CT—3D rotational angiography automatic registration: A sensitivity analysis

Abstract

Preprocessing, binning and dataset subsampling are investigated with regard to simultaneous maximisation of the speed, accuracy and robustness of CT-3D rotational angiography (3DRA) registration. Clinical diagnosis and treatment can both take advantage of this integration, because 3DRA allows the shape of vessel structures to be evaluated three-dimensionally with respect to standard 2D projective angiography. The method for optimising preprocessing, binning and subsampling consisted of independent variation of the corresponding parameters to maximise robustness and speed while maintaining subvoxel accuracy; the latter was computed as the sum of the mean squared errors initially present in the registrations with the errors relative to both binning and subsampling. The results suggest the choice of 256 bins, steps between 14 mm (coarse optimisation) and 2.5 mm (fine optimisation) and bone segmentation by threshold, for binning, subsampling and preprocessing, respectively. The application of this parameter set-up to 50 CT-3DRA registrations resulted in a saving, on average, of 40% of the time with respect to the method previously used, while registration error was maintained within 2 mm (1.97 mm, 90% confidence interval) and robustness was increased, so that no manual initial realignment was needed in 48 registrations. Validation by the registration of images acquired for a head phantom showed subvoxel residual errors. In conclusion, the proposed procedure can be considered a satisfactory strategy to optimise CT-3DRA registration.