Literature DB >> 22684343

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

Joanna M Wardlaw1, Will Brindle, Ana M Casado, Kirsten Shuler, Moira Henderson, Brenda Thomas, Jennifer Macfarlane, Susana Muñoz Maniega, Katherine Lymer, Zoe Morris, Cyril Pernet, William Nailon, Trevor Ahearn, Abdul Nashirudeen Mumuni, Carlos Mugruza, John McLean, Goultchira Chakirova, Yuehui Terry Tao, Johanna Simpson, Andrew C Stanfield, Harriet Johnston, Jehill Parikh, Natalie A Royle, Janet De Wilde, Mark E Bastin, Nick Weir, Andrew Farrall, Maria C Valdes Hernandez.   

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.

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Year:  2012        PMID: 22684343     DOI: 10.1007/s00330-012-2500-8

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  56 in total

1.  High-resolution intracranial and cervical MRA at 3.0T: technical considerations and initial experience.

Authors:  M A Bernstein; J Huston; C Lin; G F Gibbs; J P Felmlee
Journal:  Magn Reson Med       Date:  2001-11       Impact factor: 4.668

2.  Time-of-flight MR angiography: comparison of 3.0-T imaging and 1.5-T imaging--initial experience.

Authors:  Winfried A Willinek; Markus Born; Birgit Simon; Henriette J Tschampa; Carsten Krautmacher; Jurgen Gieseke; Horst Urbach; Hans J Textor; Hans H Schild
Journal:  Radiology       Date:  2003-12       Impact factor: 11.105

3.  Does high-field MR imaging have an influence on the classification of patients with clinically isolated syndromes according to current diagnostic mr imaging criteria for multiple sclerosis?

Authors:  M P Wattjes; M Harzheim; C K Kuhl; J Gieseke; S Schmidt; L Klotz; T Klockgether; H H Schild; G G Lutterbey
Journal:  AJNR Am J Neuroradiol       Date:  2006-09       Impact factor: 3.825

4.  Reproducibility of functional MR imaging: preliminary results of prospective multi-institutional study performed by Biomedical Informatics Research Network.

Authors:  Kelly H Zou; Douglas N Greve; Meng Wang; Steven D Pieper; Simon K Warfield; Nathan S White; Sanjay Manandhar; Gregory G Brown; Mark G Vangel; Ron Kikinis; William M Wells
Journal:  Radiology       Date:  2005-12       Impact factor: 11.105

5.  A picture is worth a thousand dollars.

Authors:  Martha J Farah
Journal:  J Cogn Neurosci       Date:  2009-04       Impact factor: 3.225

6.  Detection of asymptomatic cerebral microbleeds: a comparative study at 1.5 and 3.0 T.

Authors:  Christoph Stehling; Heike Wersching; Stephan P Kloska; Paulus Kirchhof; Janine Ring; Isabelle Nassenstein; Thomas Allkemper; Stefan Knecht; Rainald Bachmann; Walter Heindel
Journal:  Acad Radiol       Date:  2008-07       Impact factor: 3.173

7.  Brain tumors: full- and half-dose contrast-enhanced MR imaging at 3.0 T compared with 1.5 T--Initial Experience.

Authors:  Carsten Krautmacher; Winfried A Willinek; Henriette J Tschampa; Mark Born; Frank Träber; Jürgen Gieseke; Hans J Textor; Hans H Schild; Christiane K Kuhl
Journal:  Radiology       Date:  2005-10-19       Impact factor: 11.105

8.  Improved image quality of intracranial aneurysms: 3.0-T versus 1.5-T time-of-flight MR angiography.

Authors:  Gordon F Gibbs; John Huston; Matt A Bernstein; Stephen J Riederer; Robert D Brown
Journal:  AJNR Am J Neuroradiol       Date:  2004-01       Impact factor: 3.825

9.  Comparison of multiple sclerosis lesions at 1.5 and 3.0 Tesla.

Authors:  Nancy L Sicotte; Rhonda R Voskuhl; Seth Bouvier; Rochelle Klutch; Mark S Cohen; John C Mazziotta
Journal:  Invest Radiol       Date:  2003-07       Impact factor: 6.016

10.  Fluid attenuated inversion recovery (FLAIR) imaging of the normal brain: comparisons between under the conditions of 3.0 Tesla and 1.5 Tesla.

Authors:  Chul-Ho Sohn; Robert J Sevick; Richard Frayne; Hyuk-Won Chang; Sang-Pyo Kim; Dae-Kwang Kim
Journal:  Korean J Radiol       Date:  2009-12-28       Impact factor: 3.500

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  30 in total

1.  Progressing Toward a Cohesive Pediatric 18F-FDG PET/MR Protocol: Is Administration of Gadolinium Chelates Necessary?

Authors:  Christopher Klenk; Rakhee Gawande; Vy Thao Tran; Jennifer Trinh Leung; Kevin Chi; Daniel Owen; Sandra Luna-Fineman; Kathleen M Sakamoto; Alex McMillan; Andy Quon; Heike E Daldrup-Link
Journal:  J Nucl Med       Date:  2015-10-15       Impact factor: 10.057

2.  Basolateral amygdala-ventromedial prefrontal cortex connectivity predicts cognitive behavioural therapy outcome in adults with obsessive-compulsive disorder.

Authors:  Miquel A Fullana; Xi Zhu; Pino Alonso; Narcís Cardoner; Eva Real; Clara López-Solà; Cinto Segalàs; Marta Subirà; Hanga Galfalvy; José M Menchón; H Blair Simpson; Rachel Marsh; Carles Soriano-Mas
Journal:  J Psychiatry Neurosci       Date:  2017-11       Impact factor: 6.186

3.  Dynamic 1.5-T vs 3-T true fast imaging with steady-state precession (trueFISP)-MRI sequences for assessment of velopharyngeal function.

Authors:  K Sinko; C Czerny; R Jagsch; A Baumann; C Kulinna-Cosentini
Journal:  Dentomaxillofac Radiol       Date:  2015-06-19       Impact factor: 2.419

4.  Life cycle costing as a decision making tool for technology acquisition in radio-diagnosis.

Authors:  Abhijit Chakravarty; Jyotindu Debnath
Journal:  Med J Armed Forces India       Date:  2014-11-24

5.  Assessment of reduced field of view in diffusion tensor imaging of the lumbar nerve roots at 3 T.

Authors:  Jean-François Budzik; Sébastien Verclytte; Guillaume Lefebvre; Aurélien Monnet; Gerard Forzy; Anne Cotten
Journal:  Eur Radiol       Date:  2012-11-18       Impact factor: 5.315

6.  Letter regarding "Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases".

Authors:  Estanislao Arana; Leoncio A Arribas
Journal:  Neuro Oncol       Date:  2020-11-26       Impact factor: 12.300

7.  Response to Letter to Editor.

Authors:  Timothy J Kaufmann; Marion Smits; Jerrold Boxerman; Raymond Huang; Daniel P Barboriak; Michael Weller; Caroline Chung; Christina Tsien; Paul D Brown; Lalitha Shankar; Evanthia Galanis; Elizabeth Gerstner; Martin J van den Bent; Terry C Burns; Ian F Parney; Gavin Dunn; Priscilla K Brastianos; Nancy U Lin; Patrick Y Wen; Benjamin M Ellingson
Journal:  Neuro Oncol       Date:  2020-11-26       Impact factor: 12.300

8.  Susceptibility-weighted imaging improves the diagnostic accuracy of 3T brain MRI in the work-up of parkinsonism.

Authors:  F J A Meijer; A van Rumund; B A C M Fasen; I Titulaer; M Aerts; R Esselink; B R Bloem; M M Verbeek; B Goraj
Journal:  AJNR Am J Neuroradiol       Date:  2014-10-22       Impact factor: 3.825

Review 9.  Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease.

Authors:  François De Guio; Eric Jouvent; Geert Jan Biessels; Sandra E Black; Carol Brayne; Christopher Chen; Charlotte Cordonnier; Frank-Eric De Leeuw; Martin Dichgans; Fergus Doubal; Marco Duering; Carole Dufouil; Emrah Duzel; Franz Fazekas; Vladimir Hachinski; M Arfan Ikram; Jennifer Linn; Paul M Matthews; Bernard Mazoyer; Vincent Mok; Bo Norrving; John T O'Brien; Leonardo Pantoni; Stefan Ropele; Perminder Sachdev; Reinhold Schmidt; Sudha Seshadri; Eric E Smith; Luciano A Sposato; Blossom Stephan; Richard H Swartz; Christophe Tzourio; Mark van Buchem; Aad van der Lugt; Robert van Oostenbrugge; Meike W Vernooij; Anand Viswanathan; David Werring; Frank Wollenweber; Joanna M Wardlaw; Hugues Chabriat
Journal:  J Cereb Blood Flow Metab       Date:  2016-05-11       Impact factor: 6.200

10.  A naturalistic neuroimaging database for understanding the brain using ecological stimuli.

Authors:  Sarah Aliko; Jiawen Huang; Florin Gheorghiu; Stefanie Meliss; Jeremy I Skipper
Journal:  Sci Data       Date:  2020-10-13       Impact factor: 6.444

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