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McMaster University

Investigating the Effects of Motion Streaks on pQCT-Derived Leg Muscle Density and Its Association With Fractures

Overview of attention for article published in Journal of Clinical Densitometry, January 2017
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  • Good Attention Score compared to outputs of the same age (65th percentile)

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Title
Investigating the Effects of Motion Streaks on pQCT-Derived Leg Muscle Density and Its Association With Fractures
Published in
Journal of Clinical Densitometry, January 2017
DOI 10.1016/j.jocd.2016.12.001
Pubmed ID
Authors

Adrian C.H. Chan, Jonathan D. Adachi, Alexandra Papaioannou, Andy Kin On Wong

Abstract

Lower peripheral quantitative computed tomography (pQCT)-derived leg muscle density has been associated with fragility fractures in postmenopausal women. Limb movement during image acquisition may result in motion streaks in muscle that could dilute this relationship. This cross-sectional study examined a subset of women from the Canadian Multicentre Osteoporosis Study. pQCT leg scans were qualitatively graded (1-5) for motion severity. Muscle and motion streak were segmented using semi-automated (watershed) and fully automated (threshold-based) methods, computing area, and density. Binary logistic regression evaluated odds ratios (ORs) for fragility or all-cause fractures related to each of these measures with covariate adjustment. Among the 223 women examined (mean age: 72.7 ± 7.1 years, body mass index: 26.30 ± 4.97 kg/m(2)), muscle density was significantly lower after removing motion (p < 0.001) for both methods. Motion streak areas segmented using the semi-automated method correlated better with visual motion grades (rho = 0.90, p < 0.01) compared to the fully automated method (rho = 0.65, p < 0.01). Although the analysis-reanalysis precision of motion streak area segmentation using the semi-automated method is above 5% error (6.44%), motion-corrected muscle density measures remained well within 2% analytical error. The effect of motion-correction on strengthening the association between muscle density and fragility fractures was significant when motion grade was ≥3 (p interaction <0.05). This observation was most dramatic for the semi-automated algorithm (OR: 1.62 [0.82,3.17] before to 2.19 [1.05,4.59] after correction). Although muscle density showed an overall association with all-cause fractures (OR: 1.49 [1.05,2.12]), the effect of motion-correction was again, most impactful within individuals with scans showing grade 3 or above motion. Correcting for motion in pQCT leg scans strengthened the relationship between muscle density and fragility fractures, particularly in scans with motion grades of 3 or above. Motion streaks are not confounders to the relationship between pQCT-derived leg muscle density and fractures, but may introduce heterogeneity in muscle density measurements, rendering associations with fractures to be weaker.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 24%
Student > Bachelor 3 14%
Researcher 3 14%
Professor > Associate Professor 2 10%
Student > Ph. D. Student 1 5%
Other 0 0%
Unknown 7 33%
Readers by discipline Count As %
Medicine and Dentistry 4 19%
Biochemistry, Genetics and Molecular Biology 3 14%
Nursing and Health Professions 2 10%
Mathematics 1 5%
Computer Science 1 5%
Other 3 14%
Unknown 7 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 May 2017.
All research outputs
#8,474,477
of 25,374,647 outputs
Outputs from Journal of Clinical Densitometry
#125
of 488 outputs
Outputs of similar age
#144,966
of 422,334 outputs
Outputs of similar age from Journal of Clinical Densitometry
#3
of 4 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 488 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 422,334 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.