Skip to main content

Advertisement

SpringerLink
Log in

Diffusion tensor imaging for target volume definition in glioblastoma multiforme

Diffusions-Tensor-Bildgebung zur Zielvolumendefinition beim Glioblastoma multiforme

  • Original article
  • Published:
Strahlentherapie und Onkologie Aims and scope Submit manuscript

Abstract

Introduction

Diffusion tensor imaging (DTI) is an MR-based technique that may better detect the peritumoural region than MRI. Our aim was to explore the feasibility of using DTI for target volume delineation in glioblastoma patients.

Materials and methods

MR tensor tracts and maps of the isotropic (p) and anisotropic (q) components of water diffusion were coregistered with CT in 13 glioblastoma patients. An in-house image processing program was used to analyse water diffusion in each voxel of interest in the region of the tumour. Tumour infiltration was mapped according to validated criteria and contralateral normal brain was used as an internal control. A clinical target volume (CTV) was generated based on the T1-weighted image obtained using contrast agent (T1Gd), tractography and the infiltration map. This was compared to a conventional T2-weighted CTV (T2-w CTV).

Results

Definition of a diffusion-based CTV that included the adjacent white matter tracts proved highly feasible. A statistically significant difference was detected between the DTI-CTV and T2-w CTV volumes (p < 0.005, t = 3.480). As the DTI-CTVs were smaller than the T2-w CTVs (tumour plus peritumoural oedema), the pq maps were not simply detecting oedema. Compared to the clinical planning target volume (PTV), the DTI-PTV showed a trend towards volume reduction. These diffusion-based volumes were smaller than conventional volumes, yet still included sites of tumour recurrence.

Conclusion

Extending the CTV along the abnormal tensor tracts in order to preserve coverage of the likely routes of dissemination, whilst sparing uninvolved brain, is a rational approach to individualising radiotherapy planning for glioblastoma patients.

Zusammenfassung

Einführung

Die Diffusions-Tensor-Bildgebung (DTI) ist eine MR-Technik, die dank der Erfassung des peritumoralen Bereichs eine Verbesserung bezüglich MRI bringt. Unser Ziel war die Prüfung der Machbarkeit der Verwendung der DTI für die Zielvolumenabgrenzung für Patienten mit Glioblastomen.

Material und Methoden

MR-Tensor-Traktate und Karten von isotroper (p) und anisotroper (q) Diffusion von Wasser wurden bei 13 Patienten mit Glioblastomen mit der CT-Bildgebung koregistriert. Ein eigenes Bildverarbeitungsprogramm wurde verwendet, um die Diffusion von Wasser in jedem Voxel in der Umgebung des Tumors zu analysieren. Die Tumorinfiltration wurde nach validierten Kriterien abgebildet. Das kontralaterale normale Gehirn wurde als interne Kontrolle verwendet. Ein klinisches Zielvolumen (CTV) wurde auf Basis des T1-basierten Bilds (T1Gd), der Traktographie und des Infiltrationsmusters generiert. Dieses Zielvolumen wurde mit einem konventionellen T2-basierten CTV verglichen.

Ergebnisse

Die Erstellung eines diffusionsbasierten klinischen Zielvolumens, welches die benachbarte weiße Substanz enthält, ist sehr gut möglich. Zwischen dem DTI-CTV und dem T2-basierten CTV wurde eine statistisch signifikante Differenz nachgewiesen (p < 0,005; t = 3,480). Da die DTI-CTVs kleiner sind als die T2-basierten CTVs (Tumor plus peritumorales Ödem), werden die pq-Karten ein Ödem nicht einfach erkennen. Die DTI-PTV zeigt den Trend einer Volumenreduktion im Vergleich mit der PTV auf. Dieses diffusionsbasierte Volumen war kleiner als das herkömmlich definierte (konventionelle) Volumen.

Schlussfolgerung

Das Erweitern des CTV entlang der abnormalen Tensorabschnitte, um die Deckung der voraussichtlichen Verbreitungsrouten zu bewahren und unbeteiligtes Gehirn zu schonen, ist ein rationaler Ansatz, um die Strahlentherapieplanung für Glioblastompatienten zu individualisieren.

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

Similar content being viewed by others

References

  1. Stupp R, Mason WP, van den Bent MJ et al (2005) Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 352:987–996

    Article  PubMed  CAS  Google Scholar 

  2. Price SJ, Jena R, Burnet NG, Carpenter TA, Pickard JD, Gillard JH (2007) Predicting patterns of glioma recurrence using diffusion tensor imaging. Eur Radiol 17:1675–1684

    Article  PubMed  Google Scholar 

  3. Shapiro WR (1999) Current therapy for brain tumours: back to the future. Arch Neurol 56:429–432

    Article  PubMed  CAS  Google Scholar 

  4. Scherer HJ (1938) Structural development in gliomas. Am J Cancer 34:333–351

    Google Scholar 

  5. Scherer HJ (1940) The forms of growth in gliomas and their practical significance. Brain 63:1–35

    Article  Google Scholar 

  6. Creak AL, Tree A, Saran F (2011) Radiotherapy planning in high-grade gliomas: a survey of current UK practice. Clin. Oncol (R Coll Radiol) 23:189–198

    CAS  Google Scholar 

  7. Piroth MD; Pinkawa M, Hoy R et al (2012) Integrated boost IMRT with FET-PET-adapted local dose escalation in glioblastomas. Results of a prospective phase II study. Strahlenther Onkol 188:334–9

    Article  PubMed  CAS  Google Scholar 

  8. Witwer BP, Moftakhar R, Hasan KM et al (2002) Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm. J Neurosurg 97:568–575

    Article  PubMed  Google Scholar 

  9. Field AS, Alexander AL, Wu YC, Hasan KM, Witwer B, Badie B (2004) Diffusion tensor eigenvector directional color imaging patterns in the evaluation of cerebral white matter tracts altered by tumour. J Magn Reson Imaging 20:555–562

    Article  PubMed  Google Scholar 

  10. Price SJ, Pena A, Burnet NG et al (2004) Tissue signature characterisation of diffusion tensor abnormalities in cerebral gliomas. Eur Radiol 14:1909–1917

    Article  PubMed  Google Scholar 

  11. Price SJ, Jena R, Burnet NG et al (2006) Improved delineation of glioma margins and regions of infiltration using diffusion tensor imaging: an image-guided biopsy study. AJNR Am J Neuroradiol 27:1969–1974

    PubMed  CAS  Google Scholar 

  12. Price SJ, Burnet NG, Donovan T et al (2003) Diffusion tensor imaging of brain tumours at 3T: a potential tool for assessing white matter tract invasion? Clin Radiol 58:455–462

    Article  PubMed  CAS  Google Scholar 

  13. Provenzale JM, McGraw P, Mhatre P, Guo AC, Delong D (2004) Peritumoural brain regions in gliomas and meningiomas: investigation with isotropic diffusion-weighted MR imaging and diffusion-tensor MR imaging. Radiology 232:451–460

    Article  PubMed  Google Scholar 

  14. Price SJ, Pena A, Burnet NG, Pickard JD, Gillard JH (2004) Detecting glioma invasion of the corpus callosum using diffusion tensor imaging. Br J Neurosurg 18:391–395

    Article  PubMed  CAS  Google Scholar 

  15. Zhou XJ, Leeds NE, Poonawalla AH et al (2003) Assessment of tumour cell infiltration along white-matter fiber tracts using diffusion tensor imaging. Proc Intl Soc Mag Reson Med 11:2238

    Google Scholar 

  16. Intven M, Reerink O, Philippens ME (2013) Diffusion-weighted MRI in locally advanced rectal cancer: pathological response prediction after noe-adjuvant radiochemotherapy. Strahlenther Onkol 189:117–122

    Article  PubMed  CAS  Google Scholar 

  17. Server A, Kulle B, Maehlen J et al (2009) Quantitative apparent diffusion coefficients in the characterization of brain tumours and associated peritumoural oedema. Acta Radiol 50:682–689

    Article  PubMed  CAS  Google Scholar 

  18. Van Westen D, Lätt J, Englund E, Brockstedt S, Larsen EM (2006) Tumour extension in high-grade gliomas assessed with diffusion magnetic resonance imaging: values and lesion-to-brain ratios of apparent diffusion coefficient and fractional anisotropy. Acta Radiol 47:311–319

    Article  PubMed  CAS  Google Scholar 

  19. Berberat J, Eberle B, Rogers S et al (2013) Anisotropic phantom measurements for quality assured use of diffusion tensor imaging in clinical practice. Acta Radiol 54:576–580

    PubMed  Google Scholar 

  20. Basser PJ, Mattiello J, LeBihan D (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 103:247–254

    Article  PubMed  CAS  Google Scholar 

  21. McDonald MW, Shu HK, Curran WJ Jr, Crocker IR (2011) Pattern of failure after limited margin radiotherapy and temozolamide for glioblastoma. Int J Radiat Oncol Biol Phys 79:130–136

    Article  PubMed  CAS  Google Scholar 

  22. Minniti G, Amelio D, Amichetti M et al (2010) Patterns of failure and comparison of different target volume delineations in patients with glioblastoma treated with conformal radiotherapy plus concomitant and adjuvant temozolomide. Radiother Oncol 97:377–381

    Article  PubMed  CAS  Google Scholar 

  23. Jamal M, Rath BH, Tsang PS, Camphausen K, Tofilon PJ (2012) The brain microenvironment prefentially enhances the radioresistance of CD133(+) glioblastoma stem-like cells. Neoplasia 14:150–158

    PubMed  CAS  PubMed Central  Google Scholar 

  24. Brandsma D, Stalpers L, Taal W, Sminia P, van den Bent MJ (2008) Clinical features, mechanisms and management of pseudoprogression in malignant gliomas. Lancet Oncol 9:453–461

    Article  PubMed  Google Scholar 

  25. Sundgren PC, Cao Y (2009) Brain irradiation: effects on normal brain parenchyma and radiation injury. Neuroimaging Clin N Am 19:657–668

    Article  PubMed  Google Scholar 

  26. Jena R, Price SJ, Baker C et al (2005). NG Diffusion tensor imaging: possible implications for radiotherapy treatment planning of patients with highgrade glioma. Clin Oncol (R Coll Radiol) 17:581–590

  27. Stummer W, Pichlmeier U, Meinel T et al (2006) Fluorescence-guided surgery with 5-aminolevulinic acid for resection of malignant glioma: a randomised controlled multicentre phase III trial. Lancet Oncol 7:392–401

    Article  PubMed  CAS  Google Scholar 

  28. Lee P, Eppinga W, Lagerwaard F et al (2013) Evaluation of high ipsilateral subventricualr zone radiation therapy dose in glioblastoma: a pooled analysis. Int J Radiat Oncol Biol Phys 86:609–615

    Article  PubMed  Google Scholar 

  29. Jones DK, Cercignani M (2010) Twenty-five Pitfalls in the Analysis of Diffusion MRI Data. NMR Biomed 23:803–820

    Article  PubMed  Google Scholar 

Download references

Compliance with ethical guidelines

Acknowledgements

This work was partially funded by a grant from Krebsforschung Schweiz KFS 02779-02-2011.

Conflict of interest

J. Berberat, J. McNamara, L. Remonda, S. Bodis and S. Rogers state that there are no conflicts of interest. The accompanying manuscript does not include studies on humans or animals.

Author information

Authors and Affiliations

  1. Department of Neuro-radiology, Cantonal Hospital, Tellstrasse, 5001, Aarau, Switzerland

    Jatta Berberat Ph.D. & Luca Remonda

  2. Department of Radiation Oncology, Cantonal Hospital, 5001, Aarau, Switzerland

    Jane McNamara, Stephan Bodis & Susanne Rogers

  3. Department of Radiation Oncology, University Hospital, Zurich, Switzerland

    Stephan Bodis

Authors
  1. Jatta Berberat Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jane McNamara
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luca Remonda
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Stephan Bodis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Susanne Rogers
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jatta Berberat Ph.D..

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Berberat, J., McNamara, J., Remonda, L. et al. Diffusion tensor imaging for target volume definition in glioblastoma multiforme. Strahlenther Onkol 190, 939–943 (2014). https://doi.org/10.1007/s00066-014-0676-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00066-014-0676-3

Keywords

Schlüsselwörter

Search

Navigation