Evaluation of radiation necrosis and malignant glioma in rat models using diffusion tensor MR imaging

Silun Wang, Yifei Chen, Bachchu Lal, Eric Ford, Erik Tryggestad, Michael Armour, Kun Yan, John Laterra, Jinyuan Zhou

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Standard MRI cannot distinguish between radiation necrosis and tumor progression; however, this distinction is critical in the assessment of tumor response to therapy. In this study, one delayed radiation necrosis model (dose, 40 Gy; radiation field, 10 × 10 mm 2; n = 13) and two orthotopic glioma models in rats (9L gliosarcoma, n =8; human glioma xenografts, n = 5) were compared using multiple diffusion tensor imaging (DTI) indices. A visible isotropic apparent diffusion coefficient (ADC) pattern was observed in the lesion due to radiation necrosis, which consisted of a hypointense central zone and a hyperintense peripheral zone. There were significantly lower ADC, parallel diffusivity, and perpendicular diffusivity in the necrotic central zone than in the peripheral zone (all P<0.001). When radiation-induced necrosis was compared with viable tumor, radiation necrosis had significantly lower ADC than 9L gliosarcoma and human glioma xenografts (both P<0.01) in the central zone, and significantly lower fractional anisotropy than 9L gliosarcoma (P = 0.005) and human glioma xenografts (P = 0.012) in the peripheral zone. Histological analysis revealed parenchymal coagulative necrosis in the central zone, and damaged vessels and reactive astrogliosis in the peripheral zone. These data suggest that qualitative and quantitative analysis of the DTI maps can provide useful information by which to distinguish between radiation necrosis and viable glioma.

Original languageEnglish (US)
Pages (from-to)51-60
Number of pages10
JournalJournal of neuro-oncology
Volume107
Issue number1
DOIs
StatePublished - Mar 2012

Keywords

  • DTI
  • Glioma
  • MRI
  • Radiation necrosis
  • Rat
  • Tumor recurrence

ASJC Scopus subject areas

  • Oncology
  • Neurology
  • Clinical Neurology
  • Cancer Research

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