Interpreting scan data acquired from multiple scanners: A study with Alzheimer's disease

Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, London, UK.
NeuroImage (Impact Factor: 6.36). 03/2008; 39(3):1180-5. DOI: 10.1016/j.neuroimage.2007.09.066
Source: PubMed


Large, multi-site studies utilizing MRI-derived measures from multiple scanners present an opportunity to advance research by pooling data. On the other hand, it remains unclear whether or not the potential confound introduced by different scanners and upgrades will devalue the integrity of any results. Although there are studies of scanner differences for the purpose of calibration and quality control, the current literature is devoid of studies that describe the analysis of multi-scanner data with regard to the interaction of scanner(s) with effects of interest. We investigated a data-set of 136 subjects, 62 patients with mild to moderate Alzheimer's disease and 74 cognitively normal elderly controls, with MRI scans from one center that were acquired over 10 years with 6 different scanners and multiple upgrades over time. We used a whole-brain voxel-wise analysis to evaluate the effect of scanner, effect of disease, and the interaction of scanner and disease for the 6 different scanners. The effect of disease in patients showed the expected significant reduction of grey matter in the medial temporal lobe. Scanner differences were substantially less than the group differences and only significant in the thalamus. There was no significant interaction of scanner with disease group. We describe the rationale for concluding that our results were not confounded by scanner differences. Similar analyses in other multi-scanner data-sets could be used to justify the pooling of data when needed, such as in studies of rare disorders or in multi-center designs.

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Available from: Kewei Chen
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    • "Finally, the variable scanner (binary-coded as scanner 1/2) was included to account for possible sensitivity differences between the two MRI scanners. It has been shown that modeling different scanners can effectively account for scanner variance in VBM and does not affect contrasts of interest (Stonnington et al., 2008). The minimum gray matter density was set to .10. "
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    • "Finally, the variable scanner (binary-coded as scanner 1/2) was included to account for possible sensitivity differences between the two MRI scanners. It has been shown that modeling different scanners can effectively account for scanner variance in VBM and does not affect contrasts of interest (Stonnington et al., 2008). The minimum gray matter density was set to .10. "

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    • "Another limitation is the scanner upgrade midway, which is not modeled into our analysis. Even though there were minor cohort differences across the two scanners in some of demographic parameters, previous studies have suggested that when vendor, field strength, and acquisition parameters remained unchanged, data collected during scanner upgrades could be pooled (19). Another study (35) concluded that scanner upgrade did not increase the measurement variability nor introduce bias and that applying smoothing filters (which we have done with 10 mm FWHM Gaussian kernel) on the raw thickness maps can substantially reduce that thickness measurement variability. "
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