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  • Review Article
  • Published:

Quantitative imaging biomarkers in neuro-oncology

Nature Reviews Clinical Oncology volume 6, pages 445–454 (2009)Cite this article

Abstract

Conventional structural imaging provides limited information on tumor characterization and prognosis. Advances in neurosurgical techniques, radiotherapy planning and novel drug treatments for brain tumors have generated increasing need for reproducible, noninvasive, quantitative imaging biomarkers. This Review considers the role of physiological MRI and PET molecular imaging in understanding metabolic processes associated with tumor growth, blood flow and ultrastructure. We address the utility of various techniques in distinguishing between tumors and non-neoplastic processes, in tumor grading, in defining anatomical relationships between tumor and eloquent brain regions and in determining the biological substrates of treatment response. Much of the evidence is derived from limited case series in individual centers. Despite their 'added value', the effect of these techniques as an adjunct to structural imaging in clinical research and practice remains limited.

Key Points

  • Physiological and functional MRI is widely accessible, and provides quantitative biomarkers of blood flow and permeability, cellular turnover and tissue ultrastructure

  • Molecular imaging with PET is many orders of magnitude more sensitive, and yields additional information on specific biochemical pathways and ligand interactions, but is costly and limited to more specialist cancer centers

  • The majority of evidence derives from limited case series in individual centers, determined by local facilities and expertise

  • These techniques are useful for tumor characterization, treatment planning and therapeutic evaluation

  • Their application in routine clinical practice and prospective trials has, to date, been limited

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Figure 1: Fractional anisotropy of peritumoral brain.
Figure 2: Tissue characterization and biopsy guidance using perfusion imaging and spectroscopy.
Figure 3: Diagnosis and surgical planning using co-registered rCBV, MRS, functional MRI and DTI data.
Figure 4: Metabolic imaging with MET PET and FDG PET in a patient with a suspected recurrence of glioblastoma multiforme.

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Authors and Affiliations

  1. Department of Imaging, Imperial College, London, UK

    Adam D. Waldman

  2. Manchester Cancer Research Centre, Manchester, UK

    Alan Jackson

  3. Addenbrooke's Hospital, Cambridge, UK

    Stephen J. Price

  4. University College London Institute of Child Health in London, London, UK

    Christopher A. Clark

  5. Royal Free Hospital, London, UK

    Thomas C. Booth

  6. Nottingham University, Nottingham, UK

    Dorothee P. Auer

  7. Brighton and Sussex Medical School, Brighton, UK

    Paul S. Tofts

  8. Royal Marsden Hospital, London, UK

    David J. Collins & Martin O. Leach

  9. University College London Institute of Neurology, London, UK

    Jeremy H. Rees

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(on behalf of the National Cancer Research Institute Brain Tumour Imaging Subgroup)

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Correspondence to Adam D. Waldman.

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Waldman, A., Jackson, A., Price, S. et al. Quantitative imaging biomarkers in neuro-oncology. Nat Rev Clin Oncol 6, 445–454 (2009). https://doi.org/10.1038/nrclinonc.2009.92

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