Automated High-Definition MRI Processing Routine Robustly Detects Longitudinal Morphometry Changes in Alzheimer's Disease Patients.
Longitudinal MRI studies are of increasing importance to document the time course of neurodegenerative diseases as well as neuroprotective effects of a drug candidate in clinical trials. However, manual longitudinal image assessments are time consuming and conventional assessment routines often deli...
| Publicado en: | Frontiers in Aging Neuroscience Vol. 14; pp. 1 - 17 |
|---|---|
| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Frontiers Media S.A.
6/7/2022
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157324782&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157324782 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16634365 BG2U jtl: Frontiers in Aging Neuroscience issn: 16634365 maglogo: N pubinfo: dt: 6/7/2022 vid: 14 pid: 40038 pub: Frontiers Media S.A. artinfo: ui: 157324782 157324782 157324782 10.3389/fnagi.2022.832828 157324782 ppf: 1 ppct: 16 formats: tig: atl: Automated High-Definition MRI Processing Routine Robustly Detects Longitudinal Morphometry Changes in Alzheimer's Disease Patients. aug: au: Rechberger, Simon Li, Yong Kopetzky, Sebastian J. Butz-Ostendorf, Markus affil: Viscovery Software GmbH, Vienna, Austria sug: subj: Alzheimer's Disease Physiopathology Magnetic Resonance Imaging Methods Image Processing, Computer Assisted Methods Automation Brain Anatomy and Histology Human Male Female Middle Age Aged Aged, 80 and Over Neuroradiography Alzheimer's Disease Diagnosis Scales Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: Longitudinal MRI studies are of increasing importance to document the time course of neurodegenerative diseases as well as neuroprotective effects of a drug candidate in clinical trials. However, manual longitudinal image assessments are time consuming and conventional assessment routines often deliver unsatisfying study outcomes. Here, we propose a profound analysis pipeline that consists of the following coordinated steps: (1) an automated and highly precise image processing stream including voxel and surface based morphometry using latest highly detailed brain atlases such as the HCP MMP 1.0 atlas with 360 cortical ROIs; (2) a profound statistical assessment using a multiplicative model of annual percent change (APC); and (3) a multiple testing correction adopted from genome-wide association studies that is optimally suited for longitudinal neuroimaging studies. We tested this analysis pipeline with 25 Alzheimer's disease patients against 25 age-matched cognitively normal subjects with a baseline and a 1-year follow-up conventional MRI scan from the ADNI-3 study. Even in this small cohort, we were able to report 22 significant measurements after multiple testing correction from SBM (including cortical volume, area and thickness) complementing only three statistically significant volume changes (left/right hippocampus and left amygdala) found by VBM. A 1-year decrease in brain morphometry coincided with an increasing clinical disability and cognitive decline in patients measured by MMSE, CDR GLOBAL, FAQ TOTAL and NPI TOTAL scores. This work shows that highly precise image assessments, APC computation and an adequate multiple testing correction can produce a significant study outcome even for small study sizes. With this, automated MRI processing is now available and reliable for routine use and clinical trials. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|