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Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline

Ventricular volume (VV) is a widely used structural magnetic resonance imaging (MRI) biomarker in Alzheimer’s disease (AD) research. Abnormal enlargements of VV can be detected before clinically significant memory decline. However, VV does not pinpoint the details of subregional ventricular expansio...

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Autores principales: Dong, Qunxi, Zhang, Wen, Stonnington, Cynthia M., Wu, Jianfeng, Gutman, Boris A., Chen, Kewei, Su, Yi, Baxter, Leslie C., Thompson, Paul M., Reiman, Eric M., Caselli, Richard J., Wang, Yalin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371915/
https://www.ncbi.nlm.nih.gov/pubmed/32683323
http://dx.doi.org/10.1016/j.nicl.2020.102338
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author Dong, Qunxi
Zhang, Wen
Stonnington, Cynthia M.
Wu, Jianfeng
Gutman, Boris A.
Chen, Kewei
Su, Yi
Baxter, Leslie C.
Thompson, Paul M.
Reiman, Eric M.
Caselli, Richard J.
Wang, Yalin
author_facet Dong, Qunxi
Zhang, Wen
Stonnington, Cynthia M.
Wu, Jianfeng
Gutman, Boris A.
Chen, Kewei
Su, Yi
Baxter, Leslie C.
Thompson, Paul M.
Reiman, Eric M.
Caselli, Richard J.
Wang, Yalin
author_sort Dong, Qunxi
collection PubMed
description Ventricular volume (VV) is a widely used structural magnetic resonance imaging (MRI) biomarker in Alzheimer’s disease (AD) research. Abnormal enlargements of VV can be detected before clinically significant memory decline. However, VV does not pinpoint the details of subregional ventricular expansions. Here we introduce a ventricular morphometry analysis system (VMAS) that generates a whole connected 3D ventricular shape model and encodes a great deal of ventricular surface deformation information that is inaccessible by VV. VMAS contains an automated segmentation approach and surface-based multivariate morphometry statistics. We applied VMAS to two independent datasets of cognitively unimpaired (CU) groups. To our knowledge, it is the first work to detect ventricular abnormalities that distinguish normal aging subjects from those who imminently progress to clinically significant memory decline. Significant bilateral ventricular morphometric differences were first shown in 38 members of the Arizona APOE cohort, which included 18 CU participants subsequently progressing to the clinically significant memory decline within 2 years after baseline visits (progressors), and 20 matched CU participants with at least 4 years of post-baseline cognitive stability (non-progressors). VMAS also detected significant differences in bilateral ventricular morphometry in 44 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects (18 CU progressors vs. 26 CU non-progressors) with the same inclusion criterion. Experimental results demonstrated that the ventricular anterior horn regions were affected bilaterally in CU progressors, and more so on the left. VMAS may track disease progression at subregional levels and measure the effects of pharmacological intervention at a preclinical stage.
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spelling pubmed-73719152020-07-23 Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline Dong, Qunxi Zhang, Wen Stonnington, Cynthia M. Wu, Jianfeng Gutman, Boris A. Chen, Kewei Su, Yi Baxter, Leslie C. Thompson, Paul M. Reiman, Eric M. Caselli, Richard J. Wang, Yalin Neuroimage Clin Regular Article Ventricular volume (VV) is a widely used structural magnetic resonance imaging (MRI) biomarker in Alzheimer’s disease (AD) research. Abnormal enlargements of VV can be detected before clinically significant memory decline. However, VV does not pinpoint the details of subregional ventricular expansions. Here we introduce a ventricular morphometry analysis system (VMAS) that generates a whole connected 3D ventricular shape model and encodes a great deal of ventricular surface deformation information that is inaccessible by VV. VMAS contains an automated segmentation approach and surface-based multivariate morphometry statistics. We applied VMAS to two independent datasets of cognitively unimpaired (CU) groups. To our knowledge, it is the first work to detect ventricular abnormalities that distinguish normal aging subjects from those who imminently progress to clinically significant memory decline. Significant bilateral ventricular morphometric differences were first shown in 38 members of the Arizona APOE cohort, which included 18 CU participants subsequently progressing to the clinically significant memory decline within 2 years after baseline visits (progressors), and 20 matched CU participants with at least 4 years of post-baseline cognitive stability (non-progressors). VMAS also detected significant differences in bilateral ventricular morphometry in 44 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects (18 CU progressors vs. 26 CU non-progressors) with the same inclusion criterion. Experimental results demonstrated that the ventricular anterior horn regions were affected bilaterally in CU progressors, and more so on the left. VMAS may track disease progression at subregional levels and measure the effects of pharmacological intervention at a preclinical stage. Elsevier 2020-07-05 /pmc/articles/PMC7371915/ /pubmed/32683323 http://dx.doi.org/10.1016/j.nicl.2020.102338 Text en © 2020 The Authors http://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
Dong, Qunxi
Zhang, Wen
Stonnington, Cynthia M.
Wu, Jianfeng
Gutman, Boris A.
Chen, Kewei
Su, Yi
Baxter, Leslie C.
Thompson, Paul M.
Reiman, Eric M.
Caselli, Richard J.
Wang, Yalin
Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline
title Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline
title_full Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline
title_fullStr Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline
title_full_unstemmed Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline
title_short Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline
title_sort applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371915/
https://www.ncbi.nlm.nih.gov/pubmed/32683323
http://dx.doi.org/10.1016/j.nicl.2020.102338
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