The specific goals of this work were to identify potential vendor-dependent systematic differences in quantitative FSE-T2 maps of the ACR phantom and human brain and to study FSE-T2 histogram properties across the spectrum of normal aging, MCI, and AD. Significant overall differences were found between scanner vendors across the FSE-T2 histogram derived parameters in both phantom and human studies. Follow up analysis showed that Siemens had higher FSE-T2 peak values and broader histograms than GE and Philips. Measurements were not statistically significant between diagnostic groups when accounting for scanner vendor, which decreased the effective sample size per group to between 7 and 18 subjects. The small sample size within vendors may partially account for there not being a significant difference between peak FSE-T2 of AD, MCI, and normal aging subjects.
The trends between NL, MCI, and AD, suggest a scanner vendor-disease interaction effect, such that the trend for FSE-T2 between normal aging, MCI, and AD was inconsistent between vendors (i.e. normal aging from one vendor produced prolonged T2 compared to AD, while in another vendor we observed the opposite trend). These interactions are most concerning and will need to be verified with a larger sample. If true, this suggests that combining data from different vendors in one analysis, even when using co-factors, will end up masking the underlying effect.
Peak FSE-T2 was shown to correlate with age, consistent with the results of a previously published study (Laakso et al., 1996
). Histogram width correlated with GD scale. Histogram width reflects water environment inhomogeneity (Whittall et al., 1997
), indicating that brain tissue becomes more heterogeneous as the severity of dementia measured by the GD scale increases.
Variability between sites indicates that there was a larger degree of variance between GE and Siemens sites. The variability between sites using GE scanners was also observed in the phantom scans. Although GE was the only vendor for which the phantom was scanned on more than one platform. Additional phantom scans on Philips and Siemens platforms would be useful to help confirm the degree of variance between scanners.
Peak FSE-T2, for both phantom and human subjects, was at least 20–30ms prolonged with Siemens’ histograms compared to GE and Philips. The FSE pulse sequences used in the ADNI were not standardized between research sites, consistent with protocols of many other large scale studies including the Framingham Heart Study (DeCarli et al., 2005
), MIRAGE (Cuenco et al., 2008
), and many clinical drug trials.
This study poses a few limitations related to pulse sequence parameters and scanner hardware and software. Because the sequences were not completely standardized between all platforms, some scans were acquired with different effective TE or ETL. The signal intensity with T2 is primarily controlled by echo time. Effective TE may differ between vendors based on the k-space acquisition scheme, which may have induced some of the observed scanner-related variance. Much of the inaccuracy of FSE-T2 is due to stimulated echo, which is affected by both ETL (turbo factor) and echo spacing. The observed difference in FSE-T2 may be inherent to the vendor-specific scheme used to acquire k-lines with the fast spin echo readout, slice profile, and phase encoding order. Other factors, such as the coils, B0 and B1 inhomogeneities (Majumdar et al., 1986b
, Poon and Henkelman 1992
), RF pulse imperfections (Majumdar et al., 1986a
), and temperature variations, could also contribute to the scanner-related variance.
Whole brain histogram-derived FSE-T2 measures may not be sensitive enough to detect AD-related changes; however, T2 has been shown to regionally differ in AD and MCI compared to normal aging (Englund et al., 1987
; Kirsch et al., 1992
; Laakso et al., 1996
; Pitkanen et al., 1996
; Parsey et al., 1998
; Wang et al., 2004
; Schenck et al., 2006
; Arfanakis et al., 2007
). A potential area for future research is to examine T2 relaxation times using voxel-based relaxometry (VBR), which has been used to show T2 changes in autism (Hendry et al., 2006
), epilepsy (Pell et al., 2004
; Pell et al., 2008
) and multiple system atrophy of the cerebellar type (Specht et al., 2005
, Minnerop et al., 2007
Future studies that seek to utilize quantitative FSE-T2 measures will need to standardize the pulse sequence across scanners or devise a post-processing method to standardize measures. Alternatively, small fluid-filled objects with known T2 values could be scanned alongside each subjects’ head to provide reference signal (House et al., 2006
). Using other sequences may also help us to understand some of the differences between how each vendor handles the processing of T2 based imaging, but since these are not generally used in multi-site studies it is difficult to say how this will help us to understand the differences we have found using the FSE sequence.
This study used MRI and neuropsychological test ADNI data across NL, MCI and AD subjects. MRI data acquired with GE, Philips, and Siemens scanners to examine which properties of FSE-T2 quantitative MRI may be useful for the classification of MCI and early AD. Significant quantitative FSE-T2 differences were found between vendors in peak FSE-T2 and histogram width. The results herein suggest that FSE-T2 histogram measures can vary significantly with scanner vendor. Specifically, Siemens data consistently produced higher peak FSE-T2 values and broader histogram widths than either GE or Philips. The second purpose was to examine T2 histograms within normal aging, MCI, and AD over the whole brain. Few significant differences were found between diagnostic groups and the observed trends were inconsistent amongst the represented vendors, suggesting a potential scanner-disease interaction. The differences in scanner overshadowed the potential influence of subject diagnostic group on FSE-T2 measures. Significant correlations between peak FSE-T2 and FSE-T2 histogram width with global scale of dementia and measures of memory and cognitive functioning were observed.
To the authors’ knowledge, a multi-site study involving quantitative FSE-T2 datasets from GE, Philips, and Siemens has not been reported in previous literature. The results obtained in this study should serve to encourage increased quality control for measures of FSE-T2 related scans in large-scale studies utilizing data from multiple scanner platforms. They also point out potential differential effects of scanner brand that may not be adequately controlled by adding a co-variate to a statistical analysis.