A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies

Walker, Lindsay; Curry, Michael J.; Nayak, Amritha; Lange, Nicholas; Pierpaoli, Carlo

doi:10.1002/hbm.22081

Cited by 30 publications

(37 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additional studies with harmonised DTI protocols have already been performed in Alzheimer’s disease as well as in Huntington’s disease 36 37. A framework for the analysis of phantom data in multicentre DTI studies has been previously provided 38. Reproducibility of DTI metrics has been recently tested in a sample of healthy controls at two identical scanners39 reporting that the within-session and between-session reproducibility was lower than the values for intersubject variability.…”

Section: Discussionmentioning

confidence: 99%

A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis

Müller

Turner

Großkreutz

et al. 2016

J Neurol Neurosurg Psychiatry

151

View full text Add to dashboard Cite

ObjectiveDamage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size.Methods442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups.ResultsAnalysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings.InterpretationThis large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS.

show abstract

Section: Discussionmentioning

confidence: 99%

A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis

Müller

Turner

Großkreutz

et al. 2016

J Neurol Neurosurg Psychiatry

151

View full text Add to dashboard Cite

show abstract

“…The ACR phantom [15] and ice-water phantom [31] have been used in previous multicenter quality control studies for diffusion imaging. However, the diffusivity of the ACR phantom (~3 × 10 −3 mm 2 /s) is even more poorly matched to the diffusivity of tissue than the BIRN phantom.…”

Section: Discussionmentioning

confidence: 99%

“…Previous multicenter diffusion imaging studies have been limited to scanners from the same manufacturer or to only a few sites [14] or fewer gradient directions [5, 15]. …”

Section: Introductionmentioning

confidence: 99%

Quantitative quality assurance in a multicenter HARDI clinical trial at 3 T

Zhou

Sakaie

Debbins

et al. 2017

Magnetic Resonance Imaging

View full text Add to dashboard Cite

A phantom-based quality assurance (QA) protocol was developed for a multicenter clinical trial including high angular resolution diffusion imaging (HARDI). A total of 27 3T MR scanners from 2 major manufacturers, GE (Discovery and Signa scanners) and Siemens (Trio and Skyra scanners), were included in this trial. With this protocol, agar phantoms doped to mimic relaxation properties of brain tissue are scanned on a monthly basis, and quantitative procedures are used to detect spiking and to evaluate eddy current and Nyquist ghosting artifacts. In this study, simulations were used to determine alarm thresholds for minimal acceptable signal-to-noise ratio (SNR). Our results showed that spiking artifact was the most frequently observed type of artifact. Overall, Trio scanners exhibited less eddy current distortion than GE scanners, which in turn showed less distortion than Skyra scanners. This difference was mainly caused by the different sequences used on these scanners. The SNR for phantom scans was closely correlated with the SNR from volunteers. Nearly all of the phantom measurements with artifact-free images were above the alarm threshold, suggesting that the scanners are stable longitudinally. Software upgrades and hardware replacement sometimes affected SNR substantially but sometimes did not. In light of these results, it is important to monitor longitudinal SNR with phantom QA to help interpret potential effects on in vivo measurements. Our phantom QA procedure for HARDI scans was successful in tracking scanner performance and detecting unwanted artifacts.

show abstract

“…There are many examples of such projects that collect imaging data at several different sites and use phantoms and harmonized data collection protocols. Generally, these collaborations have a quality control center that aggregates data and evaluates the data to ensure that each site is performing the experiment as expected (Walker, et al 2013). …”

Section: Data Repositories For Brain Imagingmentioning

confidence: 99%

Can data repositories help find effective treatments for complex diseases?

Farber

2017

Progress in Neurobiology

View full text Add to dashboard Cite

There are many challenges to developing treatments for complex diseases. This review explores the question of whether it is possible to imagine a data repository that would increase the pace of understanding complex diseases sufficiently well to facilitate the development of effective treatments. First, consideration is given to the amount of data that might be needed for such a data repository and whether the existing data storage infrastructure is enough. Several successful data repositories are then examined to see if they have common characteristics. An area of science where unsuccessful attempts to develop a data infrastructure is then described to see what lessons could be learned for a data repository devoted to complex disease. Then, a variety of issues related to sharing data are discussed. In some of these areas, it is reasonably clear how to move forward. In other areas, there are significant open questions that need to be addressed by all data repositories. Using that baseline information, the question of whether data archives can be effective in understanding a complex disease is explored. The major goal of such a data archive is likely to be identifying biomarkers that define sub-populations of the disease.

show abstract

A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies

Cited by 30 publications

References 33 publications

A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis

A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis

Quantitative quality assurance in a multicenter HARDI clinical trial at 3 T

Can data repositories help find effective treatments for complex diseases?

Contact Info

Product

Resources

About