the ICD-9-CM manual
ICD-10 Diagnosis Codes
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ICD-10 Procedure Codes
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The Centers for Medicare and Medicaid Services (CMS) does not have a national Medicare coverage position. Coverage may be subject to local carrier discretion.
A national coverage position for Medicare may have been developed since this medical policy document was written. See Medicare's National Coverage at <http://www.cms.hhs.gov>.
1. American Academy of Neurology (AAN). Assessment of Digital EEG, Quantitative EEG and EEG Brain Mapping. (July 1997, reaffirmed 2009): 5, 9: Available at <http://www.acns.org> (accessed May 3, 2017).
2. FDA – Neuropsychiatric interpretive electroencephalograph assessment aid. Center for Devices and Radiologic Health (2011, revised April 1, 2016). Available at <http://www.fda.gov> (accessed May 31, 2017).
3. Arns M, Bruder G, Hegerl U, et al. EEG alpha asymmetry as a gender-specific predictor of outcome to acute treatment with different antidepressant medications in the randomized iSPOT-D study. Clin Neurophysiol. (2016 Jan); 127(1):509-19. PMID 26189209
4. Venneman S, Leuchter A, Bartzokis G, et al. Variation in neurophysiological function and evidence of quantitative electroencephalogram discordance: predicting cocaine-dependent treatment attrition. J Neuropsychiatry Clin Neurosci. (2006 Spring); 18(2):208-16. PMID 16720798
5. Hathi M, Sherman DL, Inder T, et al. Quantitative EEG in babies at risk for hypoxic ischemic encephalopathy after perinatal asphyxia. Journal ofPerinatology. (2010); 30(2):122-126. PMID 19741652
6. Chabot RJ, Michele F, et al. The Role of Quantitative Electroencephalography in Child and Adolescent Psychiatric Disorders. Child and Adolescent Psychiatric Clinics of North America. (2005 Jan); 14(1):21-53. PMID 15564051
7. Tebano MT, Cameroni M, Gallozzi G, et al. EEG spectral analysis after minor head injury in man. Electroencephalography and Clinical Neurophysiology. (1988); 70:185-189.
8. Crumbley JA. et al. The Neurometric-Quantitative Electroencephalogram as a Predictor for Psychopharmacological Treatment: An Investigation of Clinical Utility. Journal of Experimental Neuropsychology (2005) 27(6): 769-778. PMID 16019652
9. Fuggetta G, Bennett MA, Duke PA, et al. Quantitative electroencephalography as a biomarker for proneness toward developing psychosis. Schizophrenia Research. (2014 Mar); 153(1-3):68-77. PMID 24508484
10. Kim JW, Lee YS, Han DH, et al. Diagnostic utility of quantitative EEG in un-medicated schizophrenia. Neuroscience Letters. (2015 Mar 4); 589:126-31. PMID 25595562
11. Ashton, H, et al. High Frequency Localised “Hot Spots” in Temporal Lobes of Patients with Intractable Tinnitus: A Quantitative Electroencephalographic (QEEG) Study, University of Newcastle, United Kingdom. (2007 Oct 9):426(1):23-8. Available at <http://www.nih.gov> (accessed May 3, 2017). PMID 17888572
12. Quantitative Electroencephalography for Mapping Nonpsychiatric Conditions. Health Technology Assessment Information Service (2012 July):1-12. Available at <http://www.ecri.org> (accessed May 31, 2017).
13. Quantitative Electroencephalography for Mapping Psychiatric Conditions. Health Technology Assessment Information Service (2012 July):1-10. Available at <http://www.ecri.org>. (accessed May 31, 2017).
14. Weinhouse GB, Young GL. Hypoxic-ischemic brain injury: Evaluation and prognosis. In: UpToDate Post TW (Ed), UpToDate, Waltham, MA. Topic last updated: May 2017. Available at <http://www.uptodate.com> (accessed on June 20, 2017).
15. Topographic Brain Mapping - Archived. Chicago, Illinois: Blue Cross Blue Shield Association Medical Policy Reference Manual (1995 December) Medicine: 2.01.10.
|7/15/2018||Reviewed. No changes.|
|8/15/2017||Document updated with literature review. The following change was made to Coverage: Added hypoxic ischemic encephalopathy to the list of experimental, investigational and/or unproven indications.|
|3/1/2016||Reviewed. No changes.|
|8/1/2015||Document updated with literature review. The following was added to Coverage: 1) Evaluation of cerebral vascular disease (CVD), dementia and encephalopathy is considered medically necessary when any of the following criteria is met: a) Conventional testing has been completed without conclusive results; or b) The patient is not a candidate for radiologic testing (e.g. CT, MRI, cerebral angiography). The following was changed in Coverage: The diagnosis of epilepsy is no longer required for: 1) continuous monitoring in the operating room for the early detection of an acute intracranial complication during cerebrovascular surgery (i.e., intracranial, carotid endarterectomy); or 2) monitoring for the detection of nonconvulsive seizures in high risk patients in the intensive care unit and operating room attention. In addition, attention disorder was moved to a new medical policy (MED 205.040). The title changed from Topographic Brain Mapping.|
|4/15/2014||Literature reviewed. Coverage unchanged.|
|12/1/2013||Policy revised with literature review; ICD codes updated. Coverage unchanged.|
|5/15/2008||Policy revised without literature review; new review date only.|
|12/5/2006||Revised/updated entire document|
|7/1/2004||Revised/updated entire document|
|5/1/1996||Revised/updated entire document|
|7/1/1994||Revised/updated entire document|
|4/1/1994||Revised/updated entire document|
|5/1/1990||New medical document|
|Title:||Effective Date:||End Date:|
|Topographic Brain Mapping (Quantitative Electroencephalography)||08-15-2017||07-14-2018|
|Topographic Brain Mapping (Quantitative Electroencephalography)||03-01-2016||08-14-2017|
|Topographic Brain Mapping (Quantitative Electroencephalography)||08-01-2015||02-29-2016|
|Topographic Brain Mapping (TBM)||04-15-2014||07-31-2015|
|Topographic Brain Mapping (TBM)||12-01-2013||04-14-2014|
|Topographic Brain Mapping||05-15-2008||11-30-2013|
|Topographic Brain Mapping||12-15-2006||05-14-2008|
|Topographic Brain Mapping||07-01-2004||12-14-2006|
|Topographic Brain Mapping||05-01-1996||06-30-2004|