title: Evaluation of hardware-related geometrical distortion in structural MRI at 7 Tesla for image-guided applications in neurosurgery.
abstract: OBJECTIVE
  Geometrical distortion is a well-known problem in structural magnetic resonance imaging (MRI), leading to pixel shifts with variations up to several millimeters. Because the main factors of geometrical distortion are proportional to B(0), MRI spatial encoding distortions tend to increase with higher magnetic field strength. With the increasing prospects of utilizing ultra-high-field MRI (B(0) ≥ 7 Tesla) for neuroimaging and subsequently for image-guided neurosurgical therapy, the evaluation and correction of geometrical distortions occurring in ultra-high-field MRI are essential preconditions for the integration of these data. Hence, we conducted a phantom study to determine hardware-related geometrical distortion in clinically relevant sequences for structural imaging at 7 T MRI and compared the findings to 1.5 T MRI.
  
  
  METHODS
  Hardware-related geometrical distortion was evaluated using a MRI phantom (Elekta, Sweden). Both applied scanner systems (Magnetom Avanto 1.5 T and Magnetom 7 T, Siemens Healthcare, Erlangen, Germany) were equipped with similar gradient coils capable of delivering 45 mT/m of maximum amplitude and a slew rate of 220 mT/m/ms. Distortion analysis was performed for various clinically relevant gradient echo and spin echo sequences.
  
  
  RESULTS
  Overall, we found very low mean geometrical distortions at both 7 T and 1.5 T, although single values of up to 1.6 mm were detected. No major differences in mean distortion between the sequences could be found, except significantly higher distortions in turbo spin-echo sequences at 7 T, mainly caused by B(1) inhomogeneities.
  
  
  CONCLUSIONS
  Hardware-related geometrical distortions at 7 T MRI are relatively small, which may be acceptable for image coregistration or for direct tissue-targeting procedures. Using a subject-specific correction of object-related distortions, an integration of 7 T MRI data into image-guided applications may be feasible.
authors.affiliation: Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural Heritage Zollverein, Arendahls Wiese 199, Tor 3, University Duisburg-Essen, 45141 Essen, Germany. philipp.dammann@uk-essen.de
authors.forename: Philipp
authors.initials: P
authors.lastname: Dammann
authors.forename: Oliver
authors.initials: O
authors.lastname: Kraff
authors.forename: Karsten H
authors.initials: KH
authors.lastname: Wrede
authors.forename: Neriman
authors.initials: N
authors.lastname: Özkan
authors.forename: Stephan
authors.initials: S
authors.lastname: Orzada
authors.forename: Oliver M
authors.initials: OM
authors.lastname: Mueller
authors.forename: I Erol
authors.initials: IE
authors.lastname: Sandalcioglu
authors.forename: Ulrich
authors.initials: U
authors.lastname: Sure
authors.forename: Elke R
authors.initials: ER
authors.lastname: Gizewski
authors.forename: Mark E
authors.initials: ME
authors.lastname: Ladd
authors.forename: Thomas
authors.initials: T
authors.lastname: Gasser
mesh_terms: D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology* / Q000601:surgery*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000295:instrumentation*; D019635:Neurosurgical Procedures / Q000295:instrumentation*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000295:instrumentation*