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MRI for Response Assessment In Oncologic Bone Marrow Lesions

  • F. Lecouvet
  • P. Omoumi
  • A. Larbi
  • B. Tombal
  • N. Michoux
  • B. Vande Berg
  • J. Malghem
Part of the Medical Radiology book series (MEDRAD)

Abstract

Imaging has multiple roles in oncology. Besides lesion detection and characterization, disease staging, the quantification of the tumor load and the evaluation of response to therapy are of critical importance for the patient and for the clinician, both in primary and metastatic cancers. The assessment of the response to treatment of bone lesions has been considered difficult or impossible even for most prestigious cancer authorities, compared to lesions involving soft tissues or other organs like the lungs or liver, for which response evaluation criteria exist (Eisenhauer et al. 45:228–247, 2009; Therasse et al. 92:205–216, 2000). This is mainly due to the lack of sensitivity, specificity and measurement capabilities of imaging techniques that have been available for years for the assessment of bone lesions, i.e. bone scintigraphy (BS), radiographs and X-ray computed tomography (CT). This chapter first summarizes the possibilities and limitations of the aforementioned techniques. It illustrates the capabilities of “modern” imaging modalities, i.e. positron emission tomography (PET) and most importantly magnetic resonance imaging (MRI). Practical morphologic as well as functional observations that can be made using MRI at primary diagnosis are emphasized as well as the evaluation of response of bone marrow lesions to treatment. Technical advances in MRI, which further refine the capabilities of this modality for early evaluation of the response, including dynamic contrast-enhanced (DCE) imaging and diffusion-weighted imaging (DWI), are also covered.

Keywords

Positron Emission Tomography Multiple Myeloma Bone Lesion Bone Scintigraphy Soft Tissue Extension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • F. Lecouvet
    • 1
  • P. Omoumi
    • 1
  • A. Larbi
    • 1
  • B. Tombal
    • 1
  • N. Michoux
    • 1
  • B. Vande Berg
    • 1
  • J. Malghem
    • 1
  1. 1.Department of RadiologyCliniques Universitaires Saint-Luc, UCL Université de LouvainBrusselsBelgium

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