A novel framework for evaluating the image accuracy of dynamic MRI and the application on accelerated breast DCE MRI

  • Yuan Le
  • Marcel Dominik Nickel
  • Stephan Kannengiesser
  • Berthold Kiefer
  • Bruce Spottiswoode
  • Brian Dale
  • Victor Soon
  • Chen Lin
Research Article

Abstract

Objective

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).

Materials and methods

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).

Results

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.

Conclusion

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.

Keywords

View-sharing acceleration DCE-MRI Simulation Breast imaging Tumor model 

Notes

Compliance with ethical standards

Conflict of interest

This study was sponsored by Siemens Healthcare.

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Copyright information

© ESMRMB 2017

Authors and Affiliations

  1. 1.Department of Radiology and Imaging ScienceIndiana University School of MedicineIndianapolisUSA
  2. 2.Siemens HealthcareErlangenGermany
  3. 3.Siemens Medical Solutions USA IncMalvenUSA

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