Skip to main content
SpringerLink
Log in

Role of advanced MR imaging modalities in diagnosing cerebral gliomas

Ruolo delle nuove ed avanzate modalità di studio RM nella diagnostica neuroradiologica dei gliomi cerebrali

  • Neuroradiology Neuroradiologia
  • Published:
La radiologia medica Aims and scope Submit manuscript

Abstract

The objective of this study was to evaluate the potential role of newly developed, advanced magnetic resonance (MR) imaging techniques (spectroscopy, diffusion and perfusion imaging) in diagnosing brain gliomas, with special reference to histological typing and grading, treatment planning and posttreatment follow-up. Conventional MR imaging enables the detection and localisation of neoplastic lesions, as well as providing, in typical cases, some indication about their nature. However, it has limited sensitivity and specificity in evaluating histological type and grade, delineating margins and differentiating oedema, tumour and treatment side-effects. These limitations can be overcome by supplementing the morphological data obtained with conventional MR imaging with the metabolic, structural and perfusional information provided by new MR techniques that are increasingly becoming an integral part of routine MR studies. Incorporation of such new MR techniques can lead to more comprehensive and precise diagnoses that can better assist surgeons in determining prognosis and planning treatment strategies. In addition, the recent development of new, more effective, treatments for cerebral glioma strongly relies on morphofunctional MR imaging with its ability to provide a biological interpretation of these characteristically heterogeneous tumours.

Riassunto

Lo scopo del lavoro è di illustrare le potenzialità delle nuove e più avanzate modalità di studio RM (spettroscopia, diffusione, perfusione) nella diagnostica dei gliomi cerebrali, con particolare riferimento alla definizione dell’istotipo e del grading, alla pianificazione del trattamento e al follow-up post-trattamento. Con la RM di base è possibile nei casi tipici identificare la lesione neoplastica, stabilirne la sede e la topografia e proporre un’ipotesi di natura. Vi è però una limitata sensibilità e specificità nella definizione dell’istotipo e del grading, nell’individuazione dei margini neoplastici e nella differenziazione tra tumore ed edema o effetti del trattamento. È necessario pertanto integrare le informazioni fornite dalla RM di base con le informazioni di carattere metabolico, strutturale ed emodinamico fornite dalle più recenti tecniche RM, oramai parte integrante di uno studio di routine. In tal modo sono possibili diagnosi sempre più precise ed esaustive per il chirurgo, necessarie per definire la prognosi e l’impostazione delle diverse strategie terapeutiche. Inoltre, il recente sviluppo di nuovi e più efficaci trattamenti ha reso sempre più necessario uno studio RM morfofunzionale con cui ottenere in maniera non invasiva una “neuropatologia in vivo” e quindi un’interpretazione biologica della eterogeneità tipica di tali tumori.

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

Similar content being viewed by others

References/Bibliografia

  1. Ohgaki H, Kleihues P (2005) Epidemiology and etiology of glioma. Acta Neuropatholo 109:193–108

    Google Scholar 

  2. Rampling R, James A, Papanastassiou V (2004) The present and future management of malignant brain tumours: surgery, radiotherapy, chemotherapy. J Neurol Neurosurg Psych 75:24–30

    Google Scholar 

  3. Jackson RJ, Fuller GN, Abi-Said D et al (2001) Limitations of stereotactic biopsy in the initial management of gliomas. Neuro-oncol 3:193–200

    Article  PubMed  CAS  Google Scholar 

  4. Nelson SJ (2003) Multivoxel magnetic resonance spectroscopy of brain tumors. Mol Cancer Ther 2:497–507

    PubMed  CAS  Google Scholar 

  5. Law M, Yang S, Wang H et al (2003) Glioma grading: sensitivity, specificity, and predictive value of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol 24:1989–1998

    PubMed  Google Scholar 

  6. Rabinov JD, Lee PL, Barker FG et al (2002) In vivo 3-T MR spectroscopy in the distinction of recurrent glioma versus radiation effects: initial experience. Radiology 225:871–879

    Article  PubMed  CAS  Google Scholar 

  7. Li X, Lu Y, Pirzkall A, et al (2002) Analysis of the spatial characteristics of metabolic abnormalities in newly diagnosed glioma patients. J Magn Reson Imag 16:229–237

    Article  Google Scholar 

  8. Howe FA, Barton SJ, Cudlip SA et al (2003) Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy. Magn Reson Med 49:223–232

    Article  PubMed  CAS  Google Scholar 

  9. Howe FA, Opstad KS (2003) 1H MR spectroscopy of brain tumours and masses. NMR Biomed 16:123–131

    Article  PubMed  CAS  Google Scholar 

  10. Möller-Hartmann W, Herminghaus S, Krings T et al (2002) Clinical application of proton magnetic resonance spectroscopy in the diagnosis of intracranial mass lesions. Neuroradiology 44:371–381

    Article  PubMed  Google Scholar 

  11. Rees J (2003) Advances in magnetic resonance imaging of brain tumours. Curr Opin Neurol 16:643–650

    Article  PubMed  Google Scholar 

  12. Kim JH, Chang KN, Na DG et al (2006) 3 T 1H-MRS spectroscopy in grading of cerebral gliomas: comparison of short and intermediate scho time sequences. AJNR Am J Neuroradiol 27:1412–1418

    PubMed  Google Scholar 

  13. Nelson SJ, Graves E, Pirzkall A et al (2002) In vivo molecular imaging for planning radiation therapy of gliomas: an application of 1H MRSI. J Magn Reson Imag 16:464–476

    Article  Google Scholar 

  14. Dowling C, Bollen AW, Noworolski SM et al (2001) Preoperative proton MR spectroscopic imaging of brain tumors: correlation with histopathologic analysis of resection specimens. AJNR Am J Neuroradiol 22:604–612

    PubMed  CAS  Google Scholar 

  15. Graves EE, Nelson SJ, Vigneron DB et al (2000) A preliminary study of the prognostic value of proton magnetic resonance spectroscpic imaging in gamma knife radiosurgery of recurrent malignant glioma. Neurosurg 46:319–326

    Article  CAS  Google Scholar 

  16. Graves EE, Nelson SJ, Vigneron DB et al (2001) Serial proton MR spectroscopic imaging of recurrent malignat gliomas after gamma knife radiosurgery. AJNR Am J Neuroradiol 22:613–624

    PubMed  CAS  Google Scholar 

  17. Tedeschi G, Lundbom N, Raman R et al (1997) Increased choline signal coinciding with malignant degeneration of cerebral gliomas: a serial proton magnetic resonance spectroscopy imaging study. J Neurosurg 87:516–524

    PubMed  CAS  Google Scholar 

  18. Lichy MP, Bachert P, Hamprecht F et al (2006) Application of 1H-MRS spectroscopic imaging in radiation oncology: choline a marker for determining the relatove probability of tumor progression after radiation of glial brain tumors. Rofo 178:627–633

    PubMed  CAS  Google Scholar 

  19. Murphy PS, Rowland IJ, Viviers L et al (2003) Could assessment of glioma methylene lipid resonance by in vivo 1H-MRS be of clinical value? Br J Radiol 76:459–463

    Article  PubMed  CAS  Google Scholar 

  20. Pirzkall A, Mcknight TR, Graves EE et al (2001) MR-spectroscopy guided target delineation for high-grade gliomas. Int J Radiat Oncol Biol Phys 50:915–928

    Article  PubMed  CAS  Google Scholar 

  21. Weybright P, Sundgren PC, Maly P et al (2005) Differentiation between brain tumor recurrence and radiation injury using MR spectroscopy. AJR Am J Roentgenol 185:1471–1476

    Article  PubMed  Google Scholar 

  22. Zeng QS, Li CF, Zhang K et al (2007) Multivoxel 3D proton MR spectroscopy in the distinction of recurrent glioma from radiation injury. J Neurooncol 84:63–69

    Article  PubMed  CAS  Google Scholar 

  23. Rock JP, Scarpace L, Hearshen D et al (2004) Associations among magnetic resonance spectroscy, apparent diffusion coefficients, and imageguided histopatology with special attention to radiotion necrosis. Neurosurg 54:1111–1117

    Article  Google Scholar 

  24. Balmaceda C, Critchell D, Mao X et al (2006) Multisection 1H magnetic resonance spectroscopic imaging assessment of glioma response to chemiotherapy. J Neurooncol 76:185–191

    Article  PubMed  CAS  Google Scholar 

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

    PubMed  CAS  Google Scholar 

  26. Stadnik TW, Chaslis C, Michotte A et al (2001) Diffusion-weighted MR imaging of intracerebral masses: comparison with conventional MR imaging and histologic findings. AJNR Am J Neuroradiol 22:969–976

    PubMed  CAS  Google Scholar 

  27. Rollin N, Guyota J, Streichenberger N et al (2006) Clinical relevance of diffusion and perfusion magnetic resonance imaging in assessing intraaxial brain tumors. Neuroradiology 48:150–159

    Article  PubMed  CAS  Google Scholar 

  28. Lam WWM, Poon WS, Metreweli C (2002) Diffusion MR imaging in glioma: does it have any role in the preoperation determination of grading of glioma? Clinical Radiology 57:219–225

    Article  PubMed  CAS  Google Scholar 

  29. Brunberg JA, Chenevert TL, McKeever PE et al (2005) In vivo MR determination of water diffusion coefficients and diffusion anisotropy: correlation with structural alteration in gliomas of the cerebral hemisferes. AJNR Am J Neuroradiol 16:361–371

    Google Scholar 

  30. van Westen D, Litt J, Englund E et al (2006) Tumor extension in high-grade gliomas assessed with diffusion magnetic resonance imaging: value and lesion-to-brain ratios of apparent diffusion coefficient and fractional anisotropy. Acta Radiol 47:311–319

    Article  PubMed  Google Scholar 

  31. Lu S, Ahn D, Johnson G et al (2003) Peritumoral diffusion tensor imaging of high grade gliomas and metastatic brain tumours. AJNR Am J Neuroradiol 24:937–941

    PubMed  Google Scholar 

  32. Romano A, Ferrante M, Cipriani V et al (2007) Role of magnetic resonance tractography in the preoperative planning and intraoperative assessment of patients with intra-axial brain tumors. Radiol Med 112:906–920

    Article  PubMed  CAS  Google Scholar 

  33. Smith JS, Cha S, Mayo MC et al (2005) Serial diffusion-weighted magnetic resonance imaging in cases of glioma: distinguishing tumor recurrence from postresection injury. J Neurosurg 103:428–438

    Article  PubMed  Google Scholar 

  34. Hein PA, Eskey CJ, Dunn JF et al (2004) Diffusion-weighted imaging in the follow up of treated high grade gliomas: tumor recurrence versus radiation injury. AJNR Am J Neuroradiol 25:201–209

    PubMed  Google Scholar 

  35. Sudgren PC, Fan X, Weibright P et al (2006) Differentiation of recurrent brain tumor versus radiation injury using diffusion tensor imaging in patients with new contrast-enhancing lesions. Magn Reson Imaging 24:1131–1142

    Article  CAS  Google Scholar 

  36. Cha S (2006) Update on brain tumor imaging: from anatomy to physiology. AJNR Am J Neuroradiol 27:475–487

    PubMed  CAS  Google Scholar 

  37. Covarrubias DJ, Rosen BR, Lev MH (2004) Dynamic magnetic resonance perfusion imaging of brain tumors. Oncologist 9:528–537

    Article  PubMed  Google Scholar 

  38. Barbier E, Lamalle L, Decorps M (2001) Methodology of brain perfusion imaging. J Magn Reson Imag 13:496–520

    Article  CAS  Google Scholar 

  39. Hakyemez B, Erdogan C, Bolca N et al (2006) Evaluation of different cerebral mass lesions by perfusion-weighted MR imaging. J Magn Reson Imag 24:817–824

    Article  Google Scholar 

  40. Leon SP, Folkerth RD, Black PM (1996) Microvessel density is a prognostic indicator for patients with astroglial brain tumors. Cancer 77:362–372

    Article  PubMed  CAS  Google Scholar 

  41. Spampinato MV, Smith JK, Kwock L et al (2007) Cerebral blood volume measurements and proton MR spectroscopy in grading of oligodendroglial tumors. AJR Am J Roentgenol 188:204–212

    Article  PubMed  Google Scholar 

  42. Law M, Yang S, Babb JS et al (2004) Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol 25:746–755

    PubMed  Google Scholar 

  43. Chaskis C, Stadnik T, Michotte A et al (2006) Prognostic value of perfusion-weighted imaging in brain glioma: a prospective study. Acta Neurichir 148:277–285

    Article  CAS  Google Scholar 

  44. Lev MH, Ozsunar Y, Henson JW et al (2004) Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligondendrogliomas. AJNR Am J Neuroradiol 25:214–221

    PubMed  Google Scholar 

  45. Di Costanzo A, Pollice S, Trojsi F et al (2008) Role of perfusion-weighted imaging at 3 Tesla in the assessment of malignancy of cerebral gliomas. Radiol Med 113:134–143

    Article  PubMed  Google Scholar 

  46. Law M, Cha S, Knopp EA et al (2002) High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology 222:715–721

    Article  PubMed  Google Scholar 

  47. Bulakbasi N, Kocaoglu M, Ors F et al (2003) Combination of single-voxel proton spectroscopy and apparent diffusion coefficient calculation in the evaluation of common brain tumours. AJNR Am J Neuroradiol 23:225–233

    Google Scholar 

  48. Oshiro S, Tsugu H, Komatsu F et al (2007) Quantitative assessment of gliomas by proton magnetic resonance spectroscopy. Anticanc Res 27:3757–3763

    CAS  Google Scholar 

  49. Zeng QS, Li CF, Liu H et al (2007) Distinction between recurrent glioma and radiation injury using magnetic resonance spectroscopy in combination with diffusion-weigthed imaging. Int J Radiat Oncol Biol Phys 68:151–158

    PubMed  Google Scholar 

  50. Fan GG, Deng QL, WU ZH et al (2006) Usefulness of diffusion/perfusion-weighted MRI in patients with non-enhancing supratentorial brain gliomas: a valuable tool to predict tumor grading? Br J Radiol 79:652–658

    Article  PubMed  CAS  Google Scholar 

  51. Di Costanzo A, Scarabino T, Trojsi F et al (2006) Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy. Neuroradiology 48:622–631

    Article  PubMed  Google Scholar 

  52. Di Costanzo A, Trojsi F, Giannatempo GM et al (2006) Spectroscopic, diffusion and perfusion magnetic resonance imaging at 3.0 Tesla in the delineation of glioblastomas: preliminary results. J Exp Clin Cancer Res 25:383–390

    PubMed  Google Scholar 

  53. Lemort M, Canizares-Perez AC, Van der Stappen A et al (2007) Progress in magnetic resonance imaging of the brain. Curr Opin Oncol 19:616–622

    Article  PubMed  Google Scholar 

  54. Jenkinson MD, Du Plessis DG, Waljer C et al (2007) Advanced MRI in the management of adult gliomas. Br J Neurosurg 21:550–561

    Article  PubMed  CAS  Google Scholar 

  55. Al-Okaili RN, Krejza J, Wang S et al (2006) Advanced MR imaging in the diagnosis of intraaxial brain tumors in adults. Radiographics 26:5173–5189

    Article  Google Scholar 

  56. Scarabino T, Popolizio T, Giannatempo GM et al (2007) 3.0 T brain imaging: a five-year experience with morphological and angiographic imaging. Radiol Med 112:82–96

    Article  PubMed  CAS  Google Scholar 

  57. Scarabino T, Giannatempo GM, Popolizio T et al (2007) 3.0 T functional brain imaging: a five-year experience. Radiol Med 112:97–112

    Article  PubMed  CAS  Google Scholar 

  58. Di Costanzo A, Trojsi F, Tosetti M et al (2007) Proton MR spectroscopy of the brain at 3 T: an up date, Eur Radiol 17:1651–1662

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. U.O. di Neuroradiologia, AUSL BAT, Ospedale “Lorenzo Bonomo”, Andria, Italy

    T. Scarabino & S. Pollice

  2. Dipartimento di Neuroradiologia, IRCCS “Casa Sollievo della Sofferenza”, San Giovanni Rotondo, Foggia, Italy

    T. Scarabino, T. Popolizio & G. Giannatempo

  3. Dipartimento di Scienze Neurologiche, Seconda Università di Napoli, Napoli, Italy

    F. Trojsi & G. Tedeschi

  4. Facoltà di Medicina, Università degli Studi di Bari, Bari, Italy

    N. Maggialetti

  5. Dipartimento di Radiologia, Università Novara, Novara, Italy

    A. Carriero

  6. Dipartimento di Scienze per la Salute, Università degli Studi del Molise, Campobasso, Italy

    A. Di Costanzo

  7. Dipartimento di Radiologia, Azienda Ospedaliera Universitaria, “Umberto I”, Torrette, Ancona, Italy

    U. Salvolini

  8. Via Napoli 56, 70031, Andria (Ba), Italy

    T. Scarabino

Authors
  1. T. Scarabino
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. Popolizio
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. F. Trojsi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. G. Giannatempo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. S. Pollice
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. N. Maggialetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. A. Carriero
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. A. Di Costanzo
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. G. Tedeschi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. U. Salvolini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T. Scarabino.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Scarabino, T., Popolizio, T., Trojsi, F. et al. Role of advanced MR imaging modalities in diagnosing cerebral gliomas. Radiol med 114, 448–460 (2009). https://doi.org/10.1007/s11547-008-0351-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11547-008-0351-9

Keywords

Parole chiave

Search

Navigation