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Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline

Alzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and atrophy in the medial temporal lobe (MTL) and subsequent brain regions. Structural magnetic resonance imaging (sMRI) has been widely used in research and clinical care for diagnosis and monitor...

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Autores principales: Kress, Gavin T., Popa, Emily S., Thompson, Paul M., Bookheimer, Susan Y., Thomopoulos, Sophia I., Ching, Christopher R.K., Zheng, Hong, Hirsh, Daniel A., Merrill, David A., Panos, Stella E., Raji, Cyrus A., Siddarth, Prabha, Bramen, Jennifer E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338152/
https://www.ncbi.nlm.nih.gov/pubmed/37421927
http://dx.doi.org/10.1016/j.nicl.2023.103458
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author Kress, Gavin T.
Popa, Emily S.
Thompson, Paul M.
Bookheimer, Susan Y.
Thomopoulos, Sophia I.
Ching, Christopher R.K.
Zheng, Hong
Hirsh, Daniel A.
Merrill, David A.
Panos, Stella E.
Raji, Cyrus A.
Siddarth, Prabha
Bramen, Jennifer E.
author_facet Kress, Gavin T.
Popa, Emily S.
Thompson, Paul M.
Bookheimer, Susan Y.
Thomopoulos, Sophia I.
Ching, Christopher R.K.
Zheng, Hong
Hirsh, Daniel A.
Merrill, David A.
Panos, Stella E.
Raji, Cyrus A.
Siddarth, Prabha
Bramen, Jennifer E.
author_sort Kress, Gavin T.
collection PubMed
description Alzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and atrophy in the medial temporal lobe (MTL) and subsequent brain regions. Structural magnetic resonance imaging (sMRI) has been widely used in research and clinical care for diagnosis and monitoring AD progression. However, atrophy patterns are complex and vary by patient. To address this issue, researchers have made efforts to develop more concise metrics that can summarize AD-specific atrophy. Many of these methods can be difficult to interpret clinically, hampering adoption. In this study, we introduce a novel index which we call an “AD-NeuroScore,” that uses a modified Euclidean-inspired distance function to calculate differences between regional brain volumes associated with cognitive decline. The index is adjusted for intracranial volume (ICV), age, sex, and scanner model. We validated AD-NeuroScore using 929 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, with a mean age of 72.7 years (SD = 6.3; 55.1–91.5) and cognitively normal (CN), mild cognitive impairment (MCI), or AD diagnoses. Our validation results showed that AD-NeuroScore was significantly associated with diagnosis and disease severity scores (measured by MMSE, CDR-SB, and ADAS-11) at baseline. Furthermore, baseline AD-NeuroScore was associated with both changes in diagnosis and disease severity scores at all time points with available data. The performance of AD-NeuroScore was equivalent or superior to adjusted hippocampal volume (AHV), a widely used metric in AD research. Further, AD-NeuroScore typically performed as well as or sometimes better when compared to other existing sMRI-based metrics. In conclusion, we have introduced a new metric, AD-NeuroScore, which shows promising results in detecting AD, benchmarking disease severity, and predicting disease progression. AD-NeuroScore differentiates itself from other metrics by being clinically practical and interpretable.
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spelling pubmed-103381522023-07-13 Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline Kress, Gavin T. Popa, Emily S. Thompson, Paul M. Bookheimer, Susan Y. Thomopoulos, Sophia I. Ching, Christopher R.K. Zheng, Hong Hirsh, Daniel A. Merrill, David A. Panos, Stella E. Raji, Cyrus A. Siddarth, Prabha Bramen, Jennifer E. Neuroimage Clin Regular Article Alzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and atrophy in the medial temporal lobe (MTL) and subsequent brain regions. Structural magnetic resonance imaging (sMRI) has been widely used in research and clinical care for diagnosis and monitoring AD progression. However, atrophy patterns are complex and vary by patient. To address this issue, researchers have made efforts to develop more concise metrics that can summarize AD-specific atrophy. Many of these methods can be difficult to interpret clinically, hampering adoption. In this study, we introduce a novel index which we call an “AD-NeuroScore,” that uses a modified Euclidean-inspired distance function to calculate differences between regional brain volumes associated with cognitive decline. The index is adjusted for intracranial volume (ICV), age, sex, and scanner model. We validated AD-NeuroScore using 929 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, with a mean age of 72.7 years (SD = 6.3; 55.1–91.5) and cognitively normal (CN), mild cognitive impairment (MCI), or AD diagnoses. Our validation results showed that AD-NeuroScore was significantly associated with diagnosis and disease severity scores (measured by MMSE, CDR-SB, and ADAS-11) at baseline. Furthermore, baseline AD-NeuroScore was associated with both changes in diagnosis and disease severity scores at all time points with available data. The performance of AD-NeuroScore was equivalent or superior to adjusted hippocampal volume (AHV), a widely used metric in AD research. Further, AD-NeuroScore typically performed as well as or sometimes better when compared to other existing sMRI-based metrics. In conclusion, we have introduced a new metric, AD-NeuroScore, which shows promising results in detecting AD, benchmarking disease severity, and predicting disease progression. AD-NeuroScore differentiates itself from other metrics by being clinically practical and interpretable. Elsevier 2023-06-26 /pmc/articles/PMC10338152/ /pubmed/37421927 http://dx.doi.org/10.1016/j.nicl.2023.103458 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Kress, Gavin T.
Popa, Emily S.
Thompson, Paul M.
Bookheimer, Susan Y.
Thomopoulos, Sophia I.
Ching, Christopher R.K.
Zheng, Hong
Hirsh, Daniel A.
Merrill, David A.
Panos, Stella E.
Raji, Cyrus A.
Siddarth, Prabha
Bramen, Jennifer E.
Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline
title Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline
title_full Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline
title_fullStr Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline
title_full_unstemmed Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline
title_short Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline
title_sort preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338152/
https://www.ncbi.nlm.nih.gov/pubmed/37421927
http://dx.doi.org/10.1016/j.nicl.2023.103458
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