European Radiology

, Volume 22, Issue 11, pp 2295–2303

A systematic review of the utility of 1.5 versus 3 Tesla magnetic resonance brain imaging in clinical practice and research

Authors

    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
    • SINAPSE Collaboration, Brain Research Imaging Centre, Division of Clinical NeurosciencesWestern General Hospital
  • Will Brindle
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Ana M. Casado
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Kirsten Shuler
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Moira Henderson
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Brenda Thomas
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Jennifer Macfarlane
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • University of Dundee
  • Susana Muñoz Maniega
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Katherine Lymer
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Zoe Morris
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Cyril Pernet
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • William Nailon
    • Edinburgh Cancer CentreUniversity of Edinburgh
  • Trevor Ahearn
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Institute of Medical SciencesUniversity of Aberdeen
  • Abdul Nashirudeen Mumuni
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Department of Clinical PhysicsUniversity of Glasgow
  • Carlos Mugruza
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • School of PsychologyUniversity of Dundee
  • John McLean
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Institute of Neurological SciencesUniversity of Glasgow
  • Goultchira Chakirova
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of PsychiatryUniversity of Edinburgh
  • Yuehui (Terry) Tao
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Johanna Simpson
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Department of PsychologyUniversity of Stirling
  • Andrew C. Stanfield
    • Division of PsychiatryUniversity of Edinburgh
  • Harriet Johnston
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Department of PsychologyUniversity of St Andrews
  • Jehill Parikh
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Natalie A. Royle
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Janet De Wilde
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
    • The Higher Education Academy
  • Mark E. Bastin
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Nick Weir
    • Department of Medical PhysicsRoyal Infirmary of Edinburgh
  • Andrew Farrall
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • Maria C. Valdes Hernandez
    • Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration
    • Division of Clinical NeurosciencesUniversity of Edinburgh
  • The SINAPSE Collaborative Group
Magnetic Resonance

DOI: 10.1007/s00330-012-2500-8

Cite this article as:
Wardlaw, J.M., Brindle, W., Casado, A.M. et al. Eur Radiol (2012) 22: 2295. doi:10.1007/s00330-012-2500-8

Abstract

Objective

MRI at 3 T is said to be more accurate than 1.5 T MR, but costs and other practical differences mean that it is unclear which to use.

Methods

We systematically reviewed studies comparing diagnostic accuracy at 3 T with 1.5 T. We searched MEDLINE, EMBASE and other sources from 1 January 2000 to 22 October 2010 for studies comparing diagnostic accuracy at 1.5 and 3 T in human neuroimaging. We extracted data on methodology, quality criteria, technical factors, subjects, signal-to-noise, diagnostic accuracy and errors according to QUADAS and STARD criteria.

Results

Amongst 150 studies (4,500 subjects), most were tiny, compared old 1.5 T with new 3 T technology, and only 22 (15 %) described diagnostic accuracy. The 3 T images were often described as “crisper”, but we found little evidence of improved diagnosis. Improvements were limited to research applications [functional MRI (fMRI), spectroscopy, automated lesion detection]. Theoretical doubling of the signal-to-noise ratio was not confirmed, mostly being 25 %. Artefacts were worse and acquisitions took slightly longer at 3 T.

Conclusion

Objective evidence to guide MRI purchasing decisions and routine diagnostic use is lacking. Rigorous evaluation accuracy and practicalities of diagnostic imaging technologies should be the routine, as for pharmacological interventions, to improve effectiveness of healthcare.

Key Points

Higher field strength MRI may improve image quality and diagnostic accuracy.

There are few direct comparisons of 1.5 and 3 T MRI.

Theoretical doubling of the signal-to-noise ratio in practice was only 25 %.

Objective evidence of improved routine clinical diagnosis is lacking.

Other aspects of technology improved images more than field strength.

Keywords

Magnetic resonance imagingSensitivity and specificityBrainNeuroimagingSystematic review

Supplementary material

330_2012_2500_MOESM1_ESM.doc (664 kb)
ESM 1(DOC 658 kb)

Copyright information

© European Society of Radiology 2012