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Attention Score in Context
| Title |
Bayesian intravoxel incoherent motion parameter mapping in the human heart
|
|---|---|
| Published in |
Critical Reviews in Diagnostic Imaging, November 2017
|
| DOI | 10.1186/s12968-017-0391-1 |
| Pubmed ID | |
| Authors |
Georg R. Spinner, Constantin von Deuster, Kerem C. Tezcan, Christian T. Stoeck, Sebastian Kozerke |
| Abstract |
Intravoxel incoherent motion (IVIM) imaging of diffusion and perfusion in the heart suffers from high parameter estimation error. The purpose of this work is to improve cardiac IVIM parameter mapping using Bayesian inference. A second-order motion-compensated diffusion weighted spin-echo sequence with navigator-based slice tracking was implemented to collect cardiac IVIM data in early systole in eight healthy subjects on a clinical 1.5 T CMR system. IVIM data were encoded along six gradient optimized directions with b-values of 0-300 s/mm(2). Subjects were scanned twice in two scan sessions one week apart to assess intra-subject reproducibility. Bayesian shrinkage prior (BSP) inference was implemented to determine IVIM parameters (diffusion D, perfusion fraction F and pseudo-diffusion D*). Results were compared to least-squares (LSQ) parameter estimation. Signal-to-noise ratio (SNR) requirements for a given fitting error were assessed for the two methods using simulated data. Reproducibility analysis of parameter estimation in-vivo using BSP and LSQ was performed. BSP resulted in reduced SNR requirements when compared to LSQ in simulations. In-vivo, BSP analysis yielded IVIM parameter maps with smaller intra-myocardial variability and higher estimation certainty relative to LSQ. Mean IVIM parameter estimates in eight healthy subjects were (LSQ/BSP): 1.63 ± 0.28/1.51 ± 0.14·10(-3) mm(2)/s for D, 13.13 ± 19.81/13.11 ± 5.95% for F and 201.45 ± 313.23/13.11 ± 14.53·10(-3) mm(2)/s for D (∗). Parameter variation across all volunteers and measurements was lower with BSP compared to LSQ (coefficient of variation BSP vs. LSQ: 9% vs. 17% for D, 45% vs. 151% for F and 111% vs. 155% for D (∗)). In addition, reproducibility of the IVIM parameter estimates was higher with BSP compared to LSQ (Bland-Altman coefficients of repeatability BSP vs. LSQ: 0.21 vs. 0.26·10(-3) mm(2)/s for D, 5.55 vs. 6.91% for F and 15.06 vs. 422.80·10(-3) mm(2)/s for D*). Robust free-breathing cardiac IVIM data acquisition in early systole is possible with the proposed method. BSP analysis yields improved IVIM parameter maps relative to conventional LSQ fitting with fewer outliers, improved estimation certainty and higher reproducibility. IVIM parameter mapping holds promise for myocardial perfusion measurements without the need for contrast agents. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 1 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 25% |
| Student > Master | 8 | 17% |
| Researcher | 5 | 10% |
| Student > Postgraduate | 4 | 8% |
| Student > Doctoral Student | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 12 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 11 | 23% |
| Medicine and Dentistry | 8 | 17% |
| Physics and Astronomy | 5 | 10% |
| Agricultural and Biological Sciences | 3 | 6% |
| Computer Science | 2 | 4% |
| Other | 1 | 2% |
| Unknown | 18 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 November 2017.
All research outputs
#15,404,780
of 25,728,855 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#954
of 1,386 outputs
Outputs of similar age
#179,750
of 343,383 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#33
of 34 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
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