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Automated Detection of Local Normalization Areas for Ictal-Interictal Subtraction Brain SPECT

¹ Équipe d’Accueil 1880, Functional Neurology and Epilepsy Unit, Neuro-Cardiological Hospital, Lyon, France
² Nuclear Medicine Center, Neuro-Cardiological Hospital, Lyon, France
³ CERMEP (PET Center), Neuro-Cardiological Hospital, Lyon, France

Whole-brain activity is often chosen to quantitatively normalize peri-ictal and interictal SPECT scans before their subtraction. This use is not justified, because significant and extended modification of the cerebral blood flow can occur during a seizure. We validated and compared 2 automatic methods able to determine the optimal reference region, using simulation and clinical data. Methods: In the first method, the selected reference region is the intersection of peri-ictal-interictal areas with no significantly different z values. The other method relies on a 3-dimensional iterative voxel aggregation. The increase of the selected volume is stopped by using 2 different variance tests (Levene and SE). These algorithms were tested on 39 epileptic patients and were validated using 1 interictal and 10 peri-ictal scans simulated from the mean image of 22 healthy subjects. Results: In the patient studies, the mean relative activity of the selected regions, compared with whole-brain activity (classic normalization), was 122.6%. Their average relative size (compared with the size of the whole brain) was 33.2% for the z map method, 22.8% for the SE test, and 11.8% for the Levene test. After application of our automatic processes, subtraction of the simulated images revealed a recovery of abnormal regions up to 45% larger than the region obtained with classic normalization. Conclusion: These results illustrate the role of normalization on the subtracted peri-ictal and interictal images. Our methods are automatic and objective and give good results on various simulated images. The z map construction is worth considering because it is simple, selects large parts of the brain, and requires little computation time.

Key Words: epilepsy • peri-ictal SPECT • difference images • quantitative normalization

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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]