3D quantitative synthetic MRI-derived cortical thickness and subcortical brain volumes: Scan-rescan repeatability and comparison with conventional T
Journal
Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850
Informations de publication
Date de publication:
12 2019
12 2019
Historique:
received:
13
09
2018
revised:
25
03
2019
accepted:
26
03
2019
pubmed:
11
4
2019
medline:
11
11
2020
entrez:
11
4
2019
Statut:
ppublish
Résumé
Previous quantitative synthetic MRI of the brain has been solely performed in 2D. To evaluate the feasibility of the recently developed sequence 3D-QALAS for brain cortical thickness and volumetric analysis. Reproducibility/repeatability study. Twenty-one healthy volunteers (35.6 ± 13.8 years). 3D T FreeSurfer and FIRST were used to measure cortical thickness and volume of subcortical structures, respectively. Agreement with FSPGR and scan-rescan repeatability were evaluated for 3D-QALAS. Percent relative difference and intraclass correlation coefficient (ICC) were used to assess reproducibility and scan-rescan repeatability of the 3D-QALAS sequence-derived measurements. Percent relative difference compared with FSPGR in cortical thickness of the whole cortex was 3.1%, and 89% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.65, and 74% of the structures showed substantial to almost perfect agreement. For volumes of subcortical structures, the median percent relative differences were lower than 10% across all subcortical structures, except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. For the scan-rescan test, percent relative difference in cortical thickness of the whole cortex was 2.3%, and 97% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.73, and 80% showed substantial to almost perfect agreement. For volumes of subcortical structures, relative differences were less than 10% across all subcortical structures except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. 3D-QALAS could be reliably used for measuring cortical thickness and subcortical volumes in most brain regions. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1834-1842.
Sections du résumé
BACKGROUND
Previous quantitative synthetic MRI of the brain has been solely performed in 2D.
PURPOSE
To evaluate the feasibility of the recently developed sequence 3D-QALAS for brain cortical thickness and volumetric analysis.
STUDY TYPE
Reproducibility/repeatability study.
SUBJECTS
Twenty-one healthy volunteers (35.6 ± 13.8 years).
FIELD STRENGTH/SEQUENCE
3D T
ASSESSMENT
FreeSurfer and FIRST were used to measure cortical thickness and volume of subcortical structures, respectively. Agreement with FSPGR and scan-rescan repeatability were evaluated for 3D-QALAS.
STATISTICAL TESTS
Percent relative difference and intraclass correlation coefficient (ICC) were used to assess reproducibility and scan-rescan repeatability of the 3D-QALAS sequence-derived measurements.
RESULTS
Percent relative difference compared with FSPGR in cortical thickness of the whole cortex was 3.1%, and 89% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.65, and 74% of the structures showed substantial to almost perfect agreement. For volumes of subcortical structures, the median percent relative differences were lower than 10% across all subcortical structures, except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. For the scan-rescan test, percent relative difference in cortical thickness of the whole cortex was 2.3%, and 97% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.73, and 80% showed substantial to almost perfect agreement. For volumes of subcortical structures, relative differences were less than 10% across all subcortical structures except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement.
DATA CONCLUSION
3D-QALAS could be reliably used for measuring cortical thickness and subcortical volumes in most brain regions.
LEVEL OF EVIDENCE
3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1834-1842.
Identifiants
pubmed: 30968991
doi: 10.1002/jmri.26744
pmc: PMC6900192
doi:
Types de publication
Comparative Study
Evaluation Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1834-1842Informations de copyright
© 2019 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Références
Magn Reson Med. 2008 Aug;60(2):320-9
pubmed: 18666127
AJNR Am J Neuroradiol. 2017 Feb;38(2):237-242
pubmed: 27789453
Neuroimage. 2010 Oct 15;53(1):1-15
pubmed: 20547229
Magn Reson Med. 2007 Dec;58(6):1182-95
pubmed: 17969013
AJR Am J Roentgenol. 2002 Sep;179(3):777-82
pubmed: 12185063
Neuroimage. 2009 Oct 15;48(1):21-8
pubmed: 19580876
Magn Reson Med Sci. 2017 Apr 10;16(2):91-92
pubmed: 28003620
Invest Radiol. 2018 Apr;53(4):236-245
pubmed: 29504952
Magn Reson Med Sci. 2018 Oct 10;17(4):275-276
pubmed: 29238005
J Neurosci. 2003 Apr 15;23(8):3295-301
pubmed: 12716936
Magn Reson Med. 2007 Mar;57(3):528-37
pubmed: 17326183
PLoS One. 2010 Dec 20;5(12):e15710
pubmed: 21187930
J Cardiovasc Magn Reson. 2014 Dec 20;16:102
pubmed: 25526880
Bipolar Disord. 2008 Feb;10(1):1-37
pubmed: 18199239
Proc Natl Acad Sci U S A. 2002 Apr 2;99(7):4703-7
pubmed: 11930016
Neuroimage. 2014 Oct 1;99:166-79
pubmed: 24879923
AJNR Am J Neuroradiol. 2017 Feb;38(2):257-263
pubmed: 27932506
Hum Brain Mapp. 2010 Nov;31(11):1751-62
pubmed: 20162602
Acta Radiol. 2008 Dec;49(10):1167-73
pubmed: 18979271
AJNR Am J Neuroradiol. 2016 Jun;37(6):1023-9
pubmed: 26797137
PLoS One. 2014 Apr 18;9(4):e95161
pubmed: 24747946
J Magn Reson Imaging. 2008 Apr;27(4):685-91
pubmed: 18302232
Neuroimage. 2012 Apr 2;60(2):940-51
pubmed: 22297204
Neuroimage. 1999 Feb;9(2):179-94
pubmed: 9931268
Curr Treat Options Neurol. 2018 Apr 20;20(6):17
pubmed: 29679165
Neuroimage. 2006 Jul 1;31(3):968-80
pubmed: 16530430
Invest Radiol. 2019 Jan;54(1):39-47
pubmed: 30300164
Hum Brain Mapp. 2015 Sep;36(9):3472-85
pubmed: 26033168
Hum Brain Mapp. 2013 Sep;34(9):2313-29
pubmed: 22815187
AJNR Am J Neuroradiol. 2017 Jun;38(6):1103-1110
pubmed: 28450439
Neuroimage. 2006 Aug 1;32(1):180-94
pubmed: 16651008
Neuroimage. 2011 Jun 1;56(3):907-22
pubmed: 21352927
Magn Reson Imaging. 2008 Nov;26(9):1294-302
pubmed: 18499384
Invest Radiol. 2017 Oct;52(10):647-657
pubmed: 28257339
Biometrics. 1977 Mar;33(1):159-74
pubmed: 843571
Med Phys. 1987 Jan-Feb;14(1):1-37
pubmed: 3031439
Magn Reson Imaging. 2017 May;38:13-20
pubmed: 27998745
Neurology. 2005 Mar 22;64(6):1032-9
pubmed: 15781822
Neuroimage. 2012 Aug 15;62(2):774-81
pubmed: 22248573
J Magn Reson Imaging. 2012 Feb;35(2):300-8
pubmed: 21987489