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An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease
BACKGROUND: The differential diagnosis of frontotemporal dementia (FTD) and Alzheimer’s disease (AD) is difficult due to the overlaps of clinical symptoms. Structural magnetic resonance imaging (sMRI) presents distinct brain atrophy and potentially helps in their differentiation. In this study, we a...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805212/ https://www.ncbi.nlm.nih.gov/pubmed/33436059 http://dx.doi.org/10.1186/s13195-020-00757-5 |
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author | Yu, Qun Mai, Yingren Ruan, Yuting Luo, Yishan Zhao, Lei Fang, Wenli Cao, Zhiyu Li, Yi Liao, Wang Xiao, Songhua Mok, Vincent C. T. Shi, Lin Liu, Jun |
author_facet | Yu, Qun Mai, Yingren Ruan, Yuting Luo, Yishan Zhao, Lei Fang, Wenli Cao, Zhiyu Li, Yi Liao, Wang Xiao, Songhua Mok, Vincent C. T. Shi, Lin Liu, Jun |
author_sort | Yu, Qun |
collection | PubMed |
description | BACKGROUND: The differential diagnosis of frontotemporal dementia (FTD) and Alzheimer’s disease (AD) is difficult due to the overlaps of clinical symptoms. Structural magnetic resonance imaging (sMRI) presents distinct brain atrophy and potentially helps in their differentiation. In this study, we aim at deriving a novel integrated index by leveraging the volumetric measures in brain regions with significant difference between AD and FTD and developing an MRI-based strategy for the differentiation of FTD and AD. METHODS: In this study, the data were acquired from three different databases, including 47 subjects with FTD, 47 subjects with AD, and 47 normal controls in the NACC database; 50 subjects with AD in the ADNI database; and 50 subjects with FTD in the FTLDNI database. The MR images of all subjects were automatically segmented, and the brain atrophy, including the AD resemblance atrophy index (AD-RAI), was quantified using AccuBrain®. A novel MRI index, named the frontotemporal dementia index (FTDI), was derived as the ratio between the weighted sum of the volumetric indexes in “FTD dominant” structures over that obtained from “AD dominant” structures. The weights and the identification of “FTD/AD dominant” structures were acquired from the statistical analysis of NACC data. The differentiation performance of FTDI was validated using independent data from ADNI and FTLDNI databases. RESULTS: AD-RAI is a proven imaging biomarker to identify AD and FTD from NC with significantly higher values (p < 0.001 and AUC = 0.88) as we reported before, while no significant difference was found between AD and FTD (p = 0.647). FTDI showed excellent accuracy in identifying FTD from AD (AUC = 0.90; SEN = 89%, SPE = 75% with threshold value = 1.08). The validation using independent data from ADNI and FTLDNI datasets also confirmed the efficacy of FTDI (AUC = 0.93; SEN = 96%, SPE = 70% with threshold value = 1.08). CONCLUSIONS: Brain atrophy in AD, FTD, and normal elderly shows distinct patterns. In addition to AD-RAI that is designed to detect abnormal brain atrophy in dementia, a novel index specific to FTD is proposed and validated. By combining AD-RAI and FTDI, an MRI-based decision strategy was further proposed as a promising solution for the differential diagnosis of AD and FTD in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-020-00757-5. |
format | Online Article Text |
id | pubmed-7805212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78052122021-01-14 An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease Yu, Qun Mai, Yingren Ruan, Yuting Luo, Yishan Zhao, Lei Fang, Wenli Cao, Zhiyu Li, Yi Liao, Wang Xiao, Songhua Mok, Vincent C. T. Shi, Lin Liu, Jun Alzheimers Res Ther Research BACKGROUND: The differential diagnosis of frontotemporal dementia (FTD) and Alzheimer’s disease (AD) is difficult due to the overlaps of clinical symptoms. Structural magnetic resonance imaging (sMRI) presents distinct brain atrophy and potentially helps in their differentiation. In this study, we aim at deriving a novel integrated index by leveraging the volumetric measures in brain regions with significant difference between AD and FTD and developing an MRI-based strategy for the differentiation of FTD and AD. METHODS: In this study, the data were acquired from three different databases, including 47 subjects with FTD, 47 subjects with AD, and 47 normal controls in the NACC database; 50 subjects with AD in the ADNI database; and 50 subjects with FTD in the FTLDNI database. The MR images of all subjects were automatically segmented, and the brain atrophy, including the AD resemblance atrophy index (AD-RAI), was quantified using AccuBrain®. A novel MRI index, named the frontotemporal dementia index (FTDI), was derived as the ratio between the weighted sum of the volumetric indexes in “FTD dominant” structures over that obtained from “AD dominant” structures. The weights and the identification of “FTD/AD dominant” structures were acquired from the statistical analysis of NACC data. The differentiation performance of FTDI was validated using independent data from ADNI and FTLDNI databases. RESULTS: AD-RAI is a proven imaging biomarker to identify AD and FTD from NC with significantly higher values (p < 0.001 and AUC = 0.88) as we reported before, while no significant difference was found between AD and FTD (p = 0.647). FTDI showed excellent accuracy in identifying FTD from AD (AUC = 0.90; SEN = 89%, SPE = 75% with threshold value = 1.08). The validation using independent data from ADNI and FTLDNI datasets also confirmed the efficacy of FTDI (AUC = 0.93; SEN = 96%, SPE = 70% with threshold value = 1.08). CONCLUSIONS: Brain atrophy in AD, FTD, and normal elderly shows distinct patterns. In addition to AD-RAI that is designed to detect abnormal brain atrophy in dementia, a novel index specific to FTD is proposed and validated. By combining AD-RAI and FTDI, an MRI-based decision strategy was further proposed as a promising solution for the differential diagnosis of AD and FTD in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-020-00757-5. BioMed Central 2021-01-12 /pmc/articles/PMC7805212/ /pubmed/33436059 http://dx.doi.org/10.1186/s13195-020-00757-5 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Yu, Qun Mai, Yingren Ruan, Yuting Luo, Yishan Zhao, Lei Fang, Wenli Cao, Zhiyu Li, Yi Liao, Wang Xiao, Songhua Mok, Vincent C. T. Shi, Lin Liu, Jun An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease |
title | An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease |
title_full | An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease |
title_fullStr | An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease |
title_full_unstemmed | An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease |
title_short | An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease |
title_sort | mri-based strategy for differentiation of frontotemporal dementia and alzheimer’s disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805212/ https://www.ncbi.nlm.nih.gov/pubmed/33436059 http://dx.doi.org/10.1186/s13195-020-00757-5 |
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