Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Identifying hypometabolism in PET images of the brain: Application to epilepsy

  • Conference paper
  • First Online:
Visualization in Biomedical Computing (VBC 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1131))

Included in the following conference series:

  • 201 Accesses

Abstract

A technique for identifying hypometabolism from Positron Emission Tomography (PET) brain images, which accounts for patient-specific anatomical variations, scanner physical properties, and expected normal variances in metabolism, has been developed and used to identify unilateral temporal lobe seizure foci in epileptics. This method was able to distinguish the epileptogenic focus in three seizure patients with unilateral seizure onset, while demonstrating no hypometabolism in three patients with bilateral seizure onset or in the ten normal volunteers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Hoffman EJ, Huang SC, Phelps ME: Quantitation in positron computed emission tomography: 1. Effect of object size. J Comput Assist Tomog 3 (1979) 299–308.

    Google Scholar 

  2. Mazziotta JC, Phelps ME, Plummer D, Kuhl DE: Quantitation in positron emission computed tomography 5: Physical-anatomical effects. J Comput Assist Tomog 5 (1981) 734–743.

    Google Scholar 

  3. Henry TR, Engel JE, Mazziotta JC: Clinical evaluation of interictal fluorine-18-fluorodeoxyglucose PET in partial epilepsy. J Nuc Med 34 (1993) 1892–1898.

    Google Scholar 

  4. Serra J. Image Analysis and Mathematical Morphology, Academic Press, London, 1982.

    Google Scholar 

  5. Woods RP, Mazziotta JC, Cherry SR: MRI-PET registration with automated algorithm. J Comput Assist Tomog 17 (1993) 536–546.

    Google Scholar 

  6. Engel J, Henry TR, Risinger MW: Presurgical evaluation of partial epilepsy: Relative contributions of chronic depth electrode recordings vs. FDG PET and scalp-sphenoidal ictal EEG. Neurology 40 (1990) 1670–1677.

    Google Scholar 

  7. Swartz BE, Tomiyaso U, Delgado-Escuera AV, et al.: Neuroimaging in temporal lobe epilepsy: Test sensitivity and relationships to pathology and post-operative outcome. Epilepsia 33 (1992) 624–634.

    Article  Google Scholar 

  8. Radtke RA, Hanson MW, Hoffman JM, et al: Temporal lobe hypometabolism on PET: Predictor of seizure control after temporal lobectomy. Neurology 43 (1993) 1088–1092.

    Google Scholar 

  9. Jack CR, Sharbrough FW, Twomey CK, et al: Temporal lobe seizures: lateralization with MR volume measurements of hippocampal formation. Radiology 175 (1990) 423–429.

    Google Scholar 

  10. Jack CR, Sharbrough FW, Cascino GD, et al: Magnetic resonance image-based hippocampal volumetry: Correlation with outcome after temporal lobectomy. Annals of Neurology 31 (1992) 138–146.

    Article  Google Scholar 

  11. Kuzniecky R, de la Sayette V, Etheir R: Magnetic resonance imaging in temporal lobe epilepsy: pathological correlations. Ann Neurol. 22 (1987) 341–347.

    Article  Google Scholar 

  12. Jack CR, Twomey CK, Zinsmeister AR, et al.: Anterior temporal lobes and hippocampal formations: normative volumetric measurements from MR images in young adults. Radiology 172 (1989) 549–554.

    Google Scholar 

  13. Meltzer CC, Leal JP, Mayberg HS, et al.: Correction of PET data for detector response effects in human cerebral cortex by MR imaging. J Comput Assist Tomog 14 (1990) 561–570.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Karl Heinz Höhne Ron Kikinis

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Faber, T.L., Hoffman, J.M., Henry, T.R., Votaw, J.R., Brummer, M.E., Garcia, E.V. (1996). Identifying hypometabolism in PET images of the brain: Application to epilepsy. In: Höhne, K.H., Kikinis, R. (eds) Visualization in Biomedical Computing. VBC 1996. Lecture Notes in Computer Science, vol 1131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046986

Download citation

  • DOI: https://doi.org/10.1007/BFb0046986

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61649-8

  • Online ISBN: 978-3-540-70739-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics