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Blood correction reduces variability and gender differences in native myocardial T1 values at 1.5 T cardiovascular magnetic resonance – a derivation/validation approach

Overview of attention for article published in Critical Reviews in Diagnostic Imaging, April 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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Title
Blood correction reduces variability and gender differences in native myocardial T1 values at 1.5 T cardiovascular magnetic resonance – a derivation/validation approach
Published in
Critical Reviews in Diagnostic Imaging, April 2017
DOI 10.1186/s12968-017-0353-7
Pubmed ID
Authors

Jannike Nickander, Magnus Lundin, Goran Abdula, Peder Sörensson, Stefania Rosmini, James C. Moon, Peter Kellman, Andreas Sigfridsson, Martin Ugander

Abstract

Myocardial native T1 measurements are likely influenced by intramyocardial blood. Since blood T1 is both variable and longer compared to myocardial T1, this will degrade the precision of myocardial T1 measurements. Precision could be improved by correction, but the amount of correction and the optimal blood T1 variables to correct with are unknown. We hypothesized that an appropriate correction would reduce the standard deviation (SD) of native myocardial T1. Consecutive patients (n = 400) referred for CMR with known or suspected heart disease were split into a derivation cohort for model construction (n = 200, age 51 ± 18 years, 50% male) and a validation cohort for assessing model performance (n = 200, age 48 ± 17 years, 50% male). Exclusion criteria included focal septal abnormalities. A Modified Look-Locker inversion recovery sequence (MOLLI, 1.5 T Siemens Aera) was used to acquire T1 and T1* maps. T1 and T1* maps were used to measure native myocardial T1, and blood T1 and T1*. A multivariate linear regression correction model was implemented using blood measurement of R1 (1/T1), R1* (1/T1*) or hematocrit. The correction model from the derivation cohort was applied to the validation cohort, and assessed for reduction in variability with the F-test. Blood [LV + RV] mean R1, mean R1* and hematocrit correlated with myocardial T1 (Pearson's r, range 0.37 to 0.45, p < 0.05 for all) in both the derivation and validation cohorts respectively, suggesting that myocardial T1 measurements are influenced by intramyocardial blood. Mean myocardial native T1 did not differ between the derivation and validation cohorts (1030 ± 42.6 ms and 1023 ± 45.2 ms respectively, p = 0.07). In the derivation cohort, correction using blood mean R1 and mean R1* yielded a decrease in myocardial T1 SD (45.2 ms to 36.6 ms, p = 0.03). When the model from the derivation cohort was applied to the validation cohort, the SD reduction was maintained (39.3 ms, p = 0.049). This 13% reduction in measurement variability leads to a 23% reduction in sample size to detect a 50 ms difference in native myocardial T1. Correcting native myocardial T1 for R1 and R1* of blood improves the precision of myocardial T1 measurement by ~13%, and could consequently improve disease detection and reduce sample size needs for clinical research.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 17%
Researcher 6 15%
Other 3 7%
Student > Postgraduate 3 7%
Student > Master 3 7%
Other 7 17%
Unknown 12 29%
Readers by discipline Count As %
Medicine and Dentistry 16 39%
Engineering 4 10%
Nursing and Health Professions 2 5%
Physics and Astronomy 2 5%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 3 7%
Unknown 13 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 17 March 2023.
All research outputs
#3,001,159
of 25,523,622 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#153
of 1,379 outputs
Outputs of similar age
#52,695
of 324,894 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#6
of 22 outputs
Altmetric has tracked 25,523,622 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,379 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done well, scoring higher than 88% 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 324,894 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.