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Volumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia.
Bermudez, Camilo; Kerley, Cailey I; Ramadass, Karthik; Farber-Eger, Eric H; Lin, Ya-Chen; Kang, Hakmook; Taylor, Warren D; Wells, Quinn S; Landman, Bennett A.
Afiliação
  • Bermudez C; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
  • Kerley CI; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
  • Ramadass K; Department of Computer Science, Vanderbilt University, Nashville, TN, USA.
  • Farber-Eger EH; Department of Cardiology, Vanderbilt University School of Medicine, Nashville, TN, USA.
  • Lin YC; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Kang H; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Taylor WD; Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Wells QS; Department of Cardiology, Vanderbilt University School of Medicine, Nashville, TN, USA.
  • Landman BA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Psychiatry, Vanderbilt University Me
Magn Reson Imaging ; 109: 49-55, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38430976
ABSTRACT
Heart failure with preserved ejection fraction (HFpEF) is an important, emerging risk factor for dementia, but it is not clear whether HFpEF contributes to a specific pattern of neuroanatomical changes in dementia. A major challenge to studying this is the relative paucity of datasets of patients with dementia, with/without HFpEF, and relevant neuroimaging. We sought to demonstrate the feasibility of using modern data mining tools to create and analyze clinical imaging datasets and identify the neuroanatomical signature of HFpEF-associated dementia. We leveraged the bioinformatics tools at Vanderbilt University Medical Center to identify patients with a diagnosis of dementia with and without comorbid HFpEF using the electronic health record. We identified high resolution, clinically-acquired neuroimaging data on 30 dementia patients with HFpEF (age 76.9 ± 8.12 years, 61% female) as well as 301 age- and sex-matched patients with dementia but without HFpEF to serve as comparators (age 76.2 ± 8.52 years, 60% female). We used automated image processing pipelines to parcellate the brain into 132 structures and quantify their volume. We found six regions with significant atrophy associated with HFpEF accumbens area, amygdala, posterior insula, anterior orbital gyrus, angular gyrus, and cerebellar white matter. There were no regions with atrophy inversely associated with HFpEF. Patients with dementia and HFpEF have a distinct neuroimaging signature compared to patients with dementia only. Five of the six regions identified in are in the temporo-parietal region of the brain. Future studies should investigate mechanisms of injury associated with cerebrovascular disease leading to subsequent brain atrophy.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Demência / Insuficiência Cardíaca Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Demência / Insuficiência Cardíaca Idioma: En Ano de publicação: 2024 Tipo de documento: Article