Literature DB >> 16651008

Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer.

Xiao Han1, Jorge Jovicich, David Salat, Andre van der Kouwe, Brian Quinn, Silvester Czanner, Evelina Busa, Jenni Pacheco, Marilyn Albert, Ronald Killiany, Paul Maguire, Diana Rosas, Nikos Makris, Anders Dale, Bradford Dickerson, Bruce Fischl.   

Abstract

In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test-retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.

Entities:  

Mesh:

Year:  2006        PMID: 16651008     DOI: 10.1016/j.neuroimage.2006.02.051

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  663 in total

1.  Multi-site characterization of an fMRI working memory paradigm: reliability of activation indices.

Authors:  Anastasia Yendiki; Douglas N Greve; Stuart Wallace; Mark Vangel; Jeremy Bockholt; Bryon A Mueller; Vince Magnotta; Nancy Andreasen; Dara S Manoach; Randy L Gollub
Journal:  Neuroimage       Date:  2010-05-05       Impact factor: 6.556

Review 2.  Quantitative structural MRI for early detection of Alzheimer's disease.

Authors:  Linda K McEvoy; James B Brewer
Journal:  Expert Rev Neurother       Date:  2010-11       Impact factor: 4.618

3.  Papez Circuit Gray Matter and Episodic Memory in Amyotrophic Lateral Sclerosis and Behavioural Variant Frontotemporal Dementia.

Authors:  Ana Paula Arantes Bueno; Leonardo Cruz de Souza; Walter Hugo Lopez Pinaya; Antônio Lúcio Teixeira; Laura Godoy Rousseff de Prado; Paulo Caramelli; Michael Hornberger; João Ricardo Sato
Journal:  Brain Imaging Behav       Date:  2021-04       Impact factor: 3.978

4.  Atrophy and lower regional perfusion of temporo-parietal brain areas are correlated with impairment in memory performances and increase of EEG upper alpha power in prodromal Alzheimer's disease.

Authors:  Vito Davide Moretti
Journal:  Am J Neurodegener Dis       Date:  2015-09-10

5.  MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths.

Authors:  Jorge Jovicich; Silvester Czanner; Xiao Han; David Salat; Andre van der Kouwe; Brian Quinn; Jenni Pacheco; Marilyn Albert; Ronald Killiany; Deborah Blacker; Paul Maguire; Diana Rosas; Nikos Makris; Randy Gollub; Anders Dale; Bradford C Dickerson; Bruce Fischl
Journal:  Neuroimage       Date:  2009-02-20       Impact factor: 6.556

6.  Cerebellum and cognition in multiple sclerosis: the fall status matters.

Authors:  Alon Kalron; Gilles Allali; Anat Achiron
Journal:  J Neurol       Date:  2018-02-02       Impact factor: 4.849

7.  Neuroimaging abnormalities in adults with sickle cell anemia: associations with cognition.

Authors:  R Scott Mackin; Philip Insel; Diana Truran; Elliot P Vichinsky; Lynne D Neumayr; F D Armstrong; Jeffrey I Gold; Karen Kesler; Joseph Brewer; Michael W Weiner
Journal:  Neurology       Date:  2014-02-12       Impact factor: 9.910

8.  Relationship between prefrontal gray matter volumes and working memory performance in schizophrenia: a family study.

Authors:  Vina M Goghari; Angus W Macdonald; Scott R Sponheim
Journal:  Schizophr Res       Date:  2014-02-13       Impact factor: 4.939

9.  Prefrontal cortical deficits in type 1 diabetes mellitus: brain correlates of comorbid depression.

Authors:  In Kyoon Lyoo; Sujung Yoon; Alan M Jacobson; Jaeuk Hwang; Gail Musen; Jieun E Kim; Donald C Simonson; Sujin Bae; Nicolas Bolo; Dajung J Kim; Katie Weinger; Junghyun H Lee; Christopher M Ryan; Perry F Renshaw
Journal:  Arch Gen Psychiatry       Date:  2012-12

10.  Age sensitive associations of adolescent substance use with amygdalar, ventral striatum, and frontal volumes in young adulthood.

Authors:  Michael Windle; Joshua C Gray; Karlo Mankit Lei; Allen W Barton; Gene Brody; Steven R H Beach; Adrianna Galván; James MacKillop; Uraina S Clark; Lawrence H Sweet
Journal:  Drug Alcohol Depend       Date:  2018-03-14       Impact factor: 4.492

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.