Automatic estimation of brain parenchymal fraction in patients with multple sclerosis: a comparison between synthetic MRI and an established automated brain segmentation software based on FSL.
Purpose: We aimed to validate the estimation of the brain parenchymal fraction (BPF) in patients with multiple sclerosis (MS) using synthetic magnetic resonance imaging (SyMRI) by comparison with software tools of the FMRIB Software Library (FSL). In addition to a cross-sectional method comparison,...
| Publicado en: | Neuroradiology Vol. 66; no. 2; pp. 193 - 206 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Feb2024
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| 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=174971231&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 174971231 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Feb2024 vid: 66 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 174971231 174285375 174971231 174971231 10.1007/s00234-023-03264-0 174971231 ppf: 193 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automatic estimation of brain parenchymal fraction in patients with multple sclerosis: a comparison between synthetic MRI and an established automated brain segmentation software based on FSL. aug: au: Yazici, Ilyas Krieger, Britta Bellenberg, Barbara Ladopoulos, Theodoros Gold, Ralf Schneider, Ruth Lukas, Carsten affil: Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstrasse 56, 44791, Bochum, Germany sug: subj: Multiple Sclerosis Diagnosis Atrophy Pathology Brain Pathology Brain Diseases Diagnosis Magnetic Resonance Imaging Methods Software Methods Human Prospective Studies Cross Sectional Studies Descriptive Statistics Confidence Intervals Funding Source Male Female Middle Age Middle Aged: 45-64 years Male Female ab: Purpose: We aimed to validate the estimation of the brain parenchymal fraction (BPF) in patients with multiple sclerosis (MS) using synthetic magnetic resonance imaging (SyMRI) by comparison with software tools of the FMRIB Software Library (FSL). In addition to a cross-sectional method comparison, longitudinal volume changes were assessed to further elucidate the suitability of SyMRI for quantification of disease-specific changes. Methods: MRI data from 216 patients with MS and 28 control participants were included for volume estimation by SyMRI and FSL-SIENAX. Moreover, longitudinal data from 35 patients with MS were used to compare registration-based percentage brain volume changes estimated using FSL-SIENA to difference-based calculations of volume changes using SyMRI. Results: We observed strong correlations of estimated brain volumes between the two methods. While SyMRI overestimated grey matter and BPF compared to FSL-SIENAX, indicating a systematic bias, there was excellent agreement according to intra-class correlation coefficients for grey matter and good agreement for BPF and white matter. Bland–Altman plots suggested that the inter-method differences in BPF were smaller in patients with brain atrophy compared to those without atrophy. Longitudinal analyses revealed a tendency for higher atrophy rates for SyMRI than for SIENA, but SyMRI had a robust correlation and a good agreement with SIENA. Conclusion: In summary, BPF based on data from SyMRI and FSL-SIENAX is not directly transferable because an overestimation and higher variability of SyMRI values were observed. However, the consistency and correlations between the two methods were satisfactory, and SyMRI was suitable to quantify disease-specific atrophy in MS. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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