Literature DB >> 24305716

Diagnosing relapse in children's brain tumors using metabolite profiles.

Simrandip K Gill1, Martin Wilson, Nigel P Davies, Lesley MacPherson, Martin English, Theodoros N Arvanitis, Andrew C Peet.   

Abstract

BACKGROUND: Malignant brain tumors in children generally have a very poor prognosis when they relapse and improvements are required in their management. It can be difficult to accurately diagnose abnormalities detected during tumor surveillance, and new techniques are required to aid this process. This study investigates how metabolite profiles measured noninvasively by (1)H magnetic resonance spectroscopy (MRS) at relapse reflect those at diagnosis and may be used in this monitoring process.
METHODS: Single-voxel MRS (1.5 T, point-resolved spectroscopy, echo time 30 ms, repetition time 1500 ms was performed on 19 children with grades II-IV brain tumors during routine MRI scans prior to treatment for a suspected brain tumor and at suspected first relapse. MRS was analyzed using TARQUIN software to provide metabolite concentrations. Paired Student's t-tests were performed between metabolite profiles at diagnosis and at first relapse.
RESULTS: There was no significant difference (P > .05) in the level of any metabolite, lipid, or macromolecule from tumors prior to treatment and at first relapse. This was true for the whole group (n = 19), those with a local relapse (n = 12), and those with a distant relapse (n = 7). Lipids at 1.3 ppm were close to significance when comparing the level at diagnosis with that at distant first relapse (P = .07, 6.5 vs 12.9). In 5 cases the MRS indicative of tumor preceded a formal diagnosis of relapse.
CONCLUSIONS: Tumor metabolite profiles, measured by MRS, do not change greatly from diagnosis to first relapse, and this can aid the confirmation of the presence of tumor.

Entities:  

Keywords:  MR spectroscopy; brain tumors; diagnosis; pediatrics; relapse.

Mesh:

Year:  2013        PMID: 24305716      PMCID: PMC3870841          DOI: 10.1093/neuonc/not143

Source DB:  PubMed          Journal:  Neuro Oncol        ISSN: 1522-8517            Impact factor:   12.300


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