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Prediction of radiation necrosis in a rodent model using magnetic resonance imaging apparent transverse relaxation (R2∗)

  • Jean Guy Belliveau
    ,
  • Michael D. Jensen
    ,
  • James M.P. Stewart
    ,
  • Igor Solovey
    ,
  • L. Martyn Klassen
    ,
  • Glenn S. Bauman
Scholary Output:
Contribution to journal
Article
Peer-review

Abstract

Background and purpose. Radiation necrosis remains an irreversible long-term side-effect following radiotherapy to the brain. The ability to predict areas that could ultimately develop into necrosis could lead to prevention and management of radiation necrosis. Materials and Methods. Fischer 344 rats were irradiated using two platforms (micro-CT irradiator and x-Rad 225 IGRT) with radiation up to 30 Gy for the micro-CT and 40 Gy for the xRAD-224 to half the brain. Animals were subsequently imaged using a 9.4 T MRI scanner every 2-4 weeks for up to 28 weeks using a 7-echo gradient echo sequence. The apparent transverse relaxation constant (R2∗) was calculated and retrospectively analyzed. Results. Animals irradiated with the low-dose rate micro-CT did not exhibit any symptoms or imaging changes associated with RN. Animals irradiated with the xRAD-225 exhibited imaging changes consistent with RN at week 24. Analysis of the coefficient within the lesion and hippocampus shows the potential for detection of RN up to 10 weeks prior to morphological changes. Conclusions. The ability to predict areas of RN and increases of within the hippocampus provides a method for long-term monitoring and prediction of RN.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Article number

035010

Journal (Volume, Issue Number)

Physics in Medicine and Biology (Volume 63, Issue 3)

Publication milestones

  • Published - 02/2018

Publication status

Published - 02/2018

ISSN

0031-9155

Publication IDs

  • Scopus: 85041961802
  • PubMed: 29372691
  • ORCID: /0000-0003-2701-5758/work/58927859

Publication metrics

Metrics

SciVal
FWCI
0.66
SciVal
Author count
7
SciVal
citations
5
SciVal
Paper percentile
67
Scopus
citations
Fractional count
1
Fractional count
0.14
Fractional count
6
Fractional count
0.86
Fractional count
1
Fractional count
1

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Captures
12
Citation count
7