Comparing 3 T and 1.5 T MRI for tracking Alzheimer's disease progression with tensor‐based morphometry

Ho, April J.; Hou, Xue; Lee, Suh; Leow, Alex D.; Yanovsky, Igor; Gutman, Boris A.; Dinov, Ivo D.; Leporé, Natasha; Stein, Jason L.; Toga, Arthur W.; Jack, Clifford R.; Bernstein, Matt A.; Reiman, Eric M.; Harvey, Danielle; Kornak, John; Schuff, Norbert; Alexander, Gene E.; Weiner, Michael W.; Thompson, Paul M.

doi:10.1002/hbm.20882

Cited by 71 publications

(83 citation statements)

References 69 publications

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“…In volumetric studies, several groups have analyzed the effects of different scanners on cross-sectional or longitudinal morphometric results [Briellmann et al, 2001;Dickerson et al, 2008;Ewers et al, 2006;Fennema-Notestine et al, 2007;Fjell et al, 2009;Han et al, 2006;Ho et al, 2010;Huppertz et al, 2010;Jovicich et al, 2009;Kruggel et al, 2010;Meda et al, 2008;Moorhead et al, 2009;Pardoe et al, 2008;Schnack et al, 2004;Stonnington et al, 2008;Walhovd et al, 2009]. Usually, inter-scanner variability of volumetric measures is larger than intra-scanner variability.…”

Section: Discussionmentioning

confidence: 99%

Effect of scanner in longitudinal diffusion tensor imaging studies

Takao¹,

Hayashi²,

Kabasawa³

et al. 2011

Human Brain Mapping

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The purpose of this study was to evaluate the effects of longitudinal drift in scanner hardware, inter-scanner variability (bias), and scanner upgrade on longitudinal changes in global and regional diffusion properties using longitudinal data obtained on two scanners of the exact same model at one institution. A total of 224 normal subjects were scanned twice, at an interval of about 1 year, using two 3.0-T scanners of the exact same model. Both scanners were simultaneously upgraded during the study period. The subjects were divided into four groups according to the combination of scanners used. With use of tract-based spatial statistics, we evaluated the effects of scanner drift and inter-scanner variability (bias) on global and regional fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) changes of the white matter. Even with scanners of the exact same model, inter-scanner variability (bias) significantly affected longitudinal results. FA, AD, and RD of the white matter were relatively stable within the same scanner. We also investigated the effect of scanner upgrade on longitudinal FA, AD, and RD changes. The scanner upgrade included only software upgrade, not hardware upgrade; however, there was a significant effect of scanner upgrade on longitudinal results. These results indicate that inter-scanner variability and scanner upgrade can significantly affect the results of longitudinal diffusion tensor imaging studies.

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Section: Discussionmentioning

confidence: 99%

Effect of scanner in longitudinal diffusion tensor imaging studies

Takao¹,

Hayashi²,

Kabasawa³

et al. 2011

Human Brain Mapping

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“…In a strictly signal-to-noise comparison study, Fushimi et al 24 reported no significant differences in signal-to-noise ratios between 1.5T and 3T in multisection images with a 0-mm gap. Applying tensor brain morphometry and Structural Image Evaluation Using Normalization of Atrophy algorithms to ADNI-1 1.5T and 3T data, Ho et al 26 reported no significant advantage of 3T over 1.5T for detecting 1-year whole-brain atrophy rates. Perhaps most importantly, 2 groups compared the performance of their automated multiatlas hippocampal segmentation techniques at 1.5T and 3T in small samples derived from ADNI-1.…”

Section: Discussionmentioning

confidence: 99%

“…24–27 One tensor-based morphometry whole-brain study reported that analyses of 1.5T and 3T Alzheimer’s Disease Neuroimaging Initiative (ADNI) data from the same subjects did not differ statistically in detecting neurodegenerative changes during 12 months. 26 Hippocampal volumes extracted from the same study cohort at 1.5T and 3T showed only 3.2% test-retest variability. 25 Similar results were reported for manual segmentations in 8 healthy subjects with 1.5T and 3T scans in an epilepsy study.…”

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confidence: 83%

Comparing 3T and 1.5T MRI for Mapping Hippocampal Atrophy in the Alzheimer's Disease Neuroimaging Initiative

Chow

Hwang

Hurtz³

et al. 2015

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE Prior MR imaging studies, primarily at 1.5T, established hippocampal atrophy as a biomarker for Alzheimer disease. 3T MR imaging offers a higher contrast and signal-to-noise ratio, yet distortions and intensity uniformity are harder to control. We applied our automated hippocampal segmentation technique to 1.5T and 3T MR imaging data, to determine whether hippocampal atrophy detection was enhanced at 3T. MATERIALS AND METHODS We analyzed baseline MR imaging data from 166 subjects from the Alzheimer’s Disease Neuroimaging Initiative-1 (37 with Alzheimer disease, 76 with mild cognitive impairment, and 53 healthy controls) scanned at 1.5T and 3T. Using multiple linear regression, we analyzed the effect of clinical diagnosis on hippocampal radial distance, while adjusting for sex. 3D statistical maps were adjusted for multiple comparisons by using permutation-based statistics at a threshold of P < .01. RESULTS Bilaterally significant radial distance differences in the areas corresponding to the cornu ammonis 1, cornu ammonis 2, and subiculum were detected for Alzheimer disease versus healthy controls and mild cognitive impairment versus healthy controls at 1.5T and more profoundly at 3T. Comparison of Alzheimer disease with mild cognitive impairment did not reveal significant differences at either field strength. Subjects who converted from mild cognitive impairment to Alzheimer disease within 3 years of the baseline scan versus nonconverters showed significant differences in the area corresponding to cornu ammonis 1 of the right hippocampus at 3T but not at 1.5T. CONCLUSIONS While hippocampal atrophy patterns in diagnostic comparisons were similar at 1.5T and 3T, 3T showed a superior signal-to-noise ratio and detected atrophy with greater effect size compared with 1.5T.

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“…One of the aims of ADNI 1 was to compare structural MRI measures at 1.5T vs 3T to determine if field strength had a significant impact on quantitative measures that were relevant to AD clinical trials. ADNI investigators found that the two field strengths were roughly comparable with no major drawbacks unique to either [11, 12]. Because of greater signal to noise and the greater flexibility for more advanced scanning techniques at 3T, ADNI GO/2 was conducted entirely at 3T [3].…”

Section: Accomplishments Of the Adni Mri Core To Datementioning

confidence: 99%

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

Jack

Barnes

Bernstein

et al. 2015

Alzheimer's & Dementia

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172

105

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INTRODUCTION ADNI is now in its 10th year. The primary objective of the MRI core of ADNI has been to improve methods for clinical trials in Alzheimer’s disease and related disorders. METHODS We review the contributions of the MRI core from present and past cycles of ADNI (ADNI 1, GO and 2). We also review plans for the future – ADNI 3. RESULTS Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. DISCUSSION Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in Alzheimer’s disease and will continue to do so in the future.

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Comparing 3 T and 1.5 T MRI for tracking Alzheimer's disease progression with tensor‐based morphometry

Cited by 71 publications

References 69 publications

Effect of scanner in longitudinal diffusion tensor imaging studies

Effect of scanner in longitudinal diffusion tensor imaging studies

Comparing 3T and 1.5T MRI for Mapping Hippocampal Atrophy in the Alzheimer's Disease Neuroimaging Initiative

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

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