Magnetic susceptibility-induced echo-time shifts: Is there a bias in age-related fMRI studies?
To evaluate the potential for bias in functional magnetic resonance imaging (fMRI) aging studies resulting from age-related differences in magnetic field distributions that can impact echo time and functional contrast.



Magnetic field maps were taken on 31 younger adults (age: 22 ± 2.9 years) and 46 older adults (age: 66 ± 4.5 years) on a 3T scanner. Using the spatial gradients of the magnetic field map for each participant, an echo planar imaging (EPI) trajectory was simulated. The effective echo time, time at which the k-space trajectory is the closest to the center of k-space, was calculated. This was used to examine both within-subject and across-age-group differences in the effective echo time maps. The blood oxygenation level-dependent (BOLD) percent signal change resulting from those echo time shifts was also calculated to determine their impact on fMRI aging studies.



For a single subject, the effective echo time varied as much as ±5 msec across the brain. An unpaired t-test between the effective echo time across age groups resulted in significant differences in several regions of the brain (P < 0.01). The difference in echo time was only ∼1 msec, however, which is not expected to have an important impact on BOLD fMRI percent signal change (<4%).



Susceptibility-induced magnetic field gradients induce local echo-time shifts in gradient echo fMRI images, which can cause variable BOLD sensitivity across the brain. However, the age-related differences in BOLD signal are expected to be small for an fMRI study at 3T.



1 J. Magn. Reson. Imaging 2017;45:207-214.
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Beckman Institute of Technology for Advanced Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Giang-Chau
GC
Ngo
Beckman Institute of Technology for Advanced Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Chelsea N
CN
Wong
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Beckman Institute of Technology for Advanced Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Steve
S
Guo
Beckman Institute of Technology for Advanced Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Illinois Informatics Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Thomas
T
Paine
Beckman Institute of Technology for Advanced Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Arthur F
AF
Kramer
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Beckman Institute of Technology for Advanced Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Bradley P
BP
Sutton
D000328:Adult; D000375:Aging / Q000502:physiology*; D016477:Artifacts; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D060526:Magnetic Fields; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult
BOLD; field inhomogeneity; functional imaging; gradient echo imaging; k-space distortions; magnetic susceptibility