Simultaneous surface registration of ictal and interictal SPECT and magnetic resonance images for epilepsy studies.
BACKGROUND
Subtraction of ictal and interictal single photon emission computed tomography (SPECT) images is known to be successful in localizing the seizure focus in the pre-surgical evaluation of patients with partial epilepsy. A computer-aided methods for producing subtraction ictal SPECT co-registered to the magnetic resonance image (MRI) (the SISCOM method) is commonly used. The two registrations involved in SISCOM are (1) between the ictal-interictal SPECT images, which was shown to be the more critical, and (2) between the ictal image and MRI.


OBJECTIVE
To improve the accuracy of ictal-interictal registration in SISCOM by registering all three images (ictal, interictal SPECT, MRI) simultaneously.


METHODS
The registration problem is formulated as the minimization of a cost function between three surfaces. Then, to achieve a global minimum of this cost function, the Powell algorithm with randomly distributed initial configurations is used. This technique is tested by a realistic simulation study, a phantom study and a patient study.


RESULTS
The results of the simulation study demonstrate that, in surface-based registration, the triple-registration method results in a smaller ictal-interictal SPECT registration error than the pair-wise registration method (P<0.05) for a range of values of the cost-function parameter. However, the improved registration error is still larger than that obtained by the normalized mutual information method (P<0.001), which is a voxel-based registration algorithm. The phantom and patient studies reveal no observable difference between registration results.


CONCLUSIONS
Although the improved accuracy of triple registration is slightly worse than voxel-based registration, it will soon be possible to apply the results of this study in research utilizing the triple-registration principle to improving voxel-based results of ictal-interictal registration.
Mumcuoğlu
Erkan U
EU
Informatics Institute, Middle East Technical University, Ankara, Turkey. merkan@metu.edu.tr
Nar
Fatih
F
Yardimci
Yasemin
Y
Koçak
Umut
U
Ergün
Eser Lay
EL
Salanci
Bilge Volkan
BV
Uğur
Omer
O
Erbaş
Belkis
B
D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology; D003198:Computer Simulation; D004827:Epilepsy / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*