Abstract
In this chapter, the established investigative techniques for aiding diagnosis in neurodegenerative disease are reviewed. Beginning with neuropsychological analysis, this review ranges though structural (anatomic), dynamic, and functional brain imaging using MRI and radio-nucleotide scanning to complex neurophysiological applications. In each section, the increasing likelihood of developing true noninvasive biomarkers is addressed. The future of multi-modality imaging and its contribution to, not only to diagnosis, but to classification, prognosis, and treatment outcome in neurodegeneration is considered.
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Further Reading
Neuropsychology
Goldstein, L.H. and McNeil, J.E (eds) Clinical Neuropsychology: a practical guide to assessment and management for clinicians John Wiley and Sons. 2004
Gurd J, Kischka U, Marshall J C (Eds). The handbook of clinical neuropsychology. 2nd ed Oxford University Press. 2010.
Lezak, M. D. Neuropsychological assessment. 4th edition. Oxford University Press, Oxford. 2004.
MR Imaging (Anatomic)
Schmidt R, Havas D, Ropele S, Enzinger C, Fazekas F. MRI in Dementia. Magnetic Resonance Imaging Clinics of North America, Volume 18, Issue 1, Pages 121–132, February 2010.
Small GW, Bookkeeper SY, Thompson PM, Cole GM, Huang S-C, Kepe V, Barrio JR. Current and future uses of neuroimaging for cognitively impaired patients The Lancet Neurology February 2008 (Vol. 7, Issue 2, Pages 161–172)
Tartaglia MC, Vitali P, Migliaccio R, Agosta F, Rosen H. Neuroimaging in Dementia. Continuum- Dementia 2010 Vol 16(3) pp153–175
MR Imaging (Functional)
Celone KA, Calhoun VD, Dickerson BC, et al. Alterations in Memory Networks in Mild Cognitive Impairment and Alzheimer’s Disease: An Independent Component Analysis. J. Neurosci. October 4, 2006;26(40):10222–10231
Honey CJ, Sporns O, Cammoun L, et al. Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci U S A. Feb 10 2009;106(6):2035–2040
Lowe MJ, Beall EB, Sakaie KE, et al. Resting state sensorimotor functional connectivity in multiple sclerosis inversely correlates with transcallosal motor pathway transverse diffusivity. Hum Brain Mapp. Jul 2008;29(7):818–827
Misra C, Fan Y, Davatzikos C. Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. Neuroimage. Feb 15 2009;44(4):1415–1422
Plant C, Teipel SJ, Oswald A, et al. Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer’s disease. Neuroimage. Mar 2010;50(1):162–174
Nuclear Brain Imaging
Sawle GW, Costa DC. Nuclear Medicine in the management of patients with Parkinsonian movement disorders. In Ell P, Ghambir S, eds. Nuclear Medicine in Clinical Diagnosis and Treatment, 3rd ed. Philadelphia: Churchill Livingstone
Silverman D, ed. PET in the Evaluation of Alzheimer’s Disease and Related Disorders. New York: Springer 2009
Neurophysiology
Brown P, “Oscillatory nature of human basal ganglia activity: Relationship to the pathophysiology of Parkinson’s disease”, Movement Disorders, Volume: 18 Issue: 4 Pages: 357–363, Apr 2003
Coben LA, Danziger W, Storandt M, “A Longitudinal EEG Study of Mild Senile Dementia of Alzheimer Type – Changes at 1 year and at 2.5 years”, Electroencephalography and Clinical Neurophysiology, volume: 61 issue: 2 pages: 101–112, 1985
Haupt M, Gonzalez-Hernandez JA, Scherbaum WA, “Regions with different evoked frequency band responses during early-stage visual processing distinguish mild Alzheimer dementia from mild cognitive impairment and normal aging”, Neuroscience Letters, Volume: 442 Issue: 3 Pages: 273–278, Sep 2008
Jeong JS, “EEG dynamics in patients with Alzheimer’s disease”, Clinical Neurophysiology Volume: 115 Issue: 7 Pages: 1490–1505, Jul 2004
Leow AD, Yanovsky I, Parikshak N, Hua X, Lee S, Toga AW, Jack CR, Bernstein MA, Britson PJ, Gunter JL, Ward CP, Borowski B, Shaw LM, Trojanowski JQ, Fleisher AS, Harvey D, Kornak J, Schuff N, Alexander GE, Weiner MW, Thompson PM, “Alzheimer’s Disease Neuroimaging Initiative: A one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition” Neuroimage, Volume: 45 Issue: 3 Pages: 645–655, Apr 2009
Maxim V, Sendur L, Fadili J, Suckling J, Gould R, Howard R, Bullmore E, “Fractional Gaussian noise, functional MRI and Alzheimer’s disease”, Neuroimage, Volume: 25 Issue: 1, Pages: 141–158, Mar 2005
Pezard L, Jech R, Ruzicka E., “Investigation of non-linear properties of multichannel EEG in the early stages of Parkinson’s disease”, Clin. Neurophysiol. 112:38–45, 2001
Seiss E, Praamstra P, Hesse CW, Rickards H “Proprioceptive sensory function in Parkinson’s disease and Huntington’s disease: evidence from proprioception-related EEG potentials”, Experimental Brain Research, Volume: 148 Issue: 3, pages: 308–319, Feb 2003
Thakor NV, Tong S, “Advances in quantitative electroencephalogram analysis methods”, Annual Reviews of Biomedical Engineering, 6:453–495, 2004
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Bokde, A.L.W., Meaney, J.F.M., Sheehy, N.P., Reilly, R.B., Abrahams, S., Doherty, C.P. (2011). Advances in Diagnostics for Neurodegenerative Disorders. In: Hardiman, O., Doherty, C. (eds) Neurodegenerative Disorders. Springer, London. https://doi.org/10.1007/978-1-84996-011-3_2
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DOI: https://doi.org/10.1007/978-1-84996-011-3_2
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