Clinical trial NCT04041895: Detecting Probable Alzheimer's Disease From Speech Using Linguistical Analysis
Official title: Detecting Mild Cognitive Impairment and Probable Alzheimer's Disease From Speech Using Linguistic Deficits With Amyloid PET Imaging as a Baseline.
Study type: OBSERVATIONAL
Overall status: WITHDRAWN
Conditions: Alzheimer Disease
Dementia
Keywords: Alzheimer's Disease
Dementia
Linguistics
Lead sponsor: East Tennessee State University
Sponsor class: OTHER
First posted: 2019-08-01
Enrollment: 0
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Participants would have undertaken an Amyloid PET scan to confirm the presence or absence of Amyloid plaques in the brain through a previously approved study on Alzheimer's disease with Amyloid PET imaging or at the request of their physician to determine possible cause of suspected cognitive decline.

Brief summary: The object of this study is to investigate the use of linguistic deficits from speech samples for the early detection of Mild Cognitive Impairment and probable Alzheimer's disease. It will also evaluate whether the result of the Amyloid PET scan would confirm the effectiveness of a less expensive and less intrusive diagnostic technique through speech

Detailed description: This study will investigate the use of linguistic deficits through a computational diagnostic model for the prediction of Mild Cognitive Impairment (MCI) and Probable Alzheimer's disease (PrAD) from speech samples (verbal utterances). The premise is that MCI and PrAD are characterized by the deterioration of nerve cells that control cognitive speech and language processes, which consequently affects how patients compose verbal utterances. As the Amyloid Positron Emission Tomography (PET) scan is making advances in giving confirmatory evidence of the existence of plaques in the brain, there is the opportunity to investigate whether the result of the scan would confirm the effectiveness of a less expensive and less intrusive diagnostic technique. In this study, participants of a previous IRB approved study on Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) who consent to participate in the new study will be requested to perform a basic descriptive task. The main task to be done by the participants is to verbally describe the scenes on a projected image, while their verbal utterances will be recorded via an audio recorder. The descriptive task is expected to take between 10 to 15 minutes on average. Participants will be required to describe the scenes on the projected Cookie-Theft image (http://www.amyspeechlanguagetherapy.com/thecookie- theft-picture.html). The image is part of the Provide a brief but thorough description of the study. What is the study about? This does not need to contain a summary of background literature. It should just summarize the study itself. Boston Diagnostic Aphasia Examination (BDAE-3) and it is adapted in our study for the purpose of capturing the complexity in the linguistic expression similar to the DementiaBank project (https://talkbank.org/media/DementiaBank/Pitt/cookie/). Note that we are NOT conducting any psychological examination using the BDAE-3, we have only referenced the source of the Cookie-Theft image, which is publicly available for research and has been used for decades. An example of the task is demonstrated in this video: https://www.youtube.com/watch?v=1NB8wBBguMg. The transcripts of the recorded interview will be analyzed by our proposed computational model to detect the presence of Mild Cognitive Impairment or probable Alzheimer's disease. Finally, the IDEAS study PET scan data would be used in conjunction with the transcripts of the recorded interview to compare the results of the linguistic analysis of the transcript with those of the PET scan in making Mild Cognitive Impairment or probable Alzheimer's Disease diagnoses.

Eligibility criteria: Inclusion Criteria:

* Participants who have undergone the Mini Mental State Examination (MMSE).
* Participants who have undergone Amyloid PET scan with a diagnosis of having the Amyloid plaques or not.
* Participants with moderate or fluent English speaking ability.

Exclusion Criteria:

* Participants who cannot speak as the data collection process needs to obtain speech samples.
* Participants who are severely demented or at a very late stage of Alzheimer's disease.
* Participants with stroke.
* Participants who report a history of other neurodegenerative disorders than MCI and AD.
* Participants with chronic vision impairment or who cannot see with the aid of corrective glasses.
* Participants who cannot speak English.
* A participant who have been diagnosed with HIV/AIDS as this may have a cognitive effect on its own.

Primary outcomes:
measure: Analysis of speech audio recording describing the "Cookie-Thief Image" using proposed computational model designed by PI for determination of Alzheimer's disease
timeFrame: through study completion, an average of 1 year
Secondary outcomes:
measure: MMSE
timeFrame: through study completion, an average of 1 year
Other outcomes:
Locations:
city: Johnson City
country: United States
facility: East Tennessee State University
state: Tennessee
Study officials:
affiliation: East Tennessee State University
name: Sylvester O Orimaye, PhD, MPH
role: PRINCIPAL_INVESTIGATOR
References:
citation: Orimaye, S. O., Wong, J. S. M., & Golden, K. J. (2014, June). Learning predictive linguistic features for Alzheimer's disease and related dementias using verbal utterances. In Proceedings of the 1st Workshop on Computational Linguistics and Clinical Psychology (CLPsych) (pp. 78-87). sn.
citation: Orimaye SO, Wong JS, Golden KJ, Wong CP, Soyiri IN. Predicting probable Alzheimer's disease using linguistic deficits and biomarkers. BMC Bioinformatics. 2017 Jan 14;18(1):34. doi: 10.1186/s12859-016-1456-0.
citation: Roark B, Mitchell M, Hosom JP, Hollingshead K, Kaye J. Spoken Language Derived Measures for Detecting Mild Cognitive Impairment. IEEE Trans Audio Speech Lang Process. 2011 Sep 1;19(7):2081-2090. doi: 10.1109/TASL.2011.2112351.
citation: Fraser KC, Meltzer JA, Graham NL, Leonard C, Hirst G, Black SE, Rochon E. Automated classification of primary progressive aphasia subtypes from narrative speech transcripts. Cortex. 2014 Jun;55:43-60. doi: 10.1016/j.cortex.2012.12.006. Epub 2012 Dec 21.
citation: Prud'hommeaux E, Roark B. Graph-Based Word Alignment for Clinical Language Evaluation. Comput Linguist Assoc Comput Linguist. 2015 Dec;41(4):549-578. doi: 10.1162/coli_a_00232. Epub 2015 Dec 1.
citation: Verma M, Howard RJ. Semantic memory and language dysfunction in early Alzheimer's disease: a review. Int J Geriatr Psychiatry. 2012 Dec;27(12):1209-17. doi: 10.1002/gps.3766. Epub 2012 Feb 1.
citation: Reilly J, Rodriguez AD, Lamy M, Neils-Strunjas J. Cognition, language, and clinical pathological features of non-Alzheimer's dementias: an overview. J Commun Disord. 2010 Sep-Oct;43(5):438-52. doi: 10.1016/j.jcomdis.2010.04.011. Epub 2010 May 6.
citation: Klimova B, Maresova P, Valis M, Hort J, Kuca K. Alzheimer's disease and language impairments: social intervention and medical treatment. Clin Interv Aging. 2015 Aug 27;10:1401-7. doi: 10.2147/CIA.S89714. eCollection 2015.
citation: Fraser KC, Meltzer JA, Rudzicz F. Linguistic Features Identify Alzheimer's Disease in Narrative Speech. J Alzheimers Dis. 2016;49(2):407-22. doi: 10.3233/JAD-150520.
citation: 10. Lunsford, R., & Heeman, P. A. (2015, September). Using linguistic indicators of difficulty to identify mild cognitive impairment. In INTERSPEECH (pp. 658-662).