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Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy

  • Diagnostic Neuroradiology
  • Published:
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Abstract

Introduction

Contrast-enhanced MR imaging is the method of choice for routine assessment of brain tumors, but it has limited sensitivity and specificity. We verified if the addition of metabolic, diffusion and hemodynamic information improved the definition of glioma extent and grade.

Methods

Thirty-one patients with cerebral gliomas (21 high- and 10 low-grade) underwent conventional MR imaging, proton MR spectroscopic imaging (1H-MRSI), diffusion weighted imaging (DWI) and perfusion weighted imaging (PWI) at 3 Tesla, before undergoing surgery and histological confirmation. Normalized metabolite signals, including choline (Cho), N-acetylaspartate (NAA), creatine and lactate/lipids, were obtained by 1H-MRSI; apparent diffusion coefficient (ADC) by DWI; and relative cerebral blood volume (rCBV) by PWI.

Results

Perienhancing areas with abnormal MR signal showed 3 multiparametric patterns: “tumor”, with abnormal Cho/NAA ratio, lower ADC and higher rCBV; “edema”, with normal Cho/NAA ratio, higher ADC and lower rCBV; and “tumor/edema”, with abnormal Cho/NAA ratio and intermediate ADC and rCBV. Perienhancing areas with normal MR signal showed 2 multiparametric patterns: “infiltrated”, with high Cho and/or abnormal Cho/NAA ratio; and “normal”, with normal spectra. Stepwise discriminant analysis showed that the better classification accuracy of perienhancing areas was achieved when regarding all MR variables, while 1H-MRSI variables and rCBV better differentiated high- from low-grade gliomas.

Conclusion

Multiparametric MR assessment of gliomas, based on 1H-MRSI, PWI and DWI, discriminates infiltrating tumor from surrounding vasogenic edema or normal tissues, and high- from low-grade gliomas. This approach may provide useful information for guiding stereotactic biopsies, surgical resection and radiation treatment.

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Acknowledgement

The authors are grateful to Piero Ghedin for expert technical assistance.

Conflict of interest statement

We declare that we have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Health Sciences, University of Molise, Via de Sanctis 2, 86100, Campobasso, Italy

    Alfonso Di Costanzo

  2. Department of Neuroradiology, Scientific Institute ‘‘Casa Sollievo della Sofferenza’’, San Giovanni Rotondo, Foggia, Italy

    Tommaso Scarabino, Giuseppe M. Giannatempo & Teresa Popolizio

  3. Department of Neurological Sciences, Second University of Naples, Naples, Italy

    Francesca Trojsi, Domenico Catapano, Simona Bonavita & Giocchino Tedeschi

  4. Department of Neurosurgery, Scientific Institute ‘‘Casa Sollievo della Sofferenza’’, San Giovanni Rotondo, Foggia, Italy

    Vincenzo A. d’Angelo

  5. Faculty of Medicine, University of Bari, Bari, Italy

    Nicola Maggialetti

  6. Department of Magnetic Resonance, Scientific Institute ‘‘Stella Maris’’, Pisa, Italy

    Michela Tosetti

  7. Department of Neuroradiology, Azienda Ospedaliera Universitaria “Umberto I”, Torrette, Ancona, Italy

    Ugo Salvolini

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  1. Alfonso Di Costanzo
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  2. Tommaso Scarabino
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  3. Francesca Trojsi
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  4. Giuseppe M. Giannatempo
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  11. Vincenzo A. d’Angelo
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  12. Giocchino Tedeschi
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Correspondence to Alfonso Di Costanzo.

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Di Costanzo, A., Scarabino, T., Trojsi, F. et al. Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy. Neuroradiology 48, 622–631 (2006). https://doi.org/10.1007/s00234-006-0102-3

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  • DOI: https://doi.org/10.1007/s00234-006-0102-3

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