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Computer-Aided Intrapatient Comparison of Brain SPECT Images: The Gray-Level Normalization Issue Applied to Children with Epilepsy

¹ Nuclear Medicine and Biophysics Unit, Jean Godinot Institute, Reims, France
² Department of Nuclear Medicine, Rouen University Hospital and Henri Becquerel Center, Rouen, France
³ Department of Neuropediatrics, Saint Vincent de Paul Hospital, Paris, France
⁴ Unit 29, Institut National de la Santé et de la Recherche Médicale, Marseille, France
⁵ Department of Neurology and Neurosurgery, Reims University Hospital, Reims, France

A tool was developed for automated intrapatient comparison of brain SPECT images, with specific emphasis on gray-level normalization. Methods: Ictal and interictal ^99mTc-ethyl cysteinate dimer SPECT images were acquired for 6 children with partial epilepsy (age range, 2–10 y). For each patient, 3-dimensional rigid geometric ictal-to-interictal image registration optimizing different classic criteria (correlation coefficient, ratio uniformity) in a multiscale translation–rotation 6-parameter space was first performed. Gray-level normalization was then performed with different methods, using a 1- or 2-parameter linear model. In the 1-parameter case, the scaling factor was equal to the interictal-to-ictal ratio of the maximum, mean, or median values calculated within different reference volumes (whole brain or cerebellum) or obtained by linear regression between ictal and interictal counts in the brain or by maximizing a robust criterion, the number of deterministic sign changes in the subtraction images. In the 2-parameter case, the scaling factor and additive constant were estimated using these last 2 methods. For each patient, registration validity and normalization plausibility were assessed by considering the correlation scatterplot together with the different normalization lines and by comparing interictal and registered normalized ictal images using a twin display (with isocontours) in the 3 orthogonal planes. Three-dimensional volumes of interest could be selected on coupled interictal–subtraction images for further focused numeric comparison. Results: After a satisfactory and stable geometric registration with both criteria, the different normalization methods led to similar subtraction images for 5 of 6 patients, except the maxima ratio, which gave noticeably different results in 2 patients. For the remaining patient, with highly dissimilar ictal–interictal images, the maxima ratio normalization was obviously wrong and the other 1-parameter methods probably better depicted the data than did the 2-parameter methods. Conclusion: When comparing intrapatient brain SPECT images, one should be aware of the potential impact of the gray-level normalization method on clinical interpretation. For ictal–interictal images, simple robust scaling should be recommended. In particular, image maximum should generally not be considered a valid reference, and no additive constant is needed in the linear gray-level normalization model.

Key Words: image comparison • image normalization • SPECT • brain • epilepsy

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				R. C. Knowlton, N. D. Lawn, J. M. Mountz, and R. I. Kuzniecky Ictal SPECT analysis in epilepsy: Subtraction and statistical parametric mapping techniques Neurology, July 13, 2004; 63(1): 10 - 15. [Abstract] [Full Text] [PDF]