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Temporal epilepsy lesions may be detected by the voxel-based quantitative analysis of brain FDG-PET images using an original block-matching normalization software

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Abstract

Introduction

Statistical parametric mapping (SPM) provides useful voxel-by-voxel analyses of brain images from 18F-fluorodesoxyglucose positron emission tomography (FDG-PET) after an initial step of spatial normalization through an anatomical template model. In the setting of the preoperative workup of patients with temporal epilepsy, this study aimed at assessing a block-matching (BM) normalization method, where most transformations are computed through small blocks, a principle that minimizes artefacts and overcomes additional image-filtering.

Methods

Brain FDG-PET images from 31 patients with well-characterised temporal lobe epilepsy and among whom 22 had common mesial temporal lobe epilepsy were retrospectively analysed using both BM and conventional SPM normalization methods and with PET images from age-adjusted controls. Different threshold p values corrected for cluster volume were considered (0.01, 0.005, and 0.001).

Results

The use of BM provided equivalent values to those of SPM with regard to the overall volumes of temporal and extra-temporal hypometabolism, as well as similar sensitivity for detecting the involved temporal lobe, reaching 87 and 94 % for SPM and BM, respectively, at a threshold p value of 0.01. However, the ability to more accurately localize brain lesions within the mesial portion of the temporal lobe was a little higher with BM than with SPM with respective sensitivities reaching 78 % for BM and 45 % for SPM (p < 0.05).

Conclusions

BM normalization compares well with conventional SPM for the voxel-based quantitative analysis of the FDG-PET images from temporal epilepsy patients. Further studies in different population are needed to determine whether BM is truly an accurate alternative to SPM in this setting.

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Authors and Affiliations

  1. Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHU-Nancy, 54000, Nancy, France

    Antoine Verger, Yalcin Yagdigul, Axel Van Der Gucht, Sylvain Poussier, Gilles Karcher & Pierre-Yves Marie

  2. INSERM, IADI U947, 5400, Nancy, France

    Antoine Verger

  3. Lorraine-University, 54000, Nancy, France

    Antoine Verger, Louis Maillard, Gilles Karcher & Pierre-Yves Marie

  4. Department of Nuclear Medicine, AP-HM, Hospital “La Timone”, 13000, Marseille, France

    Eric Guedj

  5. CNRS UMR7289, Institut de Neurosciences de la Timone, INT, 13000, Marseille, France

    Eric Guedj

  6. Department of Neurology, CHU-Nancy, 54000, Nancy, France

    Louis Maillard

  7. INRIA Sophia Antipolis-Méditerranée, 06902, Sophia Antipolis, France

    Grégoire Malandain

  8. CIC-IT, CHU Nancy, 5400, Nancy, France

    Gabriela Hossu

  9. INSERM, CIC-IP 1433, 5400, Nancy, France

    Gabriela Hossu

  10. INSERM, U1116, 54000, Nancy, France

    Renaud Fay & Pierre-Yves Marie

Authors
  1. Antoine Verger
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  2. Yalcin Yagdigul
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  8. Gabriela Hossu
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  10. Gilles Karcher
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  11. Pierre-Yves Marie
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Correspondence to Antoine Verger.

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Verger, A., Yagdigul, Y., Van Der Gucht, A. et al. Temporal epilepsy lesions may be detected by the voxel-based quantitative analysis of brain FDG-PET images using an original block-matching normalization software. Ann Nucl Med 30, 272–278 (2016). https://doi.org/10.1007/s12149-016-1060-4

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  • DOI: https://doi.org/10.1007/s12149-016-1060-4

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