Evidence map›Paper›PMID 24803089›Full record

ArticleJournal of magnetic resonance imaging : JMRI2015

Registration-based autofocusing technique for automatic correction of motion artifacts in time-series studies of high-resolution bone MRI.

Ning Zhang, Jeremy F Magland, Hee Kwon Song, Felix W Wehrli

Open access · bronzeAbstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 93% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Ning ZhangLaboratory for Structural NMR Imaging, Department of Radiology, University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, USA.
Jeremy F Magland
Hee Kwon Song
Felix W Wehrli
University of Pennsylvania · US

Funding

Osteoporosis Treatment Response Assessed by Micromechanical Modeling of MRI DataR01AR055647 · NIAMS · UNIVERSITY OF PENNSYLVANIA · PI WEHRLI, FELIX W · 2007 to 2016
$3.6M
MRI-Based Assessment of Structural and Mechanical Implications of OsteoporosisR01AG038693 · NIA · UNIVERSITY OF PENNSYLVANIA · PI WEHRLI, FELIX W · 2011 to 2014
$1.6M
Tensor Scale-based Methods for Assessment of Trabecular Bone QualityR01AR054439 · NIAMS · UNIVERSITY OF IOWA · PI SAHA, PUNAM K. · 2009 to 2012
$1.4M
Real-time feedback MRI for improved reproducibility in imaging biomarkersK25EB007646 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI MAGLAND, JEREMY · 2008 to 2012
$682k
Computational Biomechanics for Prediction of Osteoporotic Vertebral Fracture RiskK25AR060283 · NIAMS · UNIVERSITY OF PENNSYLVANIA · PI RAJAPAKSE, CHAMITH SUDESH · 2011 to 2014
$491k
NIAMS NIH HHS AR 054439NIAMS NIH HHS K25 AR060283NIAMS NIH HHS K25-AR060283NIAMS NIH HHS R01 AR054439NIAMS NIH HHS R01 AR055647NIAMS NIH HHS R01 AR55647NIA NIH HHS R01 AG038693NIA NIH HHS R01 AG38693NIBIB NIH HHS K25 EB007646NIBIB NIH HHS K25-EB007646
6 · The paper itself

Abstract

purposeTo develop a registration-based autofocusing (RAF) motion correction technique for high-resolution trabecular bone (TB) imaging and to evaluate its performance on in vivo MR data. MATERIALS AND

methodsThe technique combines serial registration with a previously developed motion correction technique - autofocusing - for automatic correction of subject movement degradation of MR images acquired in longitudinal studies. The method was tested on in vivo images of the distal radius to measure improvements in serial reproducibility of parameters in 12 women (ages 50-75 years), and to compare with the navigator echo-based correction and autofocusing. Furthermore, the technique's ability to optimize the sensitivity to detect simulated bone loss was ascertained.

resultsThe new technique yielded superior reproducibility of image-derived structural and mechanical parameters. Average coefficient of variation across all parameters improved by 12.5%, 27.0%, 33.5%, and 37.0%, respectively, following correction by navigator echoes, autofocusing, and the RAF technique (without and with correction for rotational motion); average intra-class correlation coefficient increased by 1.2%, 2.2%, 2.8%, and 3.2%, respectively. Furthermore, simulated bone loss (5%) was well recovered independent of the choice of reference image (4.71% or 4.86% with respect to using either the original or the image subjected to bone loss) in the time series.

conclusionThe data suggest that our technique simultaneously corrects for intra-scan motion corruption while improving inter-scan registration. Furthermore, the technique is not biased by small changes in bone architecture between time-points.

Indexed as

ArtifactsSubtraction TechniqueAgedAlgorithmsFemaleHumansImage EnhancementImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMiddle AgedMotionPattern Recognition, AutomatedRadiusReproducibility of ResultsSensitivity and Specificitymotion correctionMRIreproducibilitytrabecular bone

Identifiers

PMID24803089
PMCPMC4224640
OpenAlexW1773346245

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.