Bias in estimation of hippocampal atrophy using deformation-based morphometry arises from asymmetric global normalization: An illustration in ADNI 3 T MRI data

Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
NeuroImage (Impact Factor: 6.36). 12/2009; 50(2):434-45. DOI: 10.1016/j.neuroimage.2009.12.007
Source: PubMed


Measurement of brain change due to neurodegenerative disease and treatment is one of the fundamental tasks of neuroimaging. Deformation-based morphometry (DBM) has been long recognized as an effective and sensitive tool for estimating the change in the volume of brain regions over time. This paper demonstrates that a straightforward application of DBM to estimate the change in the volume of the hippocampus can result in substantial bias, i.e., an overestimation of the rate of change in hippocampal volume. In ADNI data, this bias is manifested as a non-zero intercept of the regression line fitted to the 6 and 12 month rates of hippocampal atrophy. The bias is further confirmed by applying DBM to repeat scans of subjects acquired on the same day. This bias appears to be the result of asymmetry in the interpolation of baseline and followup images during longitudinal image registration. Correcting this asymmetry leads to bias-free atrophy estimation.

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    • "We notice that all the images undergo only one interpolation, and are therefore consistently processed in order to not introduce biases on the intensities due to asymmetric resamplings (Yushkevich et al., 2010). "

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    • "Longitudinal processing involved registration of each participantʼs image from the second measurement time point (follow-up scan) to his or her image from the first measurement time point (baseline scan). To avoid potential bias resulting from asymmetric interpolation (see, e.g., Fox, Ridgway, & Schott, 2011), the linear transformation between the follow-up and the baseline image was split halfway between the two images according to the approach described by Yushkevich et al. (2010). The symmetric linear transformations from the respective images to the halfway space were then used to initialize the nonlinear registration of the follow-up to the baseline image. "
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