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Electrophysiological techniques for clinical diagnosis

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Electrophysiological techniques for clinical diagnosis will discuss the techniques borrowed from electrophysiology used in the clinical diagnosis of subjects. There are many processes that occur in the body which produce electrical signals that can be detected. Depending on the location and the source of these signals, distinct methods and techniques have been developed to properly target them.

Role of electrophysiology in clinical medicine

Electrophysiology has a very important role in ensuring accurate clinical diagnoses. Many neurological diseases cause symptoms that manifest far from the injured or deceased tissues. Locating and treating all affected areas of the body is essential for proper patient care. Electrophysiology allows for the investigation of abnormal electrical signals in the body’s tissues. It provides quantitative data to clinicians, supporting diagnostic processes and evaluating treatment success. Often, biological measures such as electrophysiology are more useful in assessing symptom severity than existing clinical measurement scales. Their objective nature removes subjective assignment of scores to symptom severity, subsequently leading to better informed healthcare decisions.[1]

Electrophysiological techniques

There are various techniques available to study and measure the electromagnetic signals of the body.[2] The brain, the heart and skeletal muscles are prime sources of electric and magnetic fields that can be recorded and the resulting patterns can give insight on what ailments the subject may have. These electrophysiological techniques are named according to what data is measured and sometimes the anatomical location of the sources as follows:

Electroencephalography (EEG)

Main article: Electroencephalography

Electroencephalography is the measurement of brain activity through the surface of the scalp.[3] Electroencephalography data can be processed through analytical procedures and certain derived summary indices of these analyses are called quantitative electroencephalography (QEEG).[4] Data from evoked potentials can also be used processed in certain ways that can be considered quantitative EEG as well. If QEEG data is mapped then it is a topographic QEEG (also known as brain electrical activity mapping or BEAM )

Electrocardiography (EKG)

Main article: Electrocardiography

The heart is the muscle that pumps oxygenated blood to the whole body. As a very active muscle, it has peculiar electrical activity that can be measured and analyzed. Electrocardiography is the measurement of these signals.

Electromyography (EMG)

Main article: Electromyography

Electromyography is the measurement and analysis of the electrical activity in skeletal muscles. This technique is useful for diagnosing the health of the muscle tissue and the nerves that control them.[5]

EMG measures action potentials, called Motor Unit Action Potentials (MUAPs), created during muscle contraction. A few common uses are determining whether a muscle is active or inactive during movement (onset of activity), assessing the velocity of nerve conduction, and the amount of force generated during movement. Of these uses, determining the onset of muscle activity has been shown to be the most accurate.[6]

Main article: Event-related potential

The firing of neurons throughout the brain has been known to have localized relationships to certain functions, processes and reactions to stimuli. With proper equipment it is possible to locate where in the brain neurons have been activated and measure their event related potentials. Event-related potentials can be classified as either: sensory, motor or cognitive.[7]

Evoked Potentials (EPs)

Main article: Evoked potentials

Measurement of spontaneous electrophysiological activity does not always provide the desired information from the signals of interest. In such cases, the application of a stimulus to the desired target can produce transient evoked potentials that can provide further insight not obtained from solely passive recording methods such as EEG, ECG, EMG or MEG.

Magnetoencephalography (MEG)

Main article: Magnetoencephalography

The measurement of the naturally occurring magnetic fields produced by the brain's electrical activity is called magnetoencephalography. This method differs from magnetic resonance imaging in that it passively measures the magnetic fields without altering the body's magnetization. However, data from MEG and MRI can be combined to create images that approximately map the estimated location of the natural magnetic fields. This composite imaging process is called magnetic source imaging (MSI).

Nerve conduction study (NCS)

Main article: Nerve conduction studies

An NCS measures the electrical conduction velocity and other characteristics of nerves in the body.

Diagnosable conditions and applicable methods

The toolset of available electrophysiological techniques has been carefully applied to the study of patients suffering from a wide variety of conditions in the hopes of finding novel and more reliable diagnosis. For some conditions the use of these methods in their diagnosis is standard, but for others their applicability for diagnosis is still in the research phase. Some conditions where the usefulness of electrophysiological techniques has been determined or being studied with promising results follow:

Brainstem lesions in traumatic brain injury

In the event of a traumatic brain injury the presence of a brainstem lesion has a significant impact in the prognosis of the patient. Although the development of MRI has allowed for very effective detection of brainstem lesions, evoked potentials measurements are also an electrophysiological technique that has been used for over 30 years in this context.[8]

Carpal tunnel syndrome (CTS)

The compression of the median nerve within the carpal canal of the wrist and the progression of symptoms resulting from this entrapment is known as carpal tunnel syndrome (CTS). Nerve conduction studies have been used as a control electrophysiological method in the development of better CTS diagnostic techniques.[9]

Dementia

Dementia is a progressive, degenerative brain disease that impairs cognitive functions.[10] Alzheimer’s disease and other types of dementia diagnosis is being improved through the use of electroencephalogram (EEG) and event-related potentials(ERP).

Epilepsy

Abnormally excessive or synchronous neuronal activity in the brain can cause seizures. These symptoms are characteristic of the neurological disorder known as epilepsy. Epilepsy is typically diagnosed with an EEG test.[11] However, the effectiveness of MEG in the diagnosis of neocortical epilepsy has also been established.[12]

Essential tremor

It is hard to diagnose essential tremor and differentiate it from other types of tremor.[13] The burst discharge patterns of EMG signals is compared to the frequency and amplitute of videotaped tremors to evaluate and diagnose essential tremor.

Heart disease

Heart disease is one of the leading causes of death in the world. Diagnosis of heart disease can require various non-electrophysiological methods since there are many possible ailments, but EKG can be used to detect some.

Spasticity (cerebral palsy and stroke)

Spasticity is a velocity dependent resistance to stretch due to increases in gamma motor neuron activity [14] The most commonly affected muscles are those that oppose gravity, the elbow and wrist flexors, knee extensors and ankle plantarflexors.[15] Spasticity is a side effect of multiple central nervous system disorders including Cerebral Palsy, Stroke, Multiple Sclerosis and spinal cord injuries and results in limited joint range of motion of the affected limb.[16]

Stroke is currently the leading cause of death in the United States.[17] Ischemic stroke is the most common form, accounting for 85% of all stroke cases. It involves restricted blood flow to areas of the brain, resulting from a blood clot or ruptured vessel, and ultimately causes brain tissue damage. Spasticity is a common side effect of this brain tissue damage and affects the lives of many stroke survivors. The increased muscle tone of spastic muscles encumbers goal-directed movements; impairing activities of daily living while additionally causing pain and discomfort. Valid, reliable, and sensitive measures of spasticity are necessary to accurately diagnose patients suffering from this neurophysiological condition and assess the effectiveness of various treatment modalities. Electromyography (EMG) has been proposed by multiple researchers as an alternative measurement technique to quantify spasticity.

EMG is used to determine the onset of muscle activity in spastic muscles, allowing for comparison between affected patients and asymptomatic individuals. Measurement tools involving EMG are argued to be more sensitive than currently used clinical scales like the Modified Ashworth Scale (MAS) in detecting spasticity symptom severity. The use of EMG offers a quantitative value of severity as opposed to relying on subjective scoring protocols. Malhotra et al. (2008)[18] used EMG and the MAS to determine which method was more effective in detecting spasticity of the wrist flexors. In their sample of 100 patients (median age 74 years), they found that using EMG to detect onset of muscle activity during multiple passive stretch repetitions of the wrist at various velocities, successfully detected spasticity in 87 patients while the MAS only detected spasticity in 44 of these individuals. These findings support the use of EMG as a more sensitive diagnostic tool than the MAS and therefore advantageous when used in a clinical setting. Similarly, EMG was successful in detecting elbow flexor spasticity symptom improvement in six post-stroke subjects (mean age 54.16 ± 7.9 years) following a neural mobilization technique of the median nerve. At 90 degrees of flexion and full extension of the elbow, muscle activity decreased from 17% pre-treatment to 11% post-treatment. These patients had initial MAS scores of 1 or 2, and the MAS was incapable of detecting the same symptom improvements post-treatment as seen with the EMG method.[19]

Cerebral palsy is another group of disorders caused by abnormal brain development or damage to the developing brain, which may result in spasticity.[20] EMG has also been successfully used to quantify spasticity in this patient population. Using surface EMG and a torque motor, Levin et al. (1994, 2000)[21][22] demonstrated a direct relationship between the velocity of stretch and the onset of spasticity. They incorporated EMG in their use of a novel motorized manipulandum due to its ability to detect stretch reflex activity and thus incorporate the velocity-dependent nature of spasticity in the resulting diagnostic values.

Multiple sclerosis

The demyelination and scarring of axons in the neurons of the nervous system can affect their conduction properties and seriously harm the normal communication of the brain with the rest of the body. Multiple sclerosis (MS) is a disease that causes this deterioration of the myelin sheath. There isn't a unique test to diagnose MS and several studies must be combined to determine the presence of this disease. However, visual evoked potentials do play a role in the whole diagnostic process.[23]

Parkinson's disease

Parkinson's disease is a degenerative ailment that affects the central nervous system and is typically identified initially by its motor related symptoms. Accurate differentiation of PD from any other neurological disorder and the identification of the disease course is important in establishing an appropriate antiparkinsonian therapy. In the diagnostic role, surface EMG is a very informative method used to obtain relevant quantitative characteristics.[24]

References

  1. ^ Mbuya, SO (January 2006). "The role of neuro-electrophysiological diagnostic tests in clinical medicine". East African medical journal. 83 (1): 52–60. doi:10.4314/eamj.v83i1.9362. PMID 16642752.
  2. ^ Arciniegas, David B, C Alan Anderson, and Donald C Rojas, Electrophysiological Techniques. Methods in physiological psychology III. Academic Press, 1978. 385-404.
  3. ^ L. Jasmin "EEG"
  4. ^ Duffy, FH; Hughes, JR; Miranda, F; Bernad, P; Cook, P (October 1994). "Status of quantitative EEG (QEEG) in clinical practice, 1994" (PDF). Clinical EEG (electroencephalography). 25 (4): VI–XXII. doi:10.1177/155005949402500403. PMID 7813090.
  5. ^ Mayo Clinic Staff, "Electromyography (EMG)". Retrieved 27 July 2012
  6. ^ Kamen, G. & Gabriel, D. A. (2010). Essentials of Electromyography. Champaign, IL: Human Kinetics.
  7. ^ Bressler, S. L. and Ding, M. 2006. "Event-Related Potentials". Wiley Encyclopedia of Biomedical Engineering.
  8. ^ Wedekind, C., Hesselmann, V. and Klug, N. (2002), Comparison of MRI and electrophysiological studies for detecting brainstem lesions in traumatic brain injury. Muscle Nerve, 26: 270–273.
  9. ^ Yagci I, Gunduz OH, Sancak S, Agirman M, Mesci E, Akyuz G, Comparative electrophysiological techniques in the diagnosis of carpal tunnel syndrome in patients with diabetic polyneuropathy.Diabetes Res Clin Pract. 2010 May;88(2):157-63. Epub 11 Mar2010 .
  10. ^ Ifeachor, E. C., et al, "Biopattern Analysis and Subject-Specific Diagnosis and Care of Dementia "., Engineering in Medicine and Biology 27th Annual Conference, September 2005
  11. ^ A.D.A.M. Medical Encyclopedia., "Epilepsy - PubMed Health". Retrieved 27 July 2012
  12. ^ H. Stefan, "The Role of MEG in Epilepsy Diagnosis and Treatment", ACNR, Volume 4, No 2, May/June 2004
  13. ^ E.D. Louis and S.L. Pullman, "Comparison of Clinical vs Electrophysiological Methods of Diagnosing of Essential Tremor"., Movement Disorders, Vol. 16, No. 4, 2001
  14. ^ Lance, J.W., The control of muscle tone, reflexes, and movement: Robert Wartenberg Lecture, Neurology, 30 (1980) 1303- 1313.
  15. ^ Ansari, NN; Naghdi, S; Arab, TK; Jalaie, S (2008). "The interrater and intrarater reliability of the Modified Ashworth Scale in the assessment of muscle spasticity: limb and muscle group effect". NeuroRehabilitation. 23 (3): 231–7. PMID 18560139.
  16. ^ http://www.wemove.org/spa/
  17. ^ http://www.cdc.gov/stroke/
  18. ^ Malhotra, S., Cousins, E., Ward, A., Day, C., Jones, P., Roffe, C., Pandyan, A. (2008). An investigation into the agreement between clinical, biomechanical, and neurophysiological measures of spasticity. Clinical Rehabilitation, 22:1105-1115.
  19. ^ Castilho, J., Ferreira, L. A. B., Pereira, W. M., Neto, H. P., Morelli, J. G. S., Brandalize, D., Kerppers, I I., Oliveria, C. S. (2012). Analysis of electromyographic activity in spastic biceps brachii muscle following neural mobilization. Journal of Bodywork and Movement Therapies, 16: 364-368.
  20. ^ http://www.cdc.gov/ncbddd/cp/index/html
  21. ^ Levin, M. F., & Feldman, A. G., (1994). The role of stretch reflex threshold regulation in normal and impaired motor control. Brain Research, 657, 23-30.
  22. ^ Jobin, A., & Levin, M. F., (2000). Regulation of stretch reflex threshold in elbow flexors in children with cerebral palsy: A new measure of spasticity. Developmental Medicine and Child Neurology, 42, 531-540.
  23. ^ McDonald, W. I., Compston, A., Edan, G., Goodkin, D., Hartung, H.-P., Lublin, F. D., McFarland, H. F., Paty, D. W., Polman, C. H., Reingold, S. C., Sandberg-Wollheim, M., Sibley, W., Thompson, A., Van Den Noort, S., Weinshenker, B. Y. and Wolinsky, J. S. (2001), Recommended diagnostic criteria for multiple sclerosis: Guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol., 50: 121–127
  24. ^ Elena Lukhanina, Irina Karaban and Natalia Berezetskaya (2011), Diagnosis of Parkinson's Disease by Electrophysiological Methods. Diagnostics and Rehabilitation of Parkinson's Disease, Juliana Dushanova (Ed.), ISBN 978-953-307-791-8
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