Metric to quantify white matter damage on brain magnetic resonance images.
Purpose: Quantitative assessment of white matter hyperintensities (WMH) on structural Magnetic Resonance Imaging (MRI) is challenging. It is important to harmonise results from different software tools considering not only the volume but also the signal intensity. Here we propose and evaluate a metr...
| Publicado en: | Neuroradiology Vol. 59; no. 10; pp. 951 - 963 |
|---|---|
| Autores principales: | , , , , , , , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2017
|
| 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=125109660&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 125109660 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Oct2017 vid: 59 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 125109660 125109660 144079841 125109660 10.1007/s00234-017-1892-1 125109660 ppf: 951 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Metric to quantify white matter damage on brain magnetic resonance images. aug: au: Valdés Hernández, Maria Chappell, Francesca Muñoz Maniega, Susana Dickie, David Royle, Natalie Morris, Zoe Anblagan, Devasuda Sakka, Eleni Armitage, Paul Bastin, Mark Deary, Ian Wardlaw, Joanna affil: Department of Cardiovascular Sciences , University of Sheffield , Sheffield UK sug: subj: Brain Diseases Pathology Magnetic Resonance Imaging Methods Cerebrovascular Disorders Stroke Patients Human Aged Quantitative Studies Community Living In Old Age Tissue Array Analysis Spearman's Rank Correlation Coefficient Analysis of Covariance Software Aged: 65+ years ab: Purpose: Quantitative assessment of white matter hyperintensities (WMH) on structural Magnetic Resonance Imaging (MRI) is challenging. It is important to harmonise results from different software tools considering not only the volume but also the signal intensity. Here we propose and evaluate a metric of white matter (WM) damage that addresses this need. Methods: We obtained WMH and normal-appearing white matter (NAWM) volumes from brain structural MRI from community dwelling older individuals and stroke patients enrolled in three different studies, using two automatic methods followed by manual editing by two to four observers blind to each other. We calculated the average intensity values on brain structural fluid-attenuation inversion recovery (FLAIR) MRI for the NAWM and WMH. The white matter damage metric is calculated as the proportion of WMH in brain tissue weighted by the relative image contrast of the WMH-to-NAWM. The new metric was evaluated using tissue microstructure parameters and visual ratings of small vessel disease burden and WMH: Fazekas score for WMH burden and Prins scale for WMH change. Results: The correlation between the WM damage metric and the visual rating scores (Spearman ρ > =0.74, p < 0.0001) was slightly stronger than between the latter and WMH volumes (Spearman ρ > =0.72, p < 0.0001). The repeatability of the WM damage metric was better than WM volume (average median difference between measurements 3.26% (IQR 2.76%) and 5.88% (IQR 5.32%) respectively). The follow-up WM damage was highly related to total Prins score even when adjusted for baseline WM damage (ANCOVA, p < 0.0001), which was not always the case for WMH volume, as total Prins was highly associated with the change in the intense WMH volume ( p = 0.0079, increase of 4.42 ml per unit change in total Prins, 95%CI [1.17 7.67]), but not with the change in less-intense, subtle WMH, which determined the volumetric change. Conclusion: The new metric is practical and simple to calculate. It is robust to variations in image processing methods and scanning protocols, and sensitive to subtle and severe white matter damage. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|