Estimation of intracranial volume: A comparative study between synthetic MRI and FSL-brain extraction tool (BET)2.


Journal

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
ISSN: 1532-2653
Titre abrégé: J Clin Neurosci
Pays: Scotland
ID NLM: 9433352

Informations de publication

Date de publication:
Sep 2020
Historique:
received: 28 04 2020
revised: 07 07 2020
accepted: 09 07 2020
entrez: 19 10 2020
pubmed: 20 10 2020
medline: 12 1 2021
Statut: ppublish

Résumé

Brain extraction represents an important step in numerous neuroimaging analyses. The brain extraction tool (BET)2 is a widely used deformable model-based approach for extraction of intracranial volume (ICV). The aim of this study is to estimate the ICV extraction accuracy using synthetic MR(SyMRI) method and BET2 in healthy adult participants and patients with Sturge-Weber Syndrome (SWS), including infants. 'Quantification of relaxation times and proton density by multi-echo acquisition of saturation recovery with turbo-spin-echo readout' (QRAPMASTER) with a 3.0 T magnetic resonance image (MRI) system was used for data acquisition. Statistical evaluations were performed with linear regression analysis and the Jaccard similarity coefficient (J). ICV extraction accuracy with synthetic MR method is found to be higher than BET2, for both aged healthy participants and SWS.

Identifiants

pubmed: 33070892
pii: S0967-5868(20)31362-X
doi: 10.1016/j.jocn.2020.07.024
pii:
doi:

Types de publication

Comparative Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

178-182

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Masami Goto (M)

Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1 hongo, bunkyo-ku, Tokyo 113-8421, Japan. Electronic address: m.goto.ql@juntendo.ac.jp.

Akifumi Hagiwara (A)

Department of Radiology, Juntendo University School of Medicine, Japan.

Ayumi Kato (A)

Department of Radiology, Juntendo University School of Medicine, Japan; Division of Radiology, Department of Pathophysiological and Therapeutic Science, Faculty of Medicine, Tottori University, Japan.

Shohei Fujita (S)

Department of Radiology, Juntendo University School of Medicine, Japan; Department of Radiology, Graduate School of Medicine, The University of Tokyo, Japan.

Masaaki Hori (M)

Department of Radiology, Juntendo University School of Medicine, Japan; Department of Radiology, Toho University Omori Medical Center, Japan.

Koji Kamagata (K)

Department of Radiology, Juntendo University School of Medicine, Japan.

Hidenori Sugano (H)

Department of Neurosurgery, Juntendo University School of Medicine, Japan.

Hajime Arai (H)

Department of Neurosurgery, Juntendo University School of Medicine, Japan.

Shigeki Aoki (S)

Department of Radiology, Juntendo University School of Medicine, Japan.

Osamu Abe (O)

Department of Radiology, Graduate School of Medicine, The University of Tokyo, Japan.

Hajime Sakamoto (H)

Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1 hongo, bunkyo-ku, Tokyo 113-8421, Japan.

Yasuaki Sakano (Y)

Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1 hongo, bunkyo-ku, Tokyo 113-8421, Japan.

Shinsuke Kyogoku (S)

Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1 hongo, bunkyo-ku, Tokyo 113-8421, Japan.

Hiroyuki Daida (H)

Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1 hongo, bunkyo-ku, Tokyo 113-8421, Japan.

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Classifications MeSH