Left-Right Intensity Asymmetries Vary Depending on Scanner Model for FLAIR and T Weighted MRI Images

Overview

Journal J Magn Reson Imaging

Date 2022 Feb 8

PMID 35133061

Authors

Arvin Arani

Christopher G Schwarz

Heather J Wiste

Stephen D Weigand

Petrice M Cogswell

Matthew C Murphy

Joshua D Trzasko

Jeffrey L Gunter

Matthew L Senjem

Kiaran P McGee

Yunhong Shu

Matt A Bernstein

John Huston 3rd

Clifford R Jack Jr

Affiliations

Soon will be listed here.

Abstract

Background: Localized regions of left-right image intensity asymmetry (LRIA) were incidentally observed on T -weighted (T -w) and T -weighted (T -w) diagnostic magnetic resonance imaging (MRI) images. Suspicion of herpes encephalitis resulted in unnecessary follow-up imaging. A nonbiological imaging artifact that can lead to diagnostic uncertainty was identified.

Purpose: To investigate whether systematic LRIA exist for a range of scanner models and to determine if LRIA can introduce diagnostic uncertainty.

Study Type: A retrospective study using the Alzheimer's Disease Neuroimaging Initiative (ADNI) data base.

Subjects: One thousand seven hundred fifty-three (median age: 72, males/females: 878/875) unique participants with longitudinal data were included.

Field Strength: 3T.

Sequences: T -w three-dimensional inversion-recovery spoiled gradient-echo (IR-SPGR) or magnetization-prepared rapid gradient-echo (MP-RAGE) and T -w fluid-attenuated inversion recovery (FLAIR) long tau fast spin echo inversion recovery (LT-FSE-IR). Only General Electric, Philips, and Siemens' product sequences were used.

Assessment: LRIA was calculated as the left-right percent difference with respect to the mean intensity from automated anatomical atlas segmented regions. Three neuroradiologists with 37 (**), 32 (**), and 3 (**) years of experience rated the clinical impact of 30 T -w three-dimensional FLAIR exams with LRIA to determine the diagnostic uncertainty. Statistical comparisons between retrospective intensity normalized T m and original T -w images were made.

Statistical Tests: For each image type, a linear mixed effects model was fit using LRIA scores from all scanners, regions, and participants as the outcome and age and sex as predictors. Statistical significance was defined as having a P-value <0.05.

Results: LRIA scores were significantly different from zero on most scanners. All clinicians were uncertain or recommended definite diagnostic follow-up in 62.5% of cases with LRIA >10%. Individuals with acute brain pathology or focal neurologic deficits are not enrolled in ADNI; therefore, focal signal abnormalities were considered false positives.

Data Conclusion: LRIA is system specific, systematic, creates diagnostic uncertainty, and impacts IR-SPGR, MP-RAGE, and LT-FSE-IR product sequences.

Level Of Evidence: 2 Technical Efficacy Stage: 3.

Citing Articles

Clinical Evaluation of a Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis.

Rebsamen M, Jin B, Klail T, De Beukelaer S, Barth R, Rezny-Kasprzak B Clin Neuroradiol. 2023; 33(4):1045-1053.

PMID: 37358608 PMC: 10654177. DOI: 10.1007/s00062-023-01308-9.

References

Sled J, Pike G . Standing-wave and RF penetration artifacts caused by elliptic geometry: an electrodynamic analysis of MRI. IEEE Trans Med Imaging. 1998; 17(4):653-62. DOI: 10.1109/42.730409. View

Sled J, Zijdenbos A, Evans A . A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. 1998; 17(1):87-97. DOI: 10.1109/42.668698. View

Roberts R, Geda Y, Knopman D, Cha R, Pankratz V, Boeve B . The Mayo Clinic Study of Aging: design and sampling, participation, baseline measures and sample characteristics. Neuroepidemiology. 2008; 30(1):58-69. PMC: 2821441. DOI: 10.1159/000115751. View

Yushkevich P, Avants B, Das S, Pluta J, Altinay M, Craige C . Bias in estimation of hippocampal atrophy using deformation-based morphometry arises from asymmetric global normalization: an illustration in ADNI 3 T MRI data. Neuroimage. 2009; 50(2):434-45. PMC: 2823935. DOI: 10.1016/j.neuroimage.2009.12.007. View

Jack Jr C, Bernstein M, Fox N, Thompson P, Alexander G, Harvey D . The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging. 2008; 27(4):685-91. PMC: 2544629. DOI: 10.1002/jmri.21049. View

Jones R, Witte R . Signal intensity artifacts in clinical MR imaging. Radiographics. 2000; 20(3):893-901. DOI: 10.1148/radiographics.20.3.g00ma19893. View

Avants B, Epstein C, Grossman M, Gee J . Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal. 2007; 12(1):26-41. PMC: 2276735. DOI: 10.1016/j.media.2007.06.004. View

Ashburner J, Friston K . Unified segmentation. Neuroimage. 2005; 26(3):839-51. DOI: 10.1016/j.neuroimage.2005.02.018. View

Sili U, Kaya A, Mert A . Herpes simplex virus encephalitis: clinical manifestations, diagnosis and outcome in 106 adult patients. J Clin Virol. 2014; 60(2):112-8. DOI: 10.1016/j.jcv.2014.03.010. View

10.

Foo T, Hayes C, Kang Y . Reduction of RF penetration effects in high field imaging. Magn Reson Med. 1992; 23(2):287-301. DOI: 10.1002/mrm.1910230209. View

11.

Jovicich J, Czanner S, Greve D, Haley E, van der Kouwe A, Gollub R . Reliability in multi-site structural MRI studies: effects of gradient non-linearity correction on phantom and human data. Neuroimage. 2005; 30(2):436-43. DOI: 10.1016/j.neuroimage.2005.09.046. View

12.

Bernstein M, Huston 3rd J, Ward H . Imaging artifacts at 3.0T. J Magn Reson Imaging. 2006; 24(4):735-46. DOI: 10.1002/jmri.20698. View

13.

Vovk U, Pernus F, Likar B . A review of methods for correction of intensity inhomogeneity in MRI. IEEE Trans Med Imaging. 2007; 26(3):405-21. DOI: 10.1109/TMI.2006.891486. View

14.

Jack Jr C, Bernstein M, Borowski B, Gunter J, Fox N, Thompson P . Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative. Alzheimers Dement. 2010; 6(3):212-20. PMC: 2886577. DOI: 10.1016/j.jalz.2010.03.004. View

15.

Tao S, Trzasko J, Shu Y, Huston 3rd J, Bernstein M . Integrated image reconstruction and gradient nonlinearity correction. Magn Reson Med. 2014; 74(4):1019-31. PMC: 4390402. DOI: 10.1002/mrm.25487. View

16.

Ullmann P, Junge S, Wick M, Seifert F, Ruhm W, Hennig J . Experimental analysis of parallel excitation using dedicated coil setups and simultaneous RF transmission on multiple channels. Magn Reson Med. 2005; 54(4):994-1001. DOI: 10.1002/mrm.20646. View

17.

McVeigh E, Bronskill M, Henkelman R . Phase and sensitivity of receiver coils in magnetic resonance imaging. Med Phys. 1986; 13(6):806-14. PMC: 2396267. DOI: 10.1118/1.595967. View