To account for these factors, we used the volume of regions as reported in [6] and the initial score as two additional explanatory variables (covariates) of measured score improvements, in addition to the score improvements predicted by the SVR analysis.
The volume of regions of the striatum had the same relationship with carrier status as thalamic volume in one study [ 2], but this was not significantly replicated in the other study [ 1].
Finally, a higher number of CVD risk factors were associated with smaller regional white matter volumes of Region 2 (r s = −0.235, P = 0.005) and poorer performance on the TMT-A (r s = 0.174, P = 0.037).
The mean volumes of Region 3 and Region 4 were 0.038 cm3 and 0.92 cm3 respectively (see Table 3).
Level of education was positively associated with grey matter volumes of Region 1 (r s = 0.424, P = 0.000), white matter volumes of the Region 2 (r s = 0.437, P = 0.000), and CVD risk factors (r s = 0.185, P = 0.026).
From our sample, we analysed 9 patients with small subcortical lesions where the mean volumes of Region 1 and Region 2 were 0.40 cm3 and 0.34 cm3 respectively.
Microdebriders with different curvatures were placed through MMAson eight cadavers, and the surface area and volume of the region accessible to each microdebrider tip was calculated.
Here, we propose a simple approach to constructing time activity curves (TACs) for four different brain structures (the arterial & venous regions and grey & white matter) based on direct image measurements on chronologically reconstructed image volumes of regions of interest.
Volumes of regions of the state space are associated with the dimensionality of the smallest subspace containing the region, and an analogue of Liouville's Theorem holds for unitary evolution (doubly stochastic transitions may increase, but cannot decrease, this state space volume).
