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Role of FDG‐PET/MRI, FDG‐PET/CT, and Dynamic Susceptibility Contrast Perfusion MRI in Differentiating Radiation Necrosis from Tumor Recurrence in Glioblastomas
BACKGROUND AND PURPOSE: To compare the utility of quantitative PET/MRI, dynamic susceptibility contrast (DSC) perfusion MRI (pMRI), and PET/CT in differentiating radiation necrosis (RN) from tumor recurrence (TR) in patients with treated glioblastoma multiforme (GBM). METHODS: The study included 24...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811794/ https://www.ncbi.nlm.nih.gov/pubmed/28718993 http://dx.doi.org/10.1111/jon.12460 |
Sumario: | BACKGROUND AND PURPOSE: To compare the utility of quantitative PET/MRI, dynamic susceptibility contrast (DSC) perfusion MRI (pMRI), and PET/CT in differentiating radiation necrosis (RN) from tumor recurrence (TR) in patients with treated glioblastoma multiforme (GBM). METHODS: The study included 24 patients with GBM treated with surgery, radiotherapy, and temozolomide who presented with progression on imaging follow‐up. All patients underwent PET/MRI and pMRI during a single examination. Additionally, 19 of 24 patients underwent PET/CT on the same day. Diagnosis was established by pathology in 17 of 24 and by clinical/radiologic consensus in 7 of 24. For the quantitative PET/MRI and PET/CT analysis, a region of interest (ROI) was drawn around each lesion and within the contralateral white matter. Lesion to contralateral white matter ratios for relative maximum, mean, and median were calculated. For pMRI, lesion ROI was drawn on the cerebral blood volume (CBV) maps and histogram metrics were calculated. Diagnostic performance for each metric was assessed using receiver operating characteristic curve analysis and area under curve (AUC) was calculated. RESULTS: In 24 patients, 28 lesions were identified. For PET/MRI, relative mean ≥ 1.31 resulted in AUC of .94 with both sensitivity and negative predictive values (NPVs) of 100%. For pMRI, CBV max ≥3.32 yielded an AUC of .94 with both sensitivity and NPV measuring 100%. The joint model utilizing r‐mean (PET/MRI) and CBV mode (pMRI) resulted in AUC of 1.0. CONCLUSION: Our study demonstrates that quantitative PET/MRI parameters in combination with DSC pMRI provide the best diagnostic utility in distinguishing RN from TR in treated GBMs. |
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