5

Techniques for Neurological Disorders

The nervous system consists of the central nervous system (CNS), comprising the brain and spinal cord and the peripheral nervous system (PNS), encompassing nerves extending from the spinal cord to all parts of the body. The autonomic nervous system (ANS) is part of the peripheral nervous system and is a collection of neurons that influences many different organs, such as the lungs, heart and stomach, and controls body functions not consciously directed, such as breathing, heart rate, and digestion.

Clinicians form a diagnosis on the basis of the patient’s medical history and a physical exam, together with appropriate testing. A complete neurologic exam commonly includes testing of the cranial nerves (hearing, vision, motor and sensory function of the face and mouth, smell, eye movement, etc.), motor functions, sensory functioning, deep tendon reflexes, coordination, gait, balance, and cognition. Neurologic diagnoses often require additional tests, such as serum (blood) or urine tests, cerebrospinal fluid analyses, and imaging or electrodiagnoses to either confirm or eliminate possible diagnoses. For example, imaging techniques and electrodiagnostic techniques, such as electroencephalogram (EEG) and evoked potentials, are commonly used in the diagnosis of CNS disorders. The most common PNS electrodiagnostic techniques are electromyography and nerve conduction studies. The diagnosis of ANS disorders may include physiological testing such as orthostatic blood pressure and pulse and tilt table testing, along with specialized autonomic tests done at only a few medical centers. Examples of autonomic tests include the sweat test, Valsalva ratio, skin surface temperature, and the quantitative sudomotor axon reflex test; these

tests are sometimes used to diagnose autonomic conditions but are rarely used to assess limitations in functioning.

Many different medical conditions can affect the nervous system, including blood vessel disorders in the brain (e.g., arteriovenous malformations), stroke, tumors, degenerative diseases, (e.g., Alzheimer’s disease), pituitary gland disorders, epilepsy, headaches (including migraines), concussions and brain injuries, movement disorders (e.g., Parkinson disease), demyelinating diseases (e.g., multiple sclerosis), systemic diseases, neuro-ophthalmologic diseases, neuropathy, mental disorders (e.g., schizophrenia), spine disorders, and infections such as meningitis. Evaluating and diagnosing damage to the nervous system is complex, as different disorders have many of the same symptoms in common.

Over the past 10 years many advances in technologies have allowed improved assessment of the nervous system. These improvements include advances in magnetic resonance imaging (MRI) technology, specifically functional MRI (fMRI) and high-resolution imaging, which provide an improved ability to identify pathologies of the central nervous system. New digital sensors and wearable technology collect real-time diagnostic data to aid in the diagnosis of, for example, neurodegenerative diseases (Granziera et al., 2022). In addition, whole-exome sequencing is increasingly being used in clinical diagnostics for a variety of diseases, including complex neurologic diagnoses (Retterer, et al., 2016).

The chapter provides information illustrating the various types of new and improved diagnostic and evaluative techniques in neurology that have become available since 1990. It focuses on techniques that are related to potentially disabling neurologic conditions and identifies emerging techniques with the potential to influence how patients are diagnosed with disabling neurologic conditions in the future.

OVERVIEW OF SELECTED TECHNIQUES

Box 5-1 shows the neurologic diagnostic and evaluative techniques described in this chapter. In selecting these techniques, the committee considered the criteria in Chapter 1 and the neurologic conditions in Social Security Administration Listings of Impairments. The chapter discusses the evidence and information about the selected techniques and responds to the requested items (a)–(j) of the Statement of Task for each technique. Following the descriptions of the selected techniques, the last section of the chapter outlines emerging techniques used in the assessment of individuals with neurological disorders.

SELECTED DIAGNOSTIC TECHNIQUES FOR NEUROLOGICAL DISORDERS

The section describes advances in diagnostic techniques for confirming or ruling out a neurologic disorder or potentially disabling impairment. MRI techniques are where most of the advancements have occurred.

Magnetic Resonance Imaging

As discussed in Chapter 3, magnetic resonance imaging, especially when combined with advanced techniques or other diagnostics, can show anatomical images of the brain or spinal cord, measure blood flow, or reveal deposits of minerals such as iron. According to the National Institute of Neurological Disorders and Stroke, “MRI is used to diagnose stroke, traumatic brain injury, brain and spinal cord tumors, inflammation, infection, vascular irregularities, brain damage associated with epilepsy, abnormally developed brain regions, and some neurodegenerative disorders. MRI is also used to diagnose and monitor disorders such as multiple sclerosis” (NINDS, 2022). Advances in MRI techniques and the combination of MRI technology with other diagnostic techniques represent a large percentage of the new diagnostic techniques developed over the past 30 years.

Because so many different MRI-based diagnostic tests exist—a large percentage of which have been developed over the past three decades—the committee chose to not attempt to uncover and list all of them. Instead, the committee has assembled representative examples of how various forms of MRI are being used in diagnostics today, including functional MRI, diffusion-weighted MRI (dwMRI), and others. Table 5-1 offers a (necessarily incomplete) list of the ways that magnetic resonance imaging of various types is currently being used in diagnosing neurological disorders.

MRI and Multiple Sclerosis

MRI is a crucial tool in the diagnosis of multiple sclerosis (MS). In a patient with suspected MS, a physician will typically start with a thorough medical history and examination and then move onto a lumbar puncture procedure, evoked potential test, or MRI (MS Trust, 2022: Palace, 2001; Tobin, 2022; Traboulsee and Li, 2006). In cases of relapsing–remitting MS, a positive MRI combined with a pattern of symptoms consistent with MS is generally enough for a diagnosis (Tobin, 2022). In particular, MRI scans of the brains of MS patients will show lesions which appear as white patches and are indicative of damage to the brain, particularly demyelination. MS attacks myelin, or the protective covering of nerve cells, ultimately damaging the nerve cell underneath and causing the symptoms of MS; an MRI scan is particularly sensitive to such demyelination, which makes it an especially valuable tool in diagnosing MS (NMSS, 2022).

The use of MRI in the diagnosis of MS is at this point a highly developed process. The first international guidelines were established in 2001 (McDonald et al., 2001), and they were updated in 2016 (Filippi et al., 2016). It is particularly valuable in diagnoses involving clinically isolated syndrome, that is, MS in a patient who has had only one demyelinating attack (NMSS, 2022).

The requested details in the statement of task related to the diagnosis of multiple sclerosis with MRI are as follows:

1. MRI is used, in conjunction with medical history and clinical exam, to diagnose MS, particularly in the case of clinically isolated syndrome.
2. By identifying lesions in the brain indicative of demyelination, an MRI image helps identify MS as the likely diagnosis among patients who present with a set of symptoms that could arise from MS or other brain disorders; before the use of MRI, physicians had to depend upon techniques that were less definite or more risky, such as a lumbar puncture. This improved ability is seen with

TABLE 5-1 Uses of Magnetic Resonance Imaging in Neurological Diagnoses

NOTE: FLAIR = fluid-attenuated inversion recovery; MR = magnetic resonance; MRI = magnetic resonance imaging.

SOURCES: Baggio and Junqué (2019); Baliyan et al. (2016); Bash and Tanenbaum (2021); Botz (2021); de Filippis et al. (2019); (Filippi et al., 2018); Gregory and Scahill (2018); Gur and Gur (2010); Halefoglu and Yousem (2018); Kates et al. (1996); Koch et al. (2012); Kulkarni et al. (2021); Long et al. (2020); Mustafa et al. (2021); Nahab and Hallett (2010); Öz et al. (2014); RadiologyInfo.org (2022); Shi et al. (2021); Soares et al. (2013); Steardo et al. (2020); Wu et al. (2015); Yang et al. (2019).

equally strong effect among different racial, ethnic, or gender subpopulations in the United States

3. MRI can indicate with great accuracy the presence of demyelination in the brain, which leads to decreased neuronal communication and a range of physical effects.
4. International guidelines for the use of MRI is diagnosing multiple sclerosis were released in 2001; the technique had been in use for many years before that.
5. MRIs are widely available in hospitals, medical centers, and clinics around the United States. Any disparities in access to the technique arise from disparities in access to medical care in general.
6. Previously used techniques could not identify the presence of demyelination in the brain as accurately as an MRI can, leading to potentially missed diagnoses.
7. MRI scans can scan a range of lesions from demyelination in the brain, ranging from none to many. A single lesion is difficult to interpret, but multiple lesions produce a diagnosis of MS. A greater number of lesions is typically associated with a more advanced degree of MS, as more networks in the brain are affected.
8. The test should be administered by a trained technologist and interpreted by a radiologist. The validity of the test results can be seriously affected if the appropriate personnel are not involved.
9. The technique is already widely used as a medical best-practice.
10. In rare cases of MS the MRI image is normal or is not definitive for MS; in such situations, other techniques, such as spinal fluid analysis, evoked potentials, or another type of imaging, can generally provide a conclusive diagnosis (Tobin, 2022).

Diffusion-Weighted MRI and Acute Ischemic Stroke

Diffusion-weighted MRI (dwMRI), also seen as DWI, is a form of MRI that makes it possible to distinguish among different types of tissue according to the amount of diffusion of water molecules taking place within the different tissues. Tissues that are highly cellular or have cellular swelling have lower diffusion coefficients than other tissues, so, for example, injured tissues will appear different from normal healthy tissues when examined with dwMRI (Feeney, 2022). Among the clinical applications of dwMRI are the early identification of ischemic stroke, the differentiation of acute stroke from chronic stroke and from other stroke mimics, the differentiation of herpes encephalitis from diffuse temporal gliomas, the assessment of the extent of diffuse axonal injury, the assessment of active demyelination, and the assessment of cortical lesions in Creutzfeldt-Jakob disease (Feeney, 2022). This technique is very sensitive at detecting and localizing

acute ischemic brain lesions. Because stroke is common and included in a differential diagnosis in many acute neurological events, dwMRI should be considered as part of the analysis (Schaefer et al., 2000).

The requested details related to the diagnosis of acute stroke with dwMRI are as follows:

1. Studies have shown the potential for dwMRI in early detection of ischemic stroke, discriminating brain tumors, and tracking of fibers, which helps to advance knowledge on the anatomy of the brain. It can also be used in the diagnosis of epilepsy and neurotoxicity (Chilla et al., 2015).
2. The technique is an advance, as the images and maps of the brain that can be created through DWI can show changes in the brain as soon as 30 minutes after the onset of stroke, compared with 8 hours for more conventional MRI techniques (Chilla et al., 2015). Pathological changes can be detected in early stages, when other forms of imaging may not show significant changes.
3. In ischemia, DWI demonstrates superiority in identifying the stroke onset area compared with conventional MRI. The addition of DWI can improve the accuracy of region identification in the first 48 hours. DWI can also be used in prognosis for patients who underwent a thrombectomy following an ischemic stroke. Using a DWI-based predictive algorithm, researchers found it was able to predict the risk of disability for 100 percent of patients with high predictive value (Raoult et al., 2020).
4. The technique of dwMRI was applied on the human brain for the first time in 1986 (Chilla et al., 2015).
5. MRI technology is widely available, but the expertise necessary for dwMRI is more limited, so disparities in access to the technique exist because some populations, depending on geographic and insurance status, will have easier access to the technique than others. Disparities in access specifically for stroke assessment and diagnosis have not been well studied.
6. Timeliness in diagnosis of ischemic stroke can be critical to providing the right treatment and optimizing outcomes, and the previous methods of conventional MRIs would require at least eight hours following onset to be able to see significant changes in brain tissue.
7. The technique allows the recognition of water displacement over distances of 1–20 um (Charles-Edwards and de Souza, 2006). The presence of lesions can also provide insight into potential outcomes, with the identification of more lesions associated with worse outcomes for patients following acute stroke. The presence of a DWI lesion has been associated with nearly six times the odds

for worse functional outcomes at three months following hospital discharge (Garg et al., 2020). Patients with a lesion were also less likely to recover between two weeks and three months.

8. The test must be ordered by clinicians familiar with ischemic stroke and dwMRI and administered by technologists trained in dwMRI; the results should be interpreted by a radiologist. The validity of the test results can be seriously affected if the appropriate personnel are not involved.
9. One of the key barriers to wider adoption of this technique is that the hardware upgrades needed for higher strength machines and improved image quality are expensive. Additionally, translating the advances into clinical use is still subject to patient safety, and additional research is needed on post-processing methods and contrast agents (Chilla et al., 2015).
10. There are limitations in the efficacy of this technique, as DWI images are of lower quality and result in worse resolution with additional noise and artifacts, so they cannot replace conventional MR sequences entirely (Chilla et al., 2015). DWI accuracy is also limited by power requirements and hardware limitations. However, with faster acquisition times and advances in technology, image resolution is improving, and the presence of artifacts has been decreasing.

Functional MRI

Functional MRI (fMRI) is a noninvasive diagnostic test that measures small changes in blood flow as a person performs tasks (e.g., speaking or moving) while in an MRI scanner. Its ability to track changes in blood flow and oxygen levels is used to measure neural activity in the brain. In this way fMRI can determine precisely which part of the brain is handling critical functions such as thought, speech, vision, movement and sensation, and because the technique can spot neural activity that deviates from normal parameters, it can be used to show the effects of stroke, trauma, Alzheimer’s disease, or other disorders on brain function. At this point it is being used by researchers to study a number of different neurological disorders, but its best uses in the clinical are still being determined (Levin, 2022).

Genetic Testing for Hereditary Disorders

Chapter 3 provides an overview molecular genetic testing for hereditary disorders. Currently, some form of genetic sequencing is used in the diagnosis of a wide array of neurological disorders, so the responses to the questions (a)–(j) will be for the genetic diagnosis of any neurological disorder rather than for a specific one. There are obviously differences in the specifics of the

use and effectiveness of genetic testing for different neurological disorders, but delving into those differences is beyond the scope of this report. So what follows are general answers to the questions which relate to neurological genetic testing in general:

1. The accepted use of genetic testing in neurology is to diagnose a wide variety of neurological disorders, particularly in cases where clinical examination and other diagnostic techniques cannot identify a disorder with certainty. These disorders include Duchenne muscular dystrophy, Charcot-Marie-Tooth disease, Huntington’s disease, spinocerebellar ataxias, Kennedy’s disease, Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and dopa-responsive dystonia, among many others (Fischbeck, 2014). Genetic testing is also used to guide treatment in various disorders, such as autism.
2. The technique represents an advancement in diagnostic ability by identifying the specific gene(s) responsibility for a patient’s disability, which can provide a definitive diagnosis and also help to guide treatment. This improved ability is seen with equally strong effect among different racial, ethnic, or gender sub-populations in the United States.
3. Genetic testing identifies the causes of specific impairments rather than the impairments themselves, although genetic testing can help predict the likely trajectory of specific impairments before they fully appear.
4. As a practical clinical tool, genetic sequencing has been available since the mid 2000s, when next-generation sequencing was developed and tools for it become commercially available.
5. There are disparities related to access due to cost. The technique remains somewhat expensive as a diagnostic tool and is not always paid for by insurance, so people who cannot afford to pay out of pocket will have limited access in some cases.
6. The major drawback or limitation of the previously used techniques is that they did not identify the specific gene responsible for a condition and that they could sometimes not conclusively identify the presence of a particular disorder.
7. The outcome of a genetic test is the identification of particular genetic variants in a patient’s genome that are related to or responsible for a particular condition. By identifying the particular variant responsible, the test points to the specific physiological pathway(s) involved in the disorder as well as potential treatments.
8. A clinical examination must precede and inform the ordering of genetic testing. In addition to a physician familiar with genetic

disorders, a team should include a geneticist, pathologist, and genetic counselor who works with the patient to help the patient understand the diagnosis and make informed decisions in response to it. Testing should be done in an accredited lab. The validity of the test results can be seriously affected if the appropriate personnel do not perform the genetic analysis.

9. The major impediments to the increasingly widespread use of the technique as a medical best practice are the costs of genetic testing, which are coming down, and the availability of personnel trained in administering and interpreting the tests.
10. Genetic testing does not provide information about the severity of physical deficits in functioning.

Positron Emission Tomography

Positron emission tomography (PET) is a particularly powerful way to peer into the brain and observe what is happening in real time. It is used to examine brain metabolism, alterations in regional blood flow, and receptor binding of various neurotransmitters. It can be used to diagnose such neurological disorders as multiple sclerosis, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and various dementias. The major reason it is not used in clinical diagnoses more widely is that at this point it is very expensive because it requires a cyclotron to create the beam of photons and radiochemicals for injection into the bloodstream systems (Politis and Piccini, 2012).

Uses in Diagnosing Alzheimer’s Disease

There has been increasing work in recent years in the early detection and diagnosis of Alzheimer’s disease. One of the most common approaches to this early diagnosis involves positron emission tomography (PET) to detect the hallmarks of the disease even before a definitive diagnosis can be made based on clinical observations (Bao et al., 2021; Hameed et al., 2020; Nordberg et al., 2010; Silverman, 2009). In particular, various radiotracers have been developed that attach to β-amyloid plaques, the misfolded proteins that appear in the brains of Alzheimer’s patients, or to neurofibrillary tangles, another well-known marker of the disease (Bao et al., 2021). PET used with these tracers makes it possible to detect the effects of Alzheimer’s disease in the brain at a point in the progression of the disease when the behavioral effects are still inconclusive (Fantoni et al., 2018).

At present, because of the expense of PET imaging, the technique has been employed mainly in research studies, but it has been used in some clinical settings. For example, at one Department of Veterans Affairs (VA)

medical center it has been applied to look for the presence of β-amyloid plaques among veterans with cognitive complaints and to determine among those with cognitive decline which had Alzheimer’s disease and which did not (Turk et al., 2022; Vives-Rodriguez et al., 2022).

The requested details related to the PET with tracers technique are as follows:

1. The accepted use of PET in the diagnosis of Alzheimer’s disease is to detect the presence of the disease’s biomarkers in the brain, particularly β-amyloid plaques and neurofibrillary tangles.
2. The main advance is the ability to detect the presence of these biomarkers of Alzheimer’s disease in the brains of patients even at an early stage of the disease. Another available technique looks for β-amyloid plaques in the cerebral spinal fluid, but that is more invasive. Preliminary indications are that this improved ability is seen with equally strong effect among different racial, ethnic, and gender sub-populations in the United States.
3. PET with biomarkers can differentiate Alzheimer’s disease from other disorders in patients with memory loss and dementia.
4. PET has been available for several decades. The first tracer for β-amyloid plaques was approved by the FDA on April 6, 2012 (FDA, 2012).
5. Because the test is expensive and insurance rarely pays for it, the treatment is currently available mainly to patients in the VA system, those in clinical trials, or those who can afford the out-of-pocket costs.
6. Previous techniques relied mainly on behavioral tests and could not always tell the difference between Alzheimer’s disease and other causes of memory loss and dementia.
7. The test detects the presence or absence of β-amyloid plaques in the brain, which are a strong—although not definitive—indication that the patient has Alzheimer’s disease.
8. The test must be administered by clinicians familiar with the use of radioactive tracers along with those trained on the use of PET scanners, and the results should be interpreted by a radiologist. The validity of the test results can be seriously affected if the appropriate personnel are not involved.
9. The main impediments to the increasingly widespread use of this technique as a medical best practice are mainly cost, the limited availability of PET scanners, and the availability of appropriately trained technicians.
10. The main limitation of the technique’s diagnostic or evaluative efficacy is the fact that β-amyloid plaques are not a definitive sign of

Alzheimer’s disease; however, when combined with behavioral tests aimed at detecting memory loss and dementia, the test is extremely accurate.

Single Photon Emission Computed Tomography

As discussed in Chapter 3, single photon emission computed tomography (SPECT) is an advanced nuclear imaging technique that can be used to evaluate certain brain functions as part of diagnosing neurologic and psychiatric conditions. In particular, SPECT makes it possible to directly measure various elements of neurochemical transmission in the body, allowing clinicians to assess and monitor the pathophysiology of complex brain disorders (Hussain et al., 2022; Yandrapalli and Puckett, 2022). For example, SPECT scans can be used to diagnose Alzheimer’s Disease or other neurodegenerative diseases, stroke, seizure disorders such as epilepsy, or evaluating memory loss (Cedar Sinai, 2023). The detailed three-dimensional map of blood flow in the brain created from the procedure can also allow for detection of altered blood flow and clogged blood vessels, helping to diagnose or evaluate vascular brain disorders (Mayo Clinic, 2023).

Among the various uses of SPECT is assisting in the diagnosis of Parkinson’s disease, described below.

SPECT with DaTscan^TM for Parkinsonian Syndrome

In 2011 the Food and Drug Administration (FDA) approved the use of a radiopharmaceutical, ioflupane i-123, also known as DaTscan^TM, for use in the diagnosis of multiple types of parkinsonian syndromes. For the diagnosis, DaTscan^TM is injected into the bloodstream, where is makes it way to the brain and attaches to the dopamine transporters located in dopaminergic neurons. This allows the SPECT imager—which is sensitive to the signals emitted by the radioactive tracer—to map the locations and numbers of the dopaminergic neurons in the brain. Since the effects of Parkinson’s disease are caused by damage to these particular neurons, the SPECT images created with the use of DaTscan^TM can reveal the presence and severity of the disease (APDA, 2022).

Although the DaTscan^TM test has been shown to be as accurate as a clinical exam in diagnosing Parkinson’s disease, in many cases it does not add any extra information from what a clinical exam will reveal. However, there are certain situations in which it can sharpen a diagnosis. Studies have indicated, for instance, that it can likely tell when a patient has drug-induced parkinsonism or vascular parkinsonism rather than Parkinson’s disease. The major use for the test—and, in particular, the FDA indication for the use of the test—is to distinguish between Parkinson’s disease and

essential tremor. Although it is often possible for clinicians to tell the difference between the two by paying attention to the details of a patient’s tremors, there are times when it is difficult to make a clear diagnosis with just a clinical exam; in such cases, the DaTscan^TM test can provide the necessary additional information (Roussakis et al., 2013).

The requested details related to the SPECT with DaTscan^TM diagnosis technique are as follows:

1. The accepted use is for the diagnosis of Parkinson’s disease, particularly in distinguishing it from essential tremor when a clinical exam cannot clearly tell the difference.
2. The technique’s main advance is in distinguishing between Parkinson’s disease and essential tremor when such a differentiation is not possible with a clinical exam; it may also make it possible to distinguish induced parkinsonism or vascular parkinsonism from Parkinson’s disease. There are no data concerning whether this improved ability is seen with equally strong effect among different racial, ethnic, or gender subpopulations in the United States, but its mode of action indicates that the value should be equally strong among different populations.
3. Parkinson’s disease is more accurately assessed with this technique in certain cases, mainly when a clinical diagnosis does not clearly distinguish between Parkinson’s disease and essential tremor; the technique may also make it possible to distinguish induced parkinsonism or vascular parkinsonism from Parkinson’s disease.
4. The FDA approved the technique in January 2011, and DaTscan^TM was made available to clinicians shortly thereafter. A generic version of DaTscan^TM was approved by the FDA and made commercially available in the United States in April 2022 (Curium, 2022).
5. There are no known disparities in current access to the technique among various sub-populations in the United States along racial, ethnic, socioeconomic, or geographic lines beyond the disparities that affect all health care in the United States. For example, the technique is more likely to be accessed by patients with health insurance and those who live in cities with larger hospitals.
6. Clinical exam—the basic method for diagnosing Parkinson’s disease—has a significant error rate, with clinicians sometimes diagnosing idiopathic Parkinson’s disease in patients with essential tremor, drug-induced parkinsonism, or other disorders and thus starting the patients on an incorrect treatment regimen (Roussakis et al., 2013).
7. The SPECT with DaTscan^TM test reveals the level of functioning dopaminergic neurons in a brain region, with the results ranging

from normal levels to severely reduced; a greater reduction in the level of these functioning neurons implies a greater impairment in muscular control.

8. The necessary personnel for the test include the clinician, a nuclear medicine technologist, a nuclear pharmacist, a medical physicist, and a radiation safety officer, all under the supervision of a board-certified nuclear radiologist. The test should be performed in a hospital equipped with a SPECT imager, the ability to handle radioactive material, and the necessary personnel available. The validity of the test results can be seriously affected if the appropriate personnel are not involved.
9. There are no impediments to the increasingly widespread use of the technique as a medical best-practice.
10. The test is not suitable for differentiating among disorders that cause a loss of dopaminergic nerve endings in the striatum, including idiopathic Parkinson’s disease, progressive supranuclear palsy, corticobasal ganglionic degeneration, and multiple system atrophy (APDA, 2022). Various other techniques exist to make such differentiations.

Digitalized Tools for the Diagnosis of Migraines

The diagnosis of migraines is a complicated process involving medical history, clinical examination, and, in some cases, diagnostic tests to rule out such potential causes as a tumor or abcess (NYU Langone, 2022). The diagnostic tests used may include computerized tomography (CT), MRI, sinus X-ray, lumbar puncture, or electroencephalogram (WebMD, 2020). Currently there are no definitive diagnostic tests for migraine, and modern diagnostic technologies such as CT or MRI are used only as aids in helping a clinician reach a diagnosis based on a holistic assessment of multiple factors.

There is, however, one technology that may have the potential to revolutionize migraine diagnosis—a new generation of computerized diagnostic tools based on various algorithms and machine learning approaches that offer an objective, accessible means of determining the presence or absence of migraine. According to a recent review of computerized migraine diagnostic tools (Woldeamanuel and Cowan, 2022), several dozen such tools now exist, most of them developed since 2006. A dozen of them are focused solely on the diagnosis of migraines—i.e., produce a yes/no answer to the question of whether a patient has a migraine—while the remainder diagnose migraines and other types of headaches as well.

Many of the tools are based on the International Classification of Headache Disorders, Third Edition (ICHD-3), and they generally rely on a

patient’s answers to a number of questions to make a diagnosis. The digital tests are sometimes administered by clinicians, but, importantly, a large number of them are intended to be self-administered. According to published research, some of these tools performed with high accuracy in diagnosing migraines compared to interview-based diagnosis (Woldeamanuel and Cowan, 2022). The tools do not—at least at present—outperform a clinician experienced in headaches and migraines, but given the large number of headache sufferers relative to the number of specialists familiar with migraines, these computerized diagnostic tools could play a number of important roles. For instance, because migraine is a chronic condition whose attacks can be triggered by various stimuli (loss of sleep, depression or anxiety, even skipped meals), the tools could help migraine sufferers monitor their condition and adjust their behavior accordingly. More generally, “computerized migraine diagnostic tools have the potential to provide efficient, patient-centered, and improved headache care by delivering early diagnosis and management, enhancing diagnostic accuracy, saving time, boosting accessibility, enabling remote care with reduced costs, and decreasing travel to hospital/clinic care setting thereby reducing the exposure to communicable diseases in healthcare settings” (Woldeamanuel and Cowan, 2022).

The requested details related to the use of digitalized diagnostic tools for migraine are as follows:

1. The accepted uses are for the diagnosis of migraine and, depending on the tool, other types of headaches as well.
2. The technique represents an advance in that it makes diagnosis more easily available to patients, without direct interaction with a clinician. Improved access is important given the scarcity in the number of headache specialists. Cohen (2022) estimates only 1 headache specialist per 60,000 people suffering from migraines, which is a barrier for people hoping to get evaluated (Cowan et al., 2022).
3. Migraines are not assessed more accurately with digital tools than by a clinician using state-of-the-art diagnostic approaches, but the digital tools are more consistent and may provide more accurate diagnoses than clinicians who are unfamiliar with headaches and migraines. A systematic review found a high level of agreement between a self-administered computer based diagnostic engine and a semi-structured interview conducted by headache specialists, with high specificity and sensitivity of the diagnostic engine (Cowan et al., 2022). The use of tracking tools has also been shown to improve communication between patients and their providers and can aid in understanding of the burden and optimized treatment (Bensink et al., 2021).

4. Digital tools for diagnosing migraines have been available for several decades, but over the past decade and a half, a large number of new tools have been developed that rely on machine learning and other state-of-the-art digital tools.
5. There are no known disparities in current access to the technique among various sub-populations in the United States along racial, ethnic, socioeconomic, or geographic lines other than the general disparities that exist in access to health care.
6. In addition to the limited supply of headache specialists for a large patient population, other drawbacks to previous in person interviews and assessments include the higher costs and longer wait times. Digital tools can reduce these costs, improve patientcenteredness in the health care interaction, and restructure the clinical encounter and speed up decision-making and diagnosis (Cowan et al., 2022). Additionally, some, some clinicians who are available are not trained in diagnosing migraine and patients may be hesitant to approach clinicians about their migraines for a variety of reasons.
7. The range of outcomes generally seen with digital migraine diagnostic tools are the same as with standard clinical diagnostics—that is, the presence or absence of migraine or other type of headache.
8. Digital migraine diagnostic tools are designed to be either self-administered or administered by clinicians with no specialized training other than familiarity with headaches and migraine. The validity of the tools should not depend on any specialized abilities.
9. There are no known impediments to increasingly widespread use of the technique as a medical best-practice except the general impediments to digital health technologies, such as attitudes of patients, clinicians, and health care administrators. Many have been tested in specialized clinical settings, and more research can guide the implementation and use in community settings and primary care (Cowan et al., 2022).
10. There are small limitations with the use of digital tools, as they are unable to identify or interpret nonverbal behavior or conversational cues to allow for more sharing of sensitive information by the patient with the provider administering a test (Cowan et al., 2022). However, the technique’s diagnostic and evaluative efficacy are still high, and, with machine learning and artificial intelligence advancements in the future, it is conceivable that these limitations will be addressed.

Surface Electromyography

Electromyography (EMG) records the electrical activity in skeletal muscles. Because muscles develop abnormal electrical signals when there

is nerve or muscle damage, EMG can be is used to diagnose nerve and muscle disorders, spinal nerve root compression, and motor neuron disorders such as amyotrophic lateral sclerosis. Surface EMG (sEMG) is a variant of EMG in which multiple electrodes are used on a person’s skin to get multiple readings of muscle activity just under the skin. While it cannot detect signals from muscles at the same depth that is possible with typical EMG—which uses needles inserted into muscles—it has the advantage that it can gather information on muscle activity over a much greater area than EMG.

While sEMG is not a new technique—it was originally developed in the 1940s to study muscle physiology—the power of the technology has grown remarkably over time, in large part due to advances in the analytical tools used to analyze sEMG signals (Felici and Del Vecchio, 2020), and today the technique is widely used in neurophysiological research (Campanini et al., 2020) and rehabilitation (Kotov-Smolenskiy et al., 2021). It has a number of potential clinical applications as well, and although its clinical use has been limited to date, a number of neurophysiologists have argued that it should be more widely adopted in the clinic (Campanini et al., 2020; Feldner et al., 2019; Felici and Del Vecchio, 2020; Hogrel, 2005). Among the current clinical applications of sEMG are the assessment of muscle coordination, particularly in clinical gait analysis; the functional diagnosis of and monitoring of therapeutic outcomes for neurological impairments such as cerebral palsy and stroke; and the study of orthopedic issues such as degenerative joint disease and back pain research (Campanini et al., 2020). However, because standards and protocols for sEMG lack consensus, they cannot yet be recommended to assess muscle co-contraction during gait in people with neurological impairment (Rosa et al., 2014).

The requested details related to the use of sEMG in diagnosis are as follows:

1. The accepted clinical uses of sEMG include the assessment of muscle coordination, particularly in clinical gait analysis; the functional diagnosis of and monitoring of therapeutic outcomes for neurological impairments such as cerebral palsy and stroke; and the study of orthopedic issues such as degenerative joint disease and back pain research.
2. The technique represents an advancement in its ability to provide a detailed examination of muscle firing and gain insights into the level and type of disability resulting from muscle firing issues.
3. Specific impairments that are more accurately assessed with the technique include muscle injuries and impairments caused by cerebral palsy and stroke as well as orthopedic issues related to degenerative joint disease.

4. The technique was developed in the 1940s and has grown in power and applicability over time, becoming particularly valuable for clinical applications in the past couple of decades, but there is no specific date at which it became generally available.
5. There are no known disparities in current access to the technique among various sub-populations in the United States along racial, ethnic, socioeconomic, or geographic lines.
6. The technique is not replacing a previously used method.
7. Surface EMG provides information about patterns of muscle firing, including details about irregularities and weakness of the firing, which in turn offers information about muscle impairments caused by an injury or disease.
8. Surface EMG equipment, which typically costs between $10,000 and $40,000, is relatively straightforward to operate and can be used in almost any clinical setting, but its results can be difficult to interpret. Thus, the main barrier to its clinical use is the lack of specialists who have been trained in the analysis and interpretation of its output (Campanini et al., 2020).
9. The main impediments to the increasingly widespread use of sEMG are the lack of clinicians trained in its use and, more broadly, a lack of recognition of its clinical value (Campanini et al., 2020).
10. At this point, because of the limited amount of clinical experience with the technique, there is little known about the limitations of sEMG’s diagnostic or evaluative efficacy.

Neuromuscular Ultrasound

While ultrasonography using sound waves to create images has been around for decades, its use in the diagnosis of neuromuscular disorders is growing and becoming a standard element in the evaluation of peripheral nerve and muscle disease. Neuromuscular ultrasound is noninvasive, low risk, painless for the patient, easily available, and generally inexpensive, and can refine diagnosis and improve patient care. Recently, the Centers for Medicare & Medicaid Services updated their Relative Value file to include updated reimbursement for neuromuscular ultrasound (ACR, 2023), enabling providers to bill separately for the professional component and the technical component; and thus, demonstrating the general acceptance and usability of this technique into the mainstream of neurological diagnosis procedures.

The requested details related to the use of neuromuscular ultrasound are as follows:

1. The most common use of ultrasound is to aid in localization of entrapment neuropathies (Gonzalez and Hobson-Webb, 2019), and

it is also used in evaluation of neuropathies, myopathies, and motor neuron diseases. These conditions can include carpal tunnel syndrome, ulnar nerve entrapment, nerve trauma, or peripheral nerve tumors. It is increasingly being used for non-traumatic brachial plexus lesions and can also act as a potential marker of disease progression in Duchenne muscular dystrophy (Gonzalez and Hobson-Webb, 2019).

2. Ultrasound offers a valuable adjunct to electrodiagnostics helping to characterize nerve entrapments, neuropathies, and myopathies (Hommel et al., 2017). This technique is more sensitive than MRI in detecting peripheral nerve pathologies, and can be used as a biomarker for conditions such as muscular dystrophy and spinal muscular dystrophy (Mah and Van Alfen, 2018).
3. For the detection of fasciculation in patients with amyotrophic lateral sclerosis, ultrasound provided superior rates than those achieved with the standard of electromyography (Duarte et al., 2020).
4. Neuromuscular ultrasound has developed rapidly over the past 20 years, and is now used worldwide at the point of care to augment diagnostic capabilities (Gonzalez and Hobson-Webb, 2019).
5. Ultrasound is becoming more widespread, but there may still be geographic areas where there are access issues such as the lack needed expertise or equipment. For example, one study on general ultrasound access found more than 38 percent of rural counties had access to point of care ultrasound, compared to more than 88 percent of metropolitan counties (Peterman et al., 2022).
6. Previously used electrodiagnostic studies would often give inconclusive or unreliable results in the first few weeks following nerve injury; therefore, ultrasound is an important tool during this acute period (Gonzalez and Hobson-Webb, 2019). In comparison to the gold standard EMG, ultrasound is better tolerated, as EMG results can be less than optimal due to pain intolerance (Mah and Van Alfen, 2018). Additionally, MRI would often be used for neuromuscular imaging, but ultrasound is much more portable and readily available—more easily used for children and adults at the point of care.
7. Overall, the ultrasound detects neuromuscular changes examining echogenicity and cross-sectional area of nerves (Bulinski et al., 2022). In carpal tunnel syndrome, increased cross sectional area of the median nerve seen on the ultrasound at a certain point on the bone is an accurate marker for diagnosis (Shook, 2015). Diagnosis of complete nerve transection or stump neuromas can be performed after suspected nerve trauma.

8. Neuromuscular ultrasound is within the scope of practice for specialists in neurology and physical medicine and rehabilitation who have demonstrated certain prerequisites for performance (AANEM, 2023). This typically includes many physiatrists and neurologists, as well as physicians certified by the American Board of Electrodiagnostic Medicine.
9. One barrier to this technique becoming more widespread is the concern by clinical neurophysiologists over how to identify and manage non-neuromuscular findings (Walker et al., 2021). Other factors preventing more widespread uptake include the significant costs of equipment, available teaching and training experience, and the gaps in knowledge and applicability (Carrol and Simon, 2020).
10. Potential limitations of this technique include the inability to image deeper structures within the body, and reduced sensitivity in detecting certain neuromuscular diseases in young children and those with mitochondrial myopathies (Mah and Van Alfen, 2018). It also has not yet been proven to detect critical illness neuromyopathy.

Electroencephalogram

Electroencephalogram (EEG) is a procedure that measures electrical activity in the brain using small electrodes attached to the scalp. The patterns it records in different regions of the brain will show normal or abnormal activity, such as slower waves or sharper spikes, that can indicate brain disorders. Routine EEG has been around since the 1920s and used extensively as one of the main diagnostic tests for epilepsy as well as diagnosing other brain disorders such as, tumors, stroke, sleep disorders, or brain damage from a head injury (Mayo Clinic, 2023b). But as digital technology has advanced in more recent decades, advances in EEG have emerged, including prolonged EEG either with or without video, which can provide more assured diagnoses, and identify regions of the brain where the abnormalities are occurring to inform surgical evaluation.

The requested details related to the use of prolonged EEG for diagnosis are as follows:

1. EEGs can be used to evaluate various brain disorders including epilepsy, brain tumors, stroke, narcolepsy, Alzheimer’s disease, or certain psychoses (Johns Hopkins Medicine, 2023).
2. The combination of prolonged EEG and video can provide answers to questions of whether the events are related to epilepsy or not, and where the likely focus is. The ability of this technique to be used in ambulatory or home settings more recently also makes

it much more accessible to a greater proportion of patients and reduces the costs associated with hospital visits.

3. A video-EEG recording of events in question is the most definitive test to clarify a seizure type (Benbadis et al., 2020). Especially when seizures do not respond to medications, video-EEG monitoring is the best available diagnostic tool and a key technique for epilepsy centers (Benbadis et al., 2004).
4. Over the past 20 years, prolonged EEG monitoring with video has become increasingly used and relevant for assessing types of seizures.
5. Given the variability in insurance coverage for patients based on a number of factors, as well as general healthcare disparities, some have more difficulty accessing techniques such as prolonged EEG with video. One study found uninsured individuals and those using Medicare and Medicaid had significant gaps in access to video-EEG monitoring (Schiltz et al., 2013). Additionally, this technique was least commonly used by Black patients, male patients, and those with multiple comorbid conditions. Another study noted the influence of structural racism, and found that despite Black patients being admitted at high rates, they tended to seek more emergency care for seizures, with less access to video-EEG monitoring and specialized epilepsy services (Kamitaki et al., 2022).
6. A prolonged EEG may be more likely than to catch a seizure while it is happening, compared to a routine EEG that cannot diagnose epilepsy if a seizure does not happen during the 20-minute test itself; the results of a routine EEG may appear normal in between seizures (Rossetti et al., 2020).
7. Prolonged EEG measure include the presence or absence of epileptiform discharges, and presence or absence of “events” of interest, and presence of patterns associated with coma (Benbadis et al., 2020).
8. A technician measures the patient’s head and attaches electrodes to the scalp, connecting them with wires to the machine. Prolonged EEGs, either ambulatory or inpatient, may last from several hours to a few days. After the test, physicians or neurologists trained to interpret the readout, typically someone board certified in neurophysiology. More recently, ambulatory EEG with video has been possible given improvements in computers and remote access, making this possible in outpatient or home settings for the first time (Benbadis et al., 2020).
9. While prolonged EEG monitoring can now be done inpatient or in ambulatory settings, there are advantages and disadvantages to both. A reason the ambulatory version has not yet surpassed the inpatient video-EEG is the frequency at which patients are not on

camera during events in question, resulting in inconclusive study, thereby requiring inpatient EEG (Benbadis et al., 2020). The ability to safely reduce medications during the procedure is also challenging in this scenario.

10. Some factors can influence the reading or accuracy of an EEG test, such as low blood sugar in the patient, body movement, certain medications, and caffeine intake (Johns Hopkins Medicine, 2023). There can also be overreliance on EEG as a diagnostic test, leading to misinterpretation of the results, which is a well-known problem in epilepsy management. Without recording EEG patterns during an active seizure, it is only useful as a supportive tool for epilepsy diagnosis (Tatum, 2013).

SELECTED FUNCTIONAL ASSESSMENTS FOR NEUROLOGICAL DISORDERS

There is a vast number of instruments for assessing function in patients with neurological diseases and conditions. Given the infeasibility of identifying which instruments are new or have been improved over the past 30 years, the committee elected to highlight relevant resources and selected instruments in this section of the report. As mentioned in Chapter 3, the National Institute of Neurological Disorders and Stroke’s Common Data Element provides a searchable database of functional assessment instruments and other measures applicable to a variety of neurological diseases, including, but not limited to: epilepsy, stroke, Parkinson’s disease, traumatic brain injury, and spinal cord injury (NINDS, 2023). In addition, the committee compiled lists of widely used instruments for assessing function in patients with debilitating neurologic conditions; these tests are shown in Appendix B. The tables in the appendix are organized by stroke, spinal cord injury, multiple sclerosis, Parkinson’s disease, traumatic brain injury, and vestibular dysfunction, and they identify the tests by name; the areas the test assesses and the specific conditions for which the test is used; the International Classification of Functioning, Disability, and Health (ICF) domain addressed (ICF is discussed in Chapter 2); and the level of evidence related to the support for its use.

Among the types of functional assessments for neurological disorders, there is a wide variety of neuropsychological tests that provide valuable information related to cognitive functioning (intellectual capacity, attention and concentration, processing speed, language and communication, visual-spatial abilities, and memory) (NASEM 2019). Patterns of abnormalities on neuropsychological testing can determine whether a patient’s cognitive difficulties are due to neurological problems or psychiatric ones, such as attention deficit, anxiety, or depression. Certain patterns of cognitive

abnormalities correlate with certain types of dementia; for example, neuropsychological testing helps to differentiate frontotemporal dementia from Alzheimer’s disease.

To provide examples of advances in instruments for assessing function in neurological disorders, the committee briefly describes advances in two assessment tools for measuring activity limitations and participation restrictions in patients with spinal cord injury (SCI). SCI affects many body functions, including bladder, bowel, respiratory, cardiovascular, and sexual function. SCI also has social, financial, and psychological implications and increases the risk for renal complications as well as for musculoskeletal injuries, pain, osteoporosis, and other problems throughout the patient’s life. Neurological recovery after traumatic SCI depends on the severity, level, and mechanism of the injury (Khorasanizadeh et al., 2019).

Spinal Cord Independence Measure

The Spinal Cord Independence Measure (SCIM) is a disability scale developed to specifically address the ability of SCI patients to perform basic activities of daily living and mobility with or without assistance from others and/or assistive devices. Previous versions, SCIM I and SCIM II, were valid and reliable instruments, but they did not take into account intercultural differences in the patient population. Researchers developed the SCIM III in 2002 as an international version of the prior forms (Catz et al., 2007). There are versions that can be performed by a therapists and self report. SCIM III contains 16 items covering three specific areas of function in patients with SCI: self-care (feeding, grooming, bathing, and dressing), respiration and sphincter management, and mobility abilities (bed and transfers and indoors/outdoors).

The Spinal Cord Injury Functional Ambulation Inventory

The Spinal Cord Injury Functional Ambulation Inventory (SCI-FAI) was designed to assess walking ability among patients with spinal cord injuries, with a particular focus on abnormalities in gait. It has three parts, each of which is scored separately: an assessment of gait (weight shift, step width, step rhythm, step height, foot contact with floor, and step length), with each leg scored individually; an assessment of the use of assistive devices (cane, crutches, walker, parallel bars, and various types of braces); and temporal and distance measures of walking (how much a person walks in a day, how far a person can walk in 2 minutes) (Field-Fote et al., 2001; SCIRE, 2022). The inventory is designed for patients who can walk independently, either with or without assistance, and the assessment can be carried out during a regular check-up or during a home visit by a clinician (SCIRE, 2022).

The technique represents an advance over previously available instruments because of its flexibility (it can be used in at-home assessments, in the clinic, or via video recordings) and its accuracy and inter-rater consistency.

It is worth noting that the SCI-FAI is just one of multiple measures that have been developed to assess gait and ambulation in those with spinal cord injuries. Others include the Walking Index for Spinal Cord Injury II, the 50-Foot Walk Test, the 10-Meter Walk Test, Functional Independence Measure–Locomotor (Jackson et al., 2008), and the Spinal Cord Injury Functional Ambulation Profile (Musselman et al., 2011). SCI-FAI is recommended for assessment of gait and ambulation among those with spinal cord injuries by the Academy of Neurologic Physical Therapy (ANPT, n.d.).

EMERGING DIAGNOSTIC AND EVALUATIVE TECHNIQUES

The section describes emerging diagnostic techniques for confirming or ruling out a neurologic disorder and potentially disabling impairment. These techniques are generally used in research and not commonly in clinical applications at this time, but they have the potential to be useful clinical diagnostic techniques and will likely influence how neurological disorders are diagnosed and evaluated in the near future.

Magnetic Resonance Imaging-based Advanced Techniques

As noted above, MRI has been used in a wide variety of ways to explore the structure and function of the brain, and the many different varieties of MRI, such as functional MRI and diffusion-weighted MRI, offer different types of information (Levin, 2022). In particular, the various different types of MRI are widely used by clinical researchers looking to get insights into the etiology and treatment of different neurological diseases and injuries (Zhan and Yu, 2015). Many of these research uses of MRI can be applied in the clinic for diagnostic or prognostic purposes, and it would be practically impossible to list every technique in use today that might be put to work in the future as a neurological diagnostic tool. fMRI is particularly salient because it is being widely used in research into various neurodegenerative diseases and movement disorders, and it could make its way into the clinical diagnosis of many of these diseases in the near future (Zhan and Yu, 2015). Resting-state functional MRI has also shown promise in the diagnosis of Parkinsonian syndromes (Filippi et al., 2019).

Electrical Impedance Myography

In electrical impedance myography (EIM) “a weak, high-frequency electrical current is applied to a muscle or muscle group of interest and the

resulting voltages measured” (Sanchez and Rutkove, 2017, p. 107). The technique, which can be used noninvasively, is useful for assessing various neuromuscular disorders and has been suggested as a possible primary diagnostic tool (Cebrián-Ponce et al., 2021; Sanchez and Rutkove, 2017; Spieker et al., 2013; Tarulli et al., 2005).

To date, although EIM has the potential to aid in an initial diagnosis, the main focus of clinicians and researchers using the technique has been on evaluating the severity of a disease as well as its progression over time and response to therapy. Specifically, EIM has been used in clinical trials involving a number of neuromuscular disorders, including amyotrophic lateral sclerosis (ALS), Duchenne muscular dystrophy, spinal muscular atrophy, facioscapulohumeral muscular dystrophy, and sarcopenia (Sanchez and Rutkove, 2017; Spieker et al., 2013). The technique allows clinicians to evaluate muscles more easily or with greater sensitivity than existing techniques. A recent review of the technique concludes:

In addition, other emerging techniques include advances in remote patient monitoring devices with applications in the detection of various neurological disorders. See this discussion in Chapter 3 under digital diagnostic technologies.

REFERENCES