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The use of CT in dementia

Published online by Cambridge University Press:  10 June 2011

Marco Pasi
Affiliation:
Department of Neurological and Psychiatric Sciences, University of Florence, Florence, Italy
Anna Poggesi
Affiliation:
Department of Neurological and Psychiatric Sciences, University of Florence, Florence, Italy
Leonardo Pantoni*
Affiliation:
Department of Neurological and Psychiatric Sciences, University of Florence, Florence, Italy
*
Correspondence should be addressed to: Leonardo Pantoni, MD, PhD, Department of Neurological and Psychiatric Sciences, University of Florence, Largo Brambilla 3, 50134 Florence, Italy. Phone: +39 055-794-7995; Fax: +39 055-429-8461. Email: [email protected].

Abstract

Neuroimaging has become part of the required investigations when assessing a patient with dementia. In this brief paper, we summarize the role of computed tomography (CT) in the routine work-up in dementia and provide some information about the role of the CT scan in the field of dementia research.

Although CT is far less sensitive than magnetic resonance imaging (MRI) in detecting changes associated with cognitive impairment, it may still have a role in this regard. This role is mainly that of detecting secondary, sometimes treatable causes of cognitive impairment, such as intracranial masses. In this sense, CT should be seen as a first-line tool. Possible advantages of CT are lower cost; shorter acquisition time, making it more adaptable to patients with poor compliance; and the possibility that it can be performed in patients with metal devices, such as a pacemaker.

The role of CT in the field of dementia research is very restricted in comparison to that of MRI, and is limited to the structural assessment of vascular lesions, and to a lesser extent, to that of degenerative changes, particularly when using specific slicing.

Type
Review Article
Copyright
Copyright © International Psychogeriatric Association 2011

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References

Chui, H. C., Victoroff, J. I., Margolin, D., Jagust, W., Shankle, R. and Katzman, R. (1992). Criteria for the diagnosis of ischemic vascular dementia proposed by the State of California Alzheimer's Disease Diagnostic and Treatment Centers. Neurology, 42, 473480.Google Scholar
De Leon, M. J., Ferris, S. H., George, A. E., Reisberg, B., Kricheff, I. I. and Gershon, S. (1980). Computed tomography evaluations of brain-behavior relationships in senile dementia of the Alzheimer's type. Neurobiology of Aging, 1, 6979.CrossRefGoogle ScholarPubMed
Dubois, B. et al. (2007). Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria. Lancet Neurology, 6, 734746.CrossRefGoogle ScholarPubMed
Erkinjuntti, T. et al. (2000). Research criteria for subcortical vascular dementia in clinical trials. Journal of Neural Transmission, 59 (Suppl.), 2330.Google Scholar
Feldman, H. H. et al. (2008). Diagnosis and treatment of dementia. Canadian Medical Association Journal, 178, 825836.CrossRefGoogle ScholarPubMed
Frisoni, G. B. et al. (2002). Radial width of the temporal horn: a sensitive measure in Alzheimer disease. American Journal of Neuroradiology, 23, 3547.Google ScholarPubMed
Frisoni, G. B. et al. (2003). Neuroimaging tools to rate regional atrophy, subcortical cerebrovascular disease, and regional cerebral blood flow and metabolism: consensus paper of the EADC. Journal of Neurology, Neurosurgery and Psychiatry, 74, 13711381.CrossRefGoogle ScholarPubMed
Gifford, D. R., Holloway, R. G. and Vickrey, B. G. (2000). Systematic review of clinical prediction rules for neuroimaging in the evaluation of dementia. Archives of Internal Medicine, 160, 28552862.CrossRefGoogle ScholarPubMed
Guo, X. et al. (2006). Midlife respiratory function related to white matter lesions and lacunar infarcts in late life: the Prospective Population Study of Women in Gothenburg, Sweden. Stroke, 37, 16581662.Google Scholar
Guo, X., Skoog, I., Idrizbegovic, E., Pantoni, L., Simoni, M. and Rosenhall, U. (2008). Hearing loss and cortical atrophy in a population-based study on non-demented women. Age and Ageing, 37, 333336.Google Scholar
Guo, X. et al. (2009). Blood pressure components and changes in relation to white matter lesions: a 32-year prospective population study. Hypertension, 54, 5762.CrossRefGoogle ScholarPubMed
Gustafson, D., Lissner, L., Bengtsson, C., Björkelund, C. and Skoog, I. (2004). A 24-year follow-up of body mass index and cerebral atrophy. Neurology, 63, 18761881.Google Scholar
Hachinski, V. C., Potter, P. and Merskey, H. (1987). Leuko-araiosis. Archives of Neurology 44, 2123.Google Scholar
Hebb, A. O. and Cusimano, M. D. (2001). Idiopathic normal pressure hydrocephalus: a systematic review of diagnosis and outcome. Neurosurgery, 49, 11661184.Google ScholarPubMed
Hort, J. et al. (2010). EFNS guidelines for the diagnosis and management of Alzheimer's disease. European Journal of Neurology, 17, 12361248.Google Scholar
Jobst, K. A. et al. (1992). Detection in life of confirmed Alzheimer's disease using a simple measurement of medial temporal lobe atrophy by computed tomography. Lancet, 340, 11791183.Google ScholarPubMed
Musicco, M., Sorbi, S., Bonavita, V. and Caltagirone, C. (2004). Study Group on Validation of the Guidelines for the Diagnosis of Dementia and Alzheimer's Disease of the Italian Neurological Society. Validation of the guidelines for the diagnosis of dementia and Alzheimer's disease of the Italian Neurological Society: study in 72 Italian neurological centers and 1549 patients. Neurological Sciences, 25, 289295.CrossRefGoogle Scholar
O'Brien, J. T. et al. (2000). Medial temporal lobe width on CT scanning in Alzheimer's disease: comparison with vascular dementia, depression and dementia with Lewy bodies. Dementia and Geriatric Cognitive Disorders, 11, 114118.CrossRefGoogle Scholar
Olesen, P. J. et al. (2010). Temporal lobe atrophy and white matter lesions are related to major depression over 5 years in the elderly. Neuropsychopharmacology, 35, 26382645.CrossRefGoogle ScholarPubMed
Pantoni, L. and Garcia, J. H. (1995). The significance of cerebral white matter abnormalities 100 years after Binswanger's report: a review. Stroke, 26, 12931301.CrossRefGoogle ScholarPubMed
Pantoni, L., Simoni, M., Pracucci, G., Schmidt, R., Barkhof, F. and Inzitari, D. (2002). Visual rating scales for age-related white matter changes (leukoaraiosis): can the heterogeneity be reduced? Stroke, 33, 28272833.Google Scholar
Román, G. C. et al. (1993). Vascular dementia: diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology, 43, 250260.Google Scholar
Schebesch, K. M., Woertgen, C., Rothoerl, R. D., Ullrich, O. W. and Brawanski, A. T. (2008). Cognitive decline as an important sign for an operable cause of dementia: chronic subdural haematoma. Zentralblatt Neurochirurgie, 69, 6164.Google Scholar
Scheltens, P. et al. (1998). White matter changes on CT and MRI: an overview of visual rating scales. European Task Force on Age-Related White Matter Changes. European Neurology, 39, 8089.Google Scholar
Scottish Intercollegiate Guidelines Network (2006). Management of Patients with Dementia: A National Clinical Guideline. Available at www.sign.ac.uk.Google Scholar
Simoni, M. et al. (2008). Prevalence of CT-detected cerebral abnormalities in an elderly Swedish population sample. Acta Neurologica Scandinavica, 118, 260267.CrossRefGoogle Scholar
Wahlund, L. O. et al. for the European Task Force on Age-Related White Matter Changes (2001). A new rating scale for age-related white matter changes applicable to MRI and CT. Stroke, 32, 13181322.CrossRefGoogle ScholarPubMed
Wattjes, M. P. et al. (2009). Diagnostic imaging of patients in a memory clinic: comparison of MR imaging and 64-detector row CT. Radiology, 253, 174183.CrossRefGoogle Scholar