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Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease
We aim to estimate brain tissue displacements in the medial temporal lobe (MTL) using backscattered ultrasound radiofrequency (US RF) signals, and to assess the diagnostic ability of brain tissue displacement parameters for the differentiation of patients with Alzheimer’s disease (AD) from healthy c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7399840/ https://www.ncbi.nlm.nih.gov/pubmed/32635379 http://dx.doi.org/10.3390/diagnostics10070452 |
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author | Baranauskas, Mindaugas Jurkonis, Rytis Lukoševičius, Arūnas Makūnaitė, Monika Matijošaitis, Vaidas Gleiznienė, Rymantė Rastenytė, Daiva |
author_facet | Baranauskas, Mindaugas Jurkonis, Rytis Lukoševičius, Arūnas Makūnaitė, Monika Matijošaitis, Vaidas Gleiznienė, Rymantė Rastenytė, Daiva |
author_sort | Baranauskas, Mindaugas |
collection | PubMed |
description | We aim to estimate brain tissue displacements in the medial temporal lobe (MTL) using backscattered ultrasound radiofrequency (US RF) signals, and to assess the diagnostic ability of brain tissue displacement parameters for the differentiation of patients with Alzheimer’s disease (AD) from healthy controls (HC). Standard neuropsychological evaluation and transcranial sonography (TCS) for endogenous brain tissue motion data collection are performed for 20 patients with AD and for 20 age- and sex-matched HC in a prospective manner. Essential modifications of our previous method in US waveform parametrization, raising the confidence of micrometer-range displacement signals in the presence of noise, are done. Four logistic regression models are constructed, and receiver operating characteristic (ROC) curve analyses are applied. All models have cut-offs from 61.0 to 68.5% and separate AD patients from HC with a sensitivity of 89.5% and a specificity of 100%. The area under a ROC curve of predicted probability in all models is excellent (from 95.2 to 95.7%). According to our models, AD patients can be differentiated from HC by a sharper morphology of some individual MTL spatial point displacements (i.e., by spreading the spectrum of displacements to the high-end frequencies with higher variability across spatial points within a region), by lower displacement amplitude differences between adjacent spatial points (i.e., lower strain), and by a higher interaction of these attributes. |
format | Online Article Text |
id | pubmed-7399840 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73998402020-08-17 Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease Baranauskas, Mindaugas Jurkonis, Rytis Lukoševičius, Arūnas Makūnaitė, Monika Matijošaitis, Vaidas Gleiznienė, Rymantė Rastenytė, Daiva Diagnostics (Basel) Article We aim to estimate brain tissue displacements in the medial temporal lobe (MTL) using backscattered ultrasound radiofrequency (US RF) signals, and to assess the diagnostic ability of brain tissue displacement parameters for the differentiation of patients with Alzheimer’s disease (AD) from healthy controls (HC). Standard neuropsychological evaluation and transcranial sonography (TCS) for endogenous brain tissue motion data collection are performed for 20 patients with AD and for 20 age- and sex-matched HC in a prospective manner. Essential modifications of our previous method in US waveform parametrization, raising the confidence of micrometer-range displacement signals in the presence of noise, are done. Four logistic regression models are constructed, and receiver operating characteristic (ROC) curve analyses are applied. All models have cut-offs from 61.0 to 68.5% and separate AD patients from HC with a sensitivity of 89.5% and a specificity of 100%. The area under a ROC curve of predicted probability in all models is excellent (from 95.2 to 95.7%). According to our models, AD patients can be differentiated from HC by a sharper morphology of some individual MTL spatial point displacements (i.e., by spreading the spectrum of displacements to the high-end frequencies with higher variability across spatial points within a region), by lower displacement amplitude differences between adjacent spatial points (i.e., lower strain), and by a higher interaction of these attributes. MDPI 2020-07-03 /pmc/articles/PMC7399840/ /pubmed/32635379 http://dx.doi.org/10.3390/diagnostics10070452 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Baranauskas, Mindaugas Jurkonis, Rytis Lukoševičius, Arūnas Makūnaitė, Monika Matijošaitis, Vaidas Gleiznienė, Rymantė Rastenytė, Daiva Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease |
title | Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease |
title_full | Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease |
title_fullStr | Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease |
title_full_unstemmed | Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease |
title_short | Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease |
title_sort | ultrasonic assessment of the medial temporal lobe tissue displacements in alzheimer’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7399840/ https://www.ncbi.nlm.nih.gov/pubmed/32635379 http://dx.doi.org/10.3390/diagnostics10070452 |
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