A focus on brain region is gradually being supplemented by recognition of the importance of also exploring shape characteristics. Structural neuroimaging studies have provided invaluable insight into the normative development of the human brain and aetiology of neurodegeneration and disease. Elliptical Fourier analysis, particularly in combination with principal component analysis, is a powerful, assumption-free and intuitive method of quantifying global shape of the corpus callosum and shows great promise for shape analysis in neuroimaging more broadly.
Mixed effect model results indicated all methods detected similar features, but eFourier estimates were most predictive, and of the two shape operationalization techniques had the least error and better model fit. For the case study, volume, eFourier, and landmark measures were all correlated. The combination of eFourier and PCA performed particularly well in reconstructing known n-dimensional shape space but was disrupted by the inclusion of local shape manipulations. reconstructed from eFourier shapes was excellent ( M=0.98). We also compared the predictive performance of corpus callosum volume, position in Procrustes-aligned Landmark tangent space, and position in eFourier n-dimensional shape space in relation to the Symbol Digit Modalities Test. Performance of eFourier was benchmarked in terms of its capacity to capture and then reconstruct shape and systematically operationalise that shape via principal components analysis. 2088 real corpus callosum contours were manually traced from the PATH study. 8000 simulated corpus callosum contours were generated, systematically varying in terms of global shape (midbody arch, splenium size), local complexity (surface smoothness), and nonshape characteristics (e.g., rotation).
This paper evaluates the properties, performance, and utility of elliptical Fourier (eFourier) analysis to operationalise global shape, focussing on the human corpus callosum.
Shape analysis provides a unique insight into biological processes.
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