| Title |
A novel framework for evaluating the image accuracy of dynamic MRI and the application on accelerated breast DCE MRI
|
|---|---|
| Published in |
Magnetic Resonance Materials in Physics, Biology and Medicine, September 2017
|
| DOI | 10.1007/s10334-017-0648-6 |
| Pubmed ID | |
| Authors |
Yuan Le, Marcel Dominik Nickel, Stephan Kannengiesser, Berthold Kiefer, Bruce Spottiswoode, Brian Dale, Victor Soon, Chen Lin |
| Abstract |
To develop a novel framework for evaluating the accuracy of quantitative analysis on dynamic contrast-enhanced (DCE) MRI with a specific combination of imaging technique, scanning parameters, and scanner and software performance and to test this framework with breast DCE MRI with Time-resolved angiography WIth Stochastic Trajectories (TWIST). Realistic breast tumor phantoms were 3D printed as cavities and filled with solutions of MR contrast agent. Full k-space raw data of individual tumor phantoms and a uniform background phantom were acquired. DCE raw data were simulated by sorting the raw data according to TWIST view order and scaling the raw data according to the enhancement based on pharmaco-kinetic (PK) models. The measured spatial and temporal characteristics from the images reconstructed using the scanner software were compared with the original PK model (ground truth). Images could be reconstructed using the manufacturer's platform with the modified 'raw data.' Compared with the 'ground truth,' the RMS error in all images was <10% in most cases. With increasing view-sharing acceleration, the error of the initial uptake slope decreased while the error of peak enhancement increased. Deviations of PK parameters varied with the type of enhancement. A new framework has been developed and tested to more realistically evaluate the quantitative measurement errors caused by a combination of the imaging technique, parameters and scanner and software performance in DCE-MRI. |
X Demographics
The data shown below were collected from the profile of 1 X user 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 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 18% |
| Researcher | 2 | 12% |
| Student > Doctoral Student | 1 | 6% |
| Lecturer > Senior Lecturer | 1 | 6% |
| Other | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 8 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 3 | 18% |
| Medicine and Dentistry | 3 | 18% |
| Psychology | 1 | 6% |
| Environmental Science | 1 | 6% |
| Social Sciences | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 8 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 13 September 2017.
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#21,186,729
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Outputs from Magnetic Resonance Materials in Physics, Biology and Medicine
#424
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Outputs of similar age
#278,482
of 317,826 outputs
Outputs of similar age from Magnetic Resonance Materials in Physics, Biology and Medicine
#7
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