Skip to main content
SpringerLink
Log in

DTI and PWI analysis of peri-enhancing tumoral brain tissue in patients treated for glioblastoma

  • Clinical Study - Patient Studies
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

To analyse the role of MR diffusion-tensor imaging (DTI) and perfusion-weighted imaging (PWI) in characterising tumour boundaries in patients with glioblastoma multiforme. Seventeen patients with surgically treated WHO IV grade gliomas who were candidates for adjuvant chemo-radiotherapy were enrolled. Before (T0) and after radiation treatment (T1), they underwent DTI and PWI, and the apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV) in the enhancing tumour, the hyperintense tissue adjacent to the enhancing tumour, and the normal-appearing white matter (NAWM) adjacent to the hyperintense areas were analysed. The enhancing tissue at T1 was retrospectively divided on the basis of whether or not it was also enhancing at T0. The controls were the corresponding contralateral areas, on which we normalized the rCBV values, calculating the rCBV ratio. In NAWM, we did not find any significant differences in FA, ADC or rCBV. In the hyperintense perilesional regions, FA was significantly lower and ADC significantly higher than in the unaffected contralateral tissue; there were no significant differences in the rCBV maps. The values of FA, ADC and rCBV in enhancing neoplastic tissue were all significantly different from those observed in the contralateral tissue. There was no significant difference in rCBV values between the areas enhancing at T0 and those not enhancing at T0 but enhancing at T1, which may indicate the neoplastic transformation of apparently normal brain tissue. DTI metrics identify ultrastructural changes in hyperintense perilesional areas, but these are not specific for neoplastic tissue. rCBV seemed to reflect an ultrastructural alteration that was not visible at T0, but became visible (as neoplastic progression) on conventional MR images at T1. These findings could help identify tissue at risk of tumour infiltration.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Scarabino T, Popolizio T, Tosetti M, Montanaro D et al (2009) Phenylketonuria: white-matter changes assessed by 3.0-T magnetic resonance (MR) imaging, MR spectroscopy and MR diffusion. Radiol Med 114(3):461–474

    Article  PubMed  CAS  Google Scholar 

  2. Rizzo L, Crasto SG, Moruno PG et al (2009) Role of diffusion- and perfusion-weighted MR imaging for brain tumour characterisation. Radiol Med 114(4):645–659

    Article  PubMed  CAS  Google Scholar 

  3. Law M, Young RJ, Babb JS et al (2008) Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 247(2):490–498

    Article  PubMed  Google Scholar 

  4. Kealey SM, Kim Y, Provenzale JM (2004) Redefinition of multiple sclerosis plaque size using diffusion tensor. Am J Roentgenol 183(2):497–503

    Google Scholar 

  5. Lu S, Ahn D, Johnson G, Law M et al (2004) Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology 232(1):221–228

    Article  PubMed  Google Scholar 

  6. Sugahara T, Korogi Y, Kochi M et al (1998) Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. Am J Roentgenol 171(6):1479–1486

    CAS  Google Scholar 

  7. Macdonald DR, Cascino TL, Schold SC et al (1990) Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol 8:1277–1280

    PubMed  CAS  Google Scholar 

  8. Wen PY, Macdonald DR, Reardon DA et al (2010) Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 28:1963–1972

    Article  PubMed  Google Scholar 

  9. Manka C, Träber F, Gieseke J et al (2005) Three-dimensional dynamic susceptibility-weighted perfusion MR imaging at 3.0 T: feasibility and contrast agent dose. Radiology 234(3):869–877

    Article  PubMed  Google Scholar 

  10. Tanner SF, Cornette L, Ramenghi LA et al (2003) Cerebral perfusion in infants and neonates: preliminary results obtained using dynamic susceptibility contrast enhanced magnetic resonance imaging. Arch Dis Child Fetal Neonatal Ed 88(6):F525–F530

    Article  PubMed  CAS  Google Scholar 

  11. Wetzel SG, Cha S, Johnson G et al (2002) Relative cerebral blood volume measurements in intracranial mass lesions: interobserver and intraobserver reproducibility study. Radiology 224:797–803

    Article  PubMed  Google Scholar 

  12. Streiner DL, Norman GR (1989) Health measurement scale. A practical guide to their development and use. Oxford University Press, New York

    Google Scholar 

  13. McKnight TR, von dem Bussche MH, Vigneron DB et al (2002) Histopathological validation of a three-dimensional magnetic resonance spectroscopy index as a predictor of tumor presence. J Neurosurg 97:794–802

    Article  PubMed  Google Scholar 

  14. Kelly PJ, Daumas-Duport C, Kispert DB et al (1987) Imaging-based stereotaxic serial biopsies in untreated intracranial glial neoplasms. J Neurosurg 66(6):865–874

    Article  PubMed  CAS  Google Scholar 

  15. Shaw EG, Stieber V, Tatter S et al (2002) A Phase I dose escalating study of intensity modulated radiation therapy (IMRT) for the treatment of glioblastoma multiforme (GBM). Int J Radiat Oncol Biol Phys 54:206

    Article  Google Scholar 

  16. Sinha S, Bastin ME, Whittle IR et al (2002) Diffusion tensor MR imaging of high-grade cerebral gliomas. Am J Neuroradiol 23(4):520–527

    PubMed  Google Scholar 

  17. Stieltjes B, Schlüter M, Didinger B et al (2006) Diffusion tensor imaging in primary brain tumors: reproducible quantitative analysis of corpus callosum infiltration and contralateral involvement using a probabilistic mixture model. Neuroimage 31(2):531–542

    Article  PubMed  Google Scholar 

  18. Provenzale JM, McGraw P, Mhatre P et al (2004) Peritumoral brain regions in gliomas and meningiomas: investigation with isotropic diffusion-weighted MR imaging and diffusion-tensor MR imaging. Radiology 232(2):451–460

    Article  PubMed  Google Scholar 

  19. Kono K, Inoue Y, Nakayama K, Shakudo M et al (2001) The role of diffusion-weighted imaging in patients with brain tumors. Am J Neuroradiol 22(6):1081–1088

    PubMed  CAS  Google Scholar 

  20. Lu S, Ahn D, Johnson G, Cha S et al (2003) Peritumoral diffusion tensor imaging in high-grade gliomas and metastatic brain tumors. Am J Neuroradiol 24:937–941

    PubMed  Google Scholar 

  21. Zhou XJ, Yang S, Srinivasan G et al (2007) A study of glioma infiltration using fractional anisotropy and fiber coherence index. Proc Int Soc Mag Reson Med 15:344

    Google Scholar 

  22. Provenzale JM, Mukundan S, Barboriak DP (2006) Diffusion-weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response. Radiology 239(3):632–649

    Article  PubMed  Google Scholar 

  23. Kassner A, Annesley DJ, Zhu XP et al (2000) Abnormalities of the contrast re-circulation phase in cerebral tumors demonstrated using dynamic susceptibility contrast-enhanced imaging: a possible marker of vascular tortuosity. J Magn Reson Imaging 11:103–113

    Article  PubMed  CAS  Google Scholar 

  24. Barajas RF Jr, Hodgson JG, Chang JS et al (2010) Glioblastoma multiforme regional genetic and cellular expression patterns: influence on anatomic and physiologic MR imaging. Radiology 254(2):564–576

    Article  PubMed  Google Scholar 

  25. Murakami R, Sugahara T, Nakamura H et al (2007) Malignant supratentorial astrocytoma treated with postoperative radiation therapy: prognostic value of pretreatment quantitative diffusion-weighted MR imaging. Radiology 243(2):493–499

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SCDU Radiologia, Azienda Ospedaliera Universitaria “Maggiore della Carità”, Corso Mazzini 18, 28100, Novara, Italy

    Alessandro Stecco, Raffaella Quarta, Sara Zizzari, Rita Fossaceca & Alessandro Carriero

  2. SCDU Radioterapia, Azienda Ospedaliera Universitaria “Maggiore della Carità”, Novara, Italy

    Carla Pisani, Laura Masini, Debora Beldì & Marco Krengli

  3. SC Fisica Sanitaria, Azienda Ospedaliera Universitaria “Maggiore della Carità”, Novara, Italy

    Marco Brambilla

Authors
  1. Alessandro Stecco
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carla Pisani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Raffaella Quarta
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marco Brambilla
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Laura Masini
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Debora Beldì
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sara Zizzari
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Rita Fossaceca
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Marco Krengli
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Alessandro Carriero
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alessandro Stecco.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Stecco, A., Pisani, C., Quarta, R. et al. DTI and PWI analysis of peri-enhancing tumoral brain tissue in patients treated for glioblastoma. J Neurooncol 102, 261–271 (2011). https://doi.org/10.1007/s11060-010-0310-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11060-010-0310-x

Keywords

Search

Navigation