Literature DB >> 31111981

Assessing effects of scanner upgrades for clinical studies.

Kathryn E Keenan1, Zydrunas Gimbutas2, Andrew Dienstfrey2, Karl F Stupic1.   

Abstract

BACKGROUND: Scanner upgrades due to software and hardware changes are an inevitable part of MR research and, without quality assurance protocols, can jeopardize studies.
PURPOSE: To evaluate changes in T1 relaxation time by inversion recovery (IR) and variable flip angle (VFA) measurements on a 3T system that underwent an "everything but the magnet" upgrade. STUDY TYPE: Longitudinal. PHANTOM: An International Society of Magnetic Resonance in Medicine / National Institute of Standards and Technology (ISMRM/NIST) system phantom with repeated measurements across multiple (n = 3) days. FIELD STRENGTH/SEQUENCE: T1 IR, VFA at 3T. ASSESSMENT: The T1 measurements by IR and VFA were compared with the nuclear magnetic resonance (NMR) measurements, which constitute the known values for the ISMRM/NIST system phantom, to determine the measurement error. STATISTICAL TESTS: Descriptive.
RESULTS: The T1 VFA measurement errors were distributed around zero (-15% to +10%) on the original system and then the errors were distributed entirely above zero post-upgrade (+5% to 30%). The T1 IR results had a dramatic increase in error distribution (±5% original, ±20% post-upgrade) prior to the identification of signal saturation as an issue. Once the signal saturation was accounted for, the T1 IR errors decreased to ±10% post-upgrade. DATA
CONCLUSION: The T1 VFA measurement differences between the original and post-upgrade systems can be entirely attributed to contributions from B1 . The T1 IR measurements demonstrate the need for quantitative quality assurance (QA) processes. The site under study passed the QA protocols in place, which did not identify the increased T1 error, nor the signal saturation issue. To improve on this study, we would make systematic, quantitative measurements at intervals less than a year and following any hardware or software upgrade. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2019;50:1948-1954. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.

Keywords:  T1; phantom; quantitative MRI; reference objects; standards

Year:  2019        PMID: 31111981     DOI: 10.1002/jmri.26785

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  6 in total

1.  Evaluation of diffusion-weighted MRI and geometric distortion on a 0.35T MR-LINAC at multiple gantry angles.

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Review 2.  Challenges in ensuring the generalizability of image quantitation methods for MRI.

Authors:  Kathryn E Keenan; Jana G Delfino; Kalina V Jordanova; Megan E Poorman; Prathyush Chirra; Akshay S Chaudhari; Bettina Baessler; Jessica Winfield; Satish E Viswanath; Nandita M deSouza
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3.  Confound modelling in UK Biobank brain imaging.

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Journal:  Neuroimage       Date:  2020-06-02       Impact factor: 6.556

4.  Multi-site, multi-platform comparison of MRI T1 measurement using the system phantom.

Authors:  Kathryn E Keenan; Zydrunas Gimbutas; Andrew Dienstfrey; Karl F Stupic; Michael A Boss; Stephen E Russek; Thomas L Chenevert; P V Prasad; Junyu Guo; Wilburn E Reddick; Kim M Cecil; Amita Shukla-Dave; David Aramburu Nunez; Amaresh Shridhar Konar; Michael Z Liu; Sachin R Jambawalikar; Lawrence H Schwartz; Jie Zheng; Peng Hu; Edward F Jackson
Journal:  PLoS One       Date:  2021-06-30       Impact factor: 3.240

5.  Influence of equipment changes on MRI measures of brain atrophy and brain microstructure in a placebo-controlled trial of ibudilast in progressive multiple sclerosis.

Authors:  Ken Sakaie; Janel K Fedler; Jon W Yankey; Kunio Nakamura; Josef Debbins; Mark J Lowe; Paola Raska; Robert J Fox
Journal:  Mult Scler J Exp Transl Clin       Date:  2021-05-18

Review 6.  Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence.

Authors:  Akifumi Hagiwara; Shohei Fujita; Yoshiharu Ohno; Shigeki Aoki
Journal:  Invest Radiol       Date:  2020-09       Impact factor: 10.065

  6 in total

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