Ahmed A Bahrani1, Charles D Smith2, Justin M Barber3, Omar M Al-Janabi3, David K Powell4, Anders H Andersen4, Brandon D Ramey3, Erin L Abner5, Larry B Goldstein6, Zachary Winder7, Brian T Gold8, Linda Van Eldik3, Donna M Wilcock8, Gregory A Jicha9. 1. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA; Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506, USA; Biomedical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq. 2. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA; Magnetic Resonance Imaging and Spectroscopy Center (MRISC), University of Kentucky, Lexington, KY 40506, USA; Departments of Neurology, University of Kentucky, Lexington, KY 40506, USA. 3. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA. 4. Magnetic Resonance Imaging and Spectroscopy Center (MRISC), University of Kentucky, Lexington, KY 40506, USA. 5. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA; Department of Epidemiology, University of Kentucky, Lexington, KY 40506, USA; Department of Biostatistics, University of Kentucky, Lexington, KY 40506, USA. 6. Departments of Neurology, University of Kentucky, Lexington, KY 40506, USA. 7. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA; Department of Physiology, University of Kentucky, Lexington, KY 40506, USA. 8. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA; Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536, USA. 9. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA; Departments of Neurology, University of Kentucky, Lexington, KY 40506, USA; Departments of Behavioral Science, University of Kentucky, Lexington, KY 40536, USA. Electronic address: gregory.jicha@uky.edu.
Abstract
BACKGROUND: White matter hyperintensities (WMH), associated with both dementia risk and progression, can individually progress, remain stable, or even regress influencing cognitive decline related to specific cerebrovascular-risks. This study details the development and validation of a registration protocol to assess regional, within-subject, longitudinal WMH changes (ΔWMH) that is currently lacking in the field. NEW METHOD: 3D-FLAIR images (baseline and one-year-visit) were used for protocol development and validation. The method was validated by assessing the correlation between forward and reverse longitudinal registration, and between summated regional progression-regression volumes and Global ΔWMH. The clinical relevance of growth-regression ΔWMH were explored in relation to an executive function test. RESULTS: MRI scans for 79 participants (73.5 ± 8.8 years) were used in this study. Global ΔWMH vs. summated regional progression-regression volumes were highly associated (r2 = 0.90; p-value < 0.001). Bi-directional registration validated the registration method (r2 = 0.999; p-value < 0.001). Growth and regression, but not overall ΔWMH, were associated with one-year declines in performance on Trial-Making-Test-B. COMPARISON WITH EXISTING METHOD(S): This method presents a unique registration protocol for maximum tissue alignment, demonstrating three distinct patterns of longitudinal within-subject ΔWMH (stable, growth and regression). CONCLUSIONS: These data detail the development and validation of a registration protocol for use in assessing within-subject, voxel-level alterations in WMH volume. The methods developed for registration and intensity correction of longitudinal within-subject FLAIR images allow regional and within-lesion characterization of longitudinal ΔWMH. Assessing the impact of associated cerebrovascular-risks and longitudinal clinical changes in relation to dynamic regional ΔWMH is needed in future studies.
BACKGROUND: White matter hyperintensities (WMH), associated with both dementia risk and progression, can individually progress, remain stable, or even regress influencing cognitive decline related to specific cerebrovascular-risks. This study details the development and validation of a registration protocol to assess regional, within-subject, longitudinal WMH changes (ΔWMH) that is currently lacking in the field. NEW METHOD: 3D-FLAIR images (baseline and one-year-visit) were used for protocol development and validation. The method was validated by assessing the correlation between forward and reverse longitudinal registration, and between summated regional progression-regression volumes and Global ΔWMH. The clinical relevance of growth-regression ΔWMH were explored in relation to an executive function test. RESULTS: MRI scans for 79 participants (73.5 ± 8.8 years) were used in this study. Global ΔWMH vs. summated regional progression-regression volumes were highly associated (r2 = 0.90; p-value < 0.001). Bi-directional registration validated the registration method (r2 = 0.999; p-value < 0.001). Growth and regression, but not overall ΔWMH, were associated with one-year declines in performance on Trial-Making-Test-B. COMPARISON WITH EXISTING METHOD(S): This method presents a unique registration protocol for maximum tissue alignment, demonstrating three distinct patterns of longitudinal within-subject ΔWMH (stable, growth and regression). CONCLUSIONS: These data detail the development and validation of a registration protocol for use in assessing within-subject, voxel-level alterations in WMH volume. The methods developed for registration and intensity correction of longitudinal within-subject FLAIR images allow regional and within-lesion characterization of longitudinal ΔWMH. Assessing the impact of associated cerebrovascular-risks and longitudinal clinical changes in relation to dynamic regional ΔWMH is needed in future studies.
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