Computed Tomography, Electroencephalography, and Clinical Features in the Differential Diagnosis of Senile Dementia

Ettlin, Thierry; Staehelin, Hannes B.; Kischka, Udo; Ulrich, J.; Scollo-Lavizzari, G; Wiggli, U; Seiler, Walter O.

doi:10.1001/archneur.1989.00520470081031

Cited by 59 publications

(14 citation statements)

References 11 publications

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“…Therefore, the sensitivity of the EEG in discriminating between AD and nondemented controls is primarily dependent on the severity of the dementia [30,31 ]. However, the EEG is of limited value in distinguishing among patients with AD alone, AD + CVD or vascular dementia [33][34][35]. Furthermore, there are few studies that have included information about the relationship between EEG and PWMLs in AD patients.…”

Section: Introductionmentioning

confidence: 99%

Electroencephalographic Correlates of Periventricular White Matter Lesions in Probable Alzheimer’ Disease

López

Brenner²,

Becker³

et al. 1995

Dement Geriatr Cogn Disord

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We evaluated the relationship between periventricular white matter lesions (PWMLs) and EEG abnormalities in probable Alzheimer''s disease (AD). We visually analyzed the EEG of 27 probable AD patients with mild to moderate degree of cognitive impairment participating in a longitudinal study of dementia. Patients had both CT and MRI scans performed at baseline examination, which also included an EEG. PWMLs were rated in CT and MRI films using a semiquantitative method. The EEGs were classified according to the Mayo Clinic Classification System. Abnormal EEGs correlated with PWMLs rating scores were detected on CT, but not on MRI. These data suggest that the presence of PWMLs contribute to the abnormal EEGs observed in AD patients, and that white matter abnormalities in CT correlate better with both the clinical findings and EEG than does the more sensitive but less specific MRI.

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Section: Introductionmentioning

confidence: 99%

Electroencephalographic Correlates of Periventricular White Matter Lesions in Probable Alzheimer’ Disease

López

Brenner²,

Becker³

et al. 1995

Dement Geriatr Cogn Disord

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“…Brain imaging is an important part of the diagnostic evaluation (1)(2)(3)(4). However, the brain image may be qualitatively difficult to distinguish between normal and demented persons, and more so between different dementia types such as AD and VD.…”

mentioning

confidence: 99%

Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

deFigueiredo

Shankle

Maccato

et al. 1995

Proc. Natl. Acad. Sci. U.S.A.

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Single photon emission with computed tomography (SPECT) hexamethylphenylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elderly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects. After initial image preprocessing and registration, image features were obtained that were representative of the mean regional tissue uptake. These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks. After training, the network classified independent trials of patients whose clinical diagnoses conformed to published criteria for probable AD or probable/possible VD. For the SPECT data used in the current tests, the OINN agreement was 80 and 86% for probable AD and probable/possible VD, respectively. These results suggest that artificial neural network methods offer potential in diagnoses from brain images and possibly in other areas of scientific research where complex patterns of data may have scientifically meaningful groupings that are not easily identifiable by the researcher.Alzheimer disease (AD), vascular dementia (VD), or both occur in 70-90% of all dementias and are often clinically difficult to distinguish. Brain imaging is an important part of the diagnostic evaluation (1-4). However, the brain image may be qualitatively difficult to distinguish between normal and demented persons, and more so between different dementia types such as AD and VD. Since disturbances of brain metabolism may precede structural changes, metabolic images can detect more subtle patterns of change earlier than anatomical ones. We chose single photon emission with computed tomography (SPECT) because (i) it provides measures of regional tissue uptake (hexamethylphenylethyleneamineoxime technetium-99 or HMPAO-99Tc) that show complex patterns of brain activity and because (ii) it is widely available. Improvements in the recognition, quantification, and classification of these image patterns could increase diagnostic sensitivity between normal and abnormal as well as between different subtypes of dementia.The need for better methods of diagnostic interpretation of brain images is illustrated by the large variability in their diagnostic interpretation by even well-trained neuroradiologists using standardized criteria. For example, the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) conducted an interrater reliability study among 14 participating CERAD neuroradiologists for interpreting specific mag-The publication costs of this article were defrayed in part by page charge payment. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact. netic resonance imaging features and found within-feature correlations ranging from 0.64 (for detecting cerebral sulcal dilatation) to 0.79 (for rating the size of the lateral and third ventricl...

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“…The coexistence of these markers on MRI may suggest the diagnosis of MIX ante mortem, which is otherwise difficult to distinguish from AD or MID [5,28]. Patients with and those without MTLA were similar regarding age and duration and se-, verity of dementia, suggesting that MTLA is not simply a nonspecific accompaniment of aging or of chronic dementia.…”

Section: Discussionmentioning

confidence: 93%

Medial Temporal Atrophy as a Magnetic Resonance Imaging Marker for Alzheimer's Disease

Barclay

Linden

Murtagh

1992

Journal of Neuroimaging

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Medial temporal lobe atrophy (MTLA) on brain magnetic resonance imaging (MRI) may help differentiate Alzheimer's disease (AD) from multiinfarct dementia (MID) and other dementias. MTLA was seen in 6 of 11 patients with clinically diagnosed AD, 16 of 20 with mixed dementia (with both AD and MID), 1 of 5 with psychiatric disease, and in none of 32 with MID or 8 with other dementias (p less than 0.0001). Increased patchy periventricular signal, or "unidentified bright objects" were seen in 2 of 11 patients with AD, 10 of 20 patients with AD and MID, and 26 of 32 patients with MID. A larger series with autopsy correlation may verify that MTLA is a reasonably specific marker for AD, and unidentified bright objects are a sensitive, but not specific, marker for vascular dementias.

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Computed Tomography, Electroencephalography, and Clinical Features in the Differential Diagnosis of Senile Dementia

Cited by 59 publications

References 11 publications

Electroencephalographic Correlates of Periventricular White Matter Lesions in Probable Alzheimer’ Disease

Electroencephalographic Correlates of Periventricular White Matter Lesions in Probable Alzheimer’ Disease

Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

Medial Temporal Atrophy as a Magnetic Resonance Imaging Marker for Alzheimer's Disease

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