Multistage Background Field Removal (MUBAFIRE)-Compensating for B0 Distortions at Ultra-High Field

Johannes Lindemeyer; Ana-Maria Oros-Peusquens; N Jon Shah

doi:10.1371/journal.pone.0138325

Multistage Background Field Removal (MUBAFIRE)-Compensating for B0 Distortions at Ultra-High Field

PLoS One. 2015 Sep 22;10(9):e0138325. doi: 10.1371/journal.pone.0138325. eCollection 2015.

Authors

Johannes Lindemeyer¹, Ana-Maria Oros-Peusquens¹, N Jon Shah²

Affiliations

¹ Institute of Neuroscience and Medicine 4, INM-4: Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany.
² Institute of Neuroscience and Medicine 4, INM-4: Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany; Department of Neurology, Faculty of Medicine, JARA, RWTH Aachen University, Aachen, Germany.

Abstract

The investigation of tissue magnetic susceptibility and the resultant magnetic field offers a new avenue for quantitative tissue characterisation by MRI. One crucial step in mining the phase and field data for relevant tissue information is the correction of externally induced field shifts. This article outlines a multistep approach comprising several methodologies for background field removal. The virtues of B0 long-range variation detection and compensation of more localised external disturbances are unified in a sequential filter chain. The algorithm is tested by means of a numerical Monte Carlo simulation model and applied to in vivo measurements at 3T and 9.4T as well as to a fixed brain tissue measurement at 9.4T. Further, a comparison to conventional filter types has been undertaken.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Brain / diagnostic imaging*
Humans
Magnetic Fields
Magnetic Resonance Imaging*
Monte Carlo Method
Radiography
Signal-To-Noise Ratio

Grants and funding

The authors gratefully acknowledge funding from the Bundesministerium für Bildung und Forschung (Grant No.: 13N9121, http://www.bmbf.de/). This work was further funded in part by the Helmholtz Alliance ICEMED—Imaging and Curing Environmental Metabolic Diseases, through the Initiative and Network Fund of the Helmholtz Association (http://www.helmholtz.de/helmholtz_zentren_netzwerke/helmholtz_allianzen/icemed/). Generous support from Siemens for construction of the 9.4T MR scanner is also gratefully acknowledged (http://www.healthcare.siemens.de/magnetic-resonance-imaging). The authors declare that Siemens (Siemens Healthcare, Erlangen, Germany) was only acknowledged for general support and did not fund any projects, material or positions involved in this research work. Neither has the company had any role in study design, data collection and analysis, decision to publish, or preparation of this manuscript. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.