Literature DB >> 27720265

Brain parenchymal fraction in an age-stratified healthy population - determined by MRI using manual segmentation and three automated segmentation methods.

Mattias Vågberg1, Khalid Ambarki2, Thomas Lindqvist3, Richard Birgander3, Anders Svenningsson4.   

Abstract

BACKGROUND AND
PURPOSE: Brain atrophy is a prominent feature in many neurodegenerative diseases, such as multiple sclerosis, but age-related decrease of brain volume occurs regardless of pathological neurodegeneration. Changes in brain volume can be described by use of the brain parenchymal fraction (BPF), most often defined as the ratio of total brain parenchyma to total intracranial space. The BPF is of interest both in research and in clinical practice. To be able to properly interpret this variable, the normal range of BPF must be known. The objective of this study is to present normal values for BPF, stratified by age, and compare manual BPF measurement to three automated methods.
MATERIALS AND METHODS: The BPFs of 106 healthy individuals aged 21 to 85 years were determined by the automated segmentation methods SyMap, VBM8 and SPM12. In a subgroup of 54 randomly selected individuals, the BPF was also determined by manual segmentation.
RESULTS: The median (IQR) BPFs of the whole study population were 0.857 (0.064), 0.819 (0.028) and 0.784 (0.073) determined by SyMap, VBM8 and SPM12, respectively. The BPF decreased with increasing age. The correlation coefficients between manual segmentation and SyMap, VBM8 and SPM12 were 0.93 (P<0.001), 0.77 (P<0.001) and 0.56 (P<0.001), respectively.
CONCLUSIONS: There was a clear relationship between increasing age and decreasing BPF. Knowledge of the range of normal BPF in relation to age group will help in the interpretation of BPF data. The automated segmentation methods displayed varying degrees of similarity to the manual reference, with SyMap being the most similar.
Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  BPF; Brain atrophy; SPM; SyMap; VBM

Mesh:

Year:  2016        PMID: 27720265     DOI: 10.1016/j.neurad.2016.08.002

Source DB:  PubMed          Journal:  J Neuroradiol        ISSN: 0150-9861            Impact factor:   3.447


  9 in total

1.  Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database.

Authors:  Da Ma; Karteek Popuri; Mahadev Bhalla; Oshin Sangha; Donghuan Lu; Jiguo Cao; Claudia Jacova; Lei Wang; Mirza Faisal Beg
Journal:  Hum Brain Mapp       Date:  2018-11-15       Impact factor: 5.038

2.  Brain tissue and myelin volumetric analysis in multiple sclerosis at 3T MRI with various in-plane resolutions using synthetic MRI.

Authors:  Laetitia Saccenti; Christina Andica; Akifumi Hagiwara; Kazumasa Yokoyama; Mariko Yoshida Takemura; Shohei Fujita; Tomoko Maekawa; Koji Kamagata; Alice Le Berre; Masaaki Hori; Nobutaka Hattori; Shigeki Aoki
Journal:  Neuroradiology       Date:  2019-06-18       Impact factor: 2.804

3.  The profile of blunt traumatic infratentorial cranial bleed types.

Authors:  Isaac Ng; Nikolay Bugaev; Ron Riesenburger; Aaron C Shpiner; Janis L Breeze; Sandra S Arabian; Reuven Rabinovici
Journal:  J Clin Neurosci       Date:  2018-10-17       Impact factor: 1.961

Review 4.  Brain Parenchymal Fraction in Healthy Adults-A Systematic Review of the Literature.

Authors:  Mattias Vågberg; Gabriel Granåsen; Anders Svenningsson
Journal:  PLoS One       Date:  2017-01-17       Impact factor: 3.240

Review 5.  SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement.

Authors:  Akifumi Hagiwara; Marcel Warntjes; Masaaki Hori; Christina Andica; Misaki Nakazawa; Kanako Kunishima Kumamaru; Osamu Abe; Shigeki Aoki
Journal:  Invest Radiol       Date:  2017-10       Impact factor: 6.016

6.  Searching for neurodegeneration in multiple sclerosis at clinical onset: Diagnostic value of biomarkers.

Authors:  Lenka Novakova; Markus Axelsson; Clas Malmeström; Henrik Imberg; Olle Elias; Henrik Zetterberg; Olle Nerman; Jan Lycke
Journal:  PLoS One       Date:  2018-04-03       Impact factor: 3.240

7.  Application of Synthetic MRI for Direct Measurement of Magnetic Resonance Relaxation Time and Tumor Volume at Multiple Time Points after Contrast Administration: Preliminary Results in Patients with Brain Metastasis.

Authors:  Koung Mi Kang; Seung Hong Choi; Moonjung Hwang; Roh-Eul Yoo; Tae Jin Yun; Ji-Hoon Kim; Chul-Ho Sohn
Journal:  Korean J Radiol       Date:  2018-06-14       Impact factor: 3.500

Review 8.  Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis-a systematic review.

Authors:  Hugh G Pemberton; Lara A M Zaki; Olivia Goodkin; Ravi K Das; Rebecca M E Steketee; Frederik Barkhof; Meike W Vernooij
Journal:  Neuroradiology       Date:  2021-09-03       Impact factor: 2.804

9.  Age-Related Changes in Relaxation Times, Proton Density, Myelin, and Tissue Volumes in Adult Brain Analyzed by 2-Dimensional Quantitative Synthetic Magnetic Resonance Imaging.

Authors:  Akifumi Hagiwara; Kotaro Fujimoto; Koji Kamagata; Syo Murata; Ryusuke Irie; Hideyoshi Kaga; Yuki Someya; Christina Andica; Shohei Fujita; Shimpei Kato; Issei Fukunaga; Akihiko Wada; Masaaki Hori; Yoshifumi Tamura; Ryuzo Kawamori; Hirotaka Watada; Shigeki Aoki
Journal:  Invest Radiol       Date:  2021-03-01       Impact factor: 10.065

  9 in total

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