Quantitative and clinical analysis of SPECT image registration for epilepsy studies

This study reports quantitative measurements of the accuracy of two popular voxel-based registration algorithms-Woods' automated image registration algorithm and mutual information correlation-and compares these with conventional surface matching (SM) registration. Methods: The registration algorithms were compared (15 different matches each) for (a) three-dimensional brain phantom images, (b) an ictal SPECT image from a patient with partial epilepsy matched to itself after modification to simulate changes in the cerebral blood flow pattern and (c) ictal/interictal SPECT images from 15 patients with partial epilepsy. Blinded visual ranking and localization of the subtraction images derived from the patient images were also performed. Results: Both voxel-based registration methods were more accurate than SM registration (P < 0.0005). Automated image registration algorithm was more accurate than mutual information correlation for the computer-simulated ictal/interictal images and the patient ictal/interictal studies (P < 0.05). The subtraction SPECTs from SM were poorer in visual ranking more often than the voxel-based methods (P < 0.05). Conclusion: Voxel intensity-based registration algorithms provide significant improvement in ictal/interictal SPECT registration accuracy and result in a clinically detectable improvement in the subtraction SPECT images.