Finding regional models of the Alzheimer disease by fusing information from neuropsychological tests and structural MR images

Background Identifying signs of Alzheimer disease (AD) through longitudinal and passive monitoring techniques has become increasingly important. Previous studies have succeeded in quantifying language dysfunctions and identifying AD from speech data collected during neuropsychological tests. However, whether and how we can quantify language dysfunction in daily conversation remains unexplored. Objective The objective of this study was to explore the linguistic features that can be used for differentiating AD patients from daily conversations. Methods We analyzed daily conversational data of seniors with and without AD obtained from longitudinal follow-up in a regular monitoring service (from n=15 individuals including 2 AD patients at an average follow-up period of 16.1 months; 1032 conversational data items obtained during phone calls and approximately 221 person-hours). In addition to the standard linguistic features used in previous studies on connected speech data during neuropsychological tests, we extracted novel features related to atypical repetition of words and topics reported by previous observational and descriptive studies as one of the prominent characteristics in everyday conversations of AD patients. Results When we compared the discriminative power for AD, we found that atypical repetition in two conversations on different days outperformed other linguistic features used in previous studies on speech data during neuropsychological tests. It was also a better indicator than atypical repetition in single conversations as well as that in two conversations separated by a specific number of conversations. Conclusions Our results show how linguistic features related to atypical repetition across days could be used for detecting AD from daily conversations in a passive manner by taking advantage of longitudinal data.

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Neuropsychological Profiles Differentiate Alzheimer Disease from Subcortical Ischemic Vascular Dementia in an Autopsy-Defined Cohort

Dementia and Geriatric Cognitive Disorders ◽

10.1159/000477344 ◽

2017 ◽

Vol 44 (1-2) ◽

pp. 1-11 ◽

Cited By ~ 14

Author(s):

Liliana Ramirez-Gomez ◽

Ling Zheng ◽

Bruce Reed ◽

Joel Kramer ◽

Dan Mungas ◽

...

Keyword(s):

Alzheimer Disease ◽

Vascular Dementia ◽

Neuropsychological Tests ◽

Rating Scale ◽

Word Association ◽

Positive Likelihood Ratio ◽

Operating Characteristics ◽

Clinical Dementia Rating ◽

Or Education ◽

Learning Test

Background/Aims: The aim of this study was to assess the ability of neuropsychological tests to differentiate autopsy-defined Alzheimer disease (AD) from subcortical ischemic vascular dementia (SIVD). Methods: From a sample of 175 cases followed longitudinally that underwent autopsy, we selected 23 normal controls (NC), 20 SIVD, 69 AD, and 10 mixed cases of dementia. Baseline neuropsychological tests, including Memory Assessment Scale word list learning test, control oral word association test, and animal fluency, were compared between the three autopsy-defined groups. Results: The NC, SIVD, and AD groups did not differ by age or education. The SIVD and AD groups did not differ by the Global Clinical Dementia Rating Scale. Subjects with AD performed worse on delayed recall (p < 0.01). A receiver operating characteristics analysis comparing the SIVD and AD groups including age, education, difference between categorical (animals) versus phonemic fluency (letter F), and the first recall from the word learning test distinguished the two groups with a sensitivity of 85%, specificity of 67%, and positive likelihood ratio of 2.57 (AUC = 0.789, 95% CI 0.69-0.88, p < 0.0001). Conclusion: In neuropathologically defined subgroups, neuropsychological profiles have modest ability to distinguish patients with AD from those with SIVD.

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