Improved volumetric measurement of brain structure with a distortion correction procedure using an ADNI phantom

Maikusa, Norihide; Yamashita, Fumio; Tanaka, Kenichiro; Abe, Osamu; Kawaguchi, Atsushı; Kabasawa, Hiroyuki; Chiba, Shoma; Kasahara, Akihiro; Kobayashi, Nobuhisa; Yuasa, Tetsuya; Sato, Noriko; Iwatsubo, Takeshi

doi:10.1118/1.4801913

Cited by 26 publications

(30 citation statements)

References 34 publications

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“…Noise characteristics that can influence scan quality largely fall into two different categories: machine‐related and subject‐related noise. The rapid advancement in MR technologies has dramatically reduced machine‐related noise, although the regular use of phantoms is important to monitor scanner stability and geometric distortions over time (Bourel, Gibon, Coste, Daanen, & Rousseau, , Friedman and Glover, , Maikusa et al, ). In addition, major upgrades to MR hardware or software, while not considered noise, can influence image quality, and is especially important to consider in longitudinal studies.…”

Section: Discussionmentioning

confidence: 99%

Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface‐based reconstruction

White

Jansen

Muetzel

et al. 2017

Human Brain Mapping

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Motion-related artifacts are one of the major challenges associated with pediatric neuroimaging. Recent studies have shown a relationship between visual quality ratings of T images and cortical reconstruction measures. Automated algorithms offer more precision in quantifying movement-related artifacts compared to visual inspection. Thus, the goal of this study was to test three different automated quality assessment algorithms for structural MRI scans. The three algorithms included a Fourier-, integral-, and a gradient-based approach which were run on raw T -weighted imaging data collected from four different scanners. The four cohorts included a total of 6,662 MRI scans from two waves of the Generation R Study, the NIH NHGRI Study, and the GUSTO Study. Using receiver operating characteristics with visually inspected quality ratings of the T images, the area under the curve (AUC) for the gradient algorithm, which performed better than either the integral or Fourier approaches, was 0.95, 0.88, and 0.82 for the Generation R, NHGRI, and GUSTO studies, respectively. For scans of poor initial quality, repeating the scan often resulted in a better quality second image. Finally, we found that even minor differences in automated quality measurements were associated with FreeSurfer derived measures of cortical thickness and surface area, even in scans that were rated as good quality. Our findings suggest that the inclusion of automated quality assessment measures can augment visual inspection and may find use as a covariate in analyses or to identify thresholds to exclude poor quality data.

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Section: Discussionmentioning

confidence: 99%

Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface‐based reconstruction

White

Jansen

Muetzel

et al. 2017

Human Brain Mapping

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“…Subsequently, phantom-based distortion correction [39] was performed to correct geometric distortion caused by the gradient non-linearity and static magnetic field inhomogeneity of each scanner.…”

Section: Methodsmentioning

confidence: 99%

Sample Size Estimation for Alzheimer’s Disease Trials from Japanese ADNI Serial Magnetic Resonance Imaging

Fujishima

Kawaguchi

Maikusa

et al. 2017

JAD

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Background: Little is known about the sample sizes required for clinical trials of Alzheimer’s disease (AD)-modifying treatments using atrophy measures from serial brain magnetic resonance imaging (MRI) in the Japanese population.Objective: The primary objective of the present study was to estimate how large a sample size would be needed for future clinical trials for AD-modifying treatments in Japan using atrophy measures of the brain as a surrogate biomarker.Methods: Sample sizes were estimated from the rates of change of the whole brain and hippocampus by the k-means normalized boundary shift integral (KN-BSI) and cognitive measures using the data of 537 Japanese Alzheimer’s Neuroimaging Initiative (J-ADNI) participants with a linear mixed-effects model. We also examined the potential use of ApoE status as a trial enrichment strategy.Results: The hippocampal atrophy rate required smaller sample sizes than cognitive measures of AD and mild cognitive impairment (MCI). Inclusion of ApoE status reduced sample sizes for AD and MCI patients in the atrophy measures.Conclusion: These results show the potential use of longitudinal hippocampal atrophy measurement using automated image analysis as a progression biomarker and ApoE status as a trial enrichment strategy in a clinical trial of AD-modifying treatment in Japanese people.

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“…This algorithm was based on the three-dimensional magnetization-prepared rapid gradient-echo protocol. Programs to improve image clarity and other factors were administered to enable accurate and reproducible volumetric analysis of structural MRI data [67]. The PET core has set up a standardized protocol for PET imaging in J-ADNI, and a versatile and rigorous quality control system of PET images.…”

Section: Japanese Adnimentioning

confidence: 99%

The Worldwide Alzheimer's Disease Neuroimaging Initiative: An update

Hendrix

Finger²,

Weiner

et al. 2015

Alzheimer's & Dementia

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The Alzheimer's Disease Neuroimaging Initiative (ADNI), launched in 2004, has worked to accelerate drug development by validating imaging and blood/cerebrospinal fluid biomarkers for Alzheimer's disease clinical treatment trials. ADNI is a naturalistic (nontreatment) multisite longitudinal study. A true public-private partnership, the initiative has set a new standard for data sharing without embargo and for the use of biomarkers in dementia research. The ADNI effort in North America is not the only such effort in the world. The Alzheimer's Association recognized these global efforts and formed Worldwide ADNI (WW-ADNI). By creating a platform for international collaboration and cooperation, WW-ADNI's goals are to harmonize projects and results across geographical regions and to facilitate data management and availability to investigators around the world. WW-ADNI projects include those based in North America, Europe, Japan, Australia, Korea, and Argentina.

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Improved volumetric measurement of brain structure with a distortion correction procedure using an ADNI phantom

Cited by 26 publications

References 34 publications

Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface‐based reconstruction

Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface‐based reconstruction

Sample Size Estimation for Alzheimer’s Disease Trials from Japanese ADNI Serial Magnetic Resonance Imaging

The Worldwide Alzheimer's Disease Neuroimaging Initiative: An update

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