Prediction of brain tumor therapy response by PET. Review uri icon

Overview

abstract

  • In the context of brain tumor therapy it is an important issue to assess whether positron emission tomography (PET) investigation of tumor metabolism can predict tumor response to therapy, whether the information obtained with PET is substantially different from that obtained by computed tomography (CT) and magnetic resonance (MR) imaging, and whether this information will be sufficiently useful in the management of patients to warrant the cost of PET studies. Aggressive neurosurgery, radiotherapy and adjuvant chemotherapy have become the standard of care for many patients with primary brain tumors, and the limitations of CT and MR imaging in the post-treatment period have become more apparent. Both techniques are frequently unable to differentiate between therapy-related tissue changes and progressive tumor. Two clinical situations are particularly difficult to resolve: 1) transient radiographic and clinical deterioration following intensive radiotherapy or less commonly following intensive chemotherapy, and 2) clinical deterioration in a patient who has failed initial therapy, but has stable radiographic findings following a second therapy. Available PET tracers in this context fall into the following categories of tumor biochemistry: 1) energy metabolism, 2) amino acid and protein metabolism, and 3) DNA and RNA metabolism. The use of these tracers will be described in detail below. The question is not only whether therapeutic interventions specifically alter one or more of these biochemical processes in tumors, but whether the magnitude of alterations has prognostic value with respect to clinical response and survival. Moreover, an early identification of treatment 'success' or 'failure' could significantly influence patient management by providing more objective criteria for continuing or changing a specific therapeutic strategy.

publication date

  • January 1, 1994

Research

keywords

  • Brain Neoplasms
  • Tomography, Emission-Computed

Identity

Scopus Document Identifier

  • 0028633552

Digital Object Identifier (DOI)

  • 10.1007/BF01052934

PubMed ID

  • 7760108

Additional Document Info

volume

  • 22

issue

  • 3