Literature DB >> 32086836

The 2016 QSM Challenge: Lessons learned and considerations for a future challenge design.

Carlos Milovic1,2,3, Cristian Tejos1,2,3, Julio Acosta-Cabronero4, Pinar Senay Özbay5, Ferdinand Schwesser6,7, Jose Pedro Marques8, Pablo Irarrazaval1,3,9, Berkin Bilgic10, Christian Langkammer11.   

Abstract

PURPOSE: The 4th International Workshop on MRI Phase Contrast and QSM (2016, Graz, Austria) hosted the first QSM Challenge. A single-orientation gradient recalled echo acquisition was provided, along with COSMOS and the χ33 STI component as ground truths. The submitted solutions differed more than expected depending on the error metric used for optimization and were generally over-regularized. This raised (unanswered) questions about the ground truths and the metrics utilized.
METHODS: We investigated the influence of background field remnants by applying additional filters. We also estimated the anisotropic contributions from the STI tensor to the apparent susceptibility to amend the χ33 ground truth and to investigate the impact on the reconstructions. Lastly, we used forward simulations from the COSMOS reconstruction to investigate the impact noise had on the metric scores.
RESULTS: Reconstructions compared against the amended STI ground truth returned lower errors. We show that the background field remnants had a minor impact in the errors. In the absence of inconsistencies, all metrics converged to the same regularization weights, whereas structural similarity index metric was more insensitive to such inconsistencies.
CONCLUSION: There was a mismatch between the provided data and the ground truths due to the presence of unaccounted anisotropic susceptibility contributions and noise. Given the lack of reliable ground truths when using in vivo acquisitions, simulations are suggested for future QSM Challenges.
© 2020 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  FANSI; magnetic susceptibility; quantitative susceptibility mapping; total variation

Mesh:

Year:  2020        PMID: 32086836      PMCID: PMC7526054          DOI: 10.1002/mrm.28185

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  41 in total

1.  Susceptibility mapping in the human brain using threshold-based k-space division.

Authors:  Sam Wharton; Andreas Schäfer; Richard Bowtell
Journal:  Magn Reson Med       Date:  2010-05       Impact factor: 4.668

2.  Calculation of susceptibility through multiple orientation sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI.

Authors:  Tian Liu; Pascal Spincemaille; Ludovic de Rochefort; Bryan Kressler; Yi Wang
Journal:  Magn Reson Med       Date:  2009-01       Impact factor: 4.668

3.  Background field removal by solving the Laplacian boundary value problem.

Authors:  Dong Zhou; Tian Liu; Pascal Spincemaille; Yi Wang
Journal:  NMR Biomed       Date:  2014-01-07       Impact factor: 4.044

4.  Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: validation and application to brain imaging.

Authors:  Ludovic de Rochefort; Tian Liu; Bryan Kressler; Jing Liu; Pascal Spincemaille; Vincent Lebon; Jianlin Wu; Yi Wang
Journal:  Magn Reson Med       Date:  2010-01       Impact factor: 4.668

Review 5.  Quantitative Susceptibility Mapping: Concepts and Applications.

Authors:  J R Reichenbach; F Schweser; B Serres; A Deistung
Journal:  Clin Neuroradiol       Date:  2015-07-22       Impact factor: 3.649

Review 6.  Quantitative susceptibility mapping: current status and future directions.

Authors:  E Mark Haacke; Saifeng Liu; Sagar Buch; Weili Zheng; Dongmei Wu; Yongquan Ye
Journal:  Magn Reson Imaging       Date:  2014-10-25       Impact factor: 2.546

7.  Phase processing for quantitative susceptibility mapping of regions with large susceptibility and lack of signal.

Authors:  Véronique Fortier; Ives R Levesque
Journal:  Magn Reson Med       Date:  2017-11-11       Impact factor: 4.668

Review 8.  An illustrated comparison of processing methods for phase MRI and QSM: removal of background field contributions from sources outside the region of interest.

Authors:  Ferdinand Schweser; Simon Daniel Robinson; Ludovic de Rochefort; Wei Li; Kristian Bredies
Journal:  NMR Biomed       Date:  2016-10-07       Impact factor: 4.044

9.  Preconditioned total field inversion (TFI) method for quantitative susceptibility mapping.

Authors:  Zhe Liu; Youngwook Kee; Dong Zhou; Yi Wang; Pascal Spincemaille
Journal:  Magn Reson Med       Date:  2016-07-28       Impact factor: 4.668

10.  Single-step quantitative susceptibility mapping with variational penalties.

Authors:  Itthi Chatnuntawech; Patrick McDaniel; Stephen F Cauley; Borjan A Gagoski; Christian Langkammer; Adrian Martin; P Ellen Grant; Lawrence L Wald; Kawin Setsompop; Elfar Adalsteinsson; Berkin Bilgic
Journal:  NMR Biomed       Date:  2016-06-22       Impact factor: 4.044

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  3 in total

1.  Comparison of parameter optimization methods for quantitative susceptibility mapping.

Authors:  Carlos Milovic; Claudia Prieto; Berkin Bilgic; Sergio Uribe; Julio Acosta-Cabronero; Pablo Irarrazaval; Cristian Tejos
Journal:  Magn Reson Med       Date:  2020-08-01       Impact factor: 4.668

2.  Single-step calculation of susceptibility through multiple orientation sampling.

Authors:  Lin Chen; Shuhui Cai; Peter C M van Zijl; Xu Li
Journal:  NMR Biomed       Date:  2021-04-06       Impact factor: 4.478

3.  QSM reconstruction challenge 2.0: A realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures.

Authors:  José P Marques; Jakob Meineke; Carlos Milovic; Berkin Bilgic; Kwok-Shing Chan; Renaud Hedouin; Wietske van der Zwaag; Christian Langkammer; Ferdinand Schweser
Journal:  Magn Reson Med       Date:  2021-02-26       Impact factor: 4.668

  3 in total

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