Computer-aided subtraction of the co-registered and normalized interictal from the ictal single photon emission tomography (SPET) scan, followed by co-registration to the magnetic resonance image, may improve the utility of ictal SPET in the localization of partial epilepsy. This paper describes and technically validates our method. The SPET to SPET co-registration was tested using six sequential 99Tcm brain phantom SPET images of different known positions (15 matches). The registration error was determined by multiplying the calculated match transformation matrix by the inverse of the known transformation matrix. The ‘worst case’ co-registration error was less that one voxel diameter in all cases (median 3.2 mm, range 1.2-4.8 mm). For interictal to ictal SPET registrations in 10 consecutive intractable partial epilepsy patients, a similar root mean square distance (RMSD) between corresponding points on the matched scans was found as for the phantom studies (median 2.2 vs 2.6 mm). The appropriateness of our normalization was studied by comparing the pixel intensity distributions between the matched scans, and by analysing the subtraction pixel intensity distribution. The pixel intensity distribution for both the normalized phantom, and paired normalized patient studies, were closely matched to each other except for the extreme values, which in clinical situations likely represent regions of ictal activation or depression. The subtraction image intensity distributions were symmetrically centred on zero for all values up to at least within the 5th to 95th centile range, confirming good normalization for the ‘non-activated’ pixels. Also, a linear relationship was demonstrated between the measured pixel intensity on the phantom scans and the true changes in 99Tcm activity based on its decay constant. The results of this study demonstrate that our method produces accurate SPET to SPET co-registration, and appropriate SPET normalization, thereby allowing a valid ictal subtraction image to be derived.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging