Publication: The use of treatment response assessment maps in discriminating between radiation effect and persistent tumoral lesion in metastatic brain tumors treated with Gamma Knife radiosurgery
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Background: Traditional imaging modalities are not useful in the follow-up of irradiated metastatic brain tumors, because radiation can change imaging characteristics. We aimed to assess the ability of treatment response assessment maps (TRAMs) calculated from delayed-contrast magnetic resonance imaging (MRI) in differentiation between radiation effect and persistent tumoral tissue. Methods: TRAMs were calculated by subtracting three-dimensional T1 MRIs acquired 5 minutes after contrast injection from the images acquired 60–105 minutes later. Red areas were regarded as radiation effect and blue areas as persistent tumoral lesion. Thirty-seven patients with 130 metastatic brain tumors who were treated with Gamma Knife radiosurgery and who underwent TRAMs perfusion-weighted MRI were enrolled in this retrospective study. Results: The median age was 58 years and the most common primary diagnosis was lung cancer (n = 21). The median follow-up period of patients was 12 months. The overall local control rate was 100% at 1 year and 98.9% at 2 years. The median progression-free survival was 12 months. The mean overall survival was 27.3 months. The radiologic and clinical follow-up showed a clinicoradiologic diagnosis of a persistent tumoral lesion in 3 tumors (2.3%) and radiation effect in 127 tumors (97.7%). There was a fair agreement between clinicoradiologic diagnosis and TRAMs analysis (κ = 0.380). The sensitivity and positive predictive value of TRAMs in diagnosing radiation effect were 96.06% and 99.2%, respectively. TRAMs showed comparable results to perfusion-weighted MRI, with a diagnostic odds ratio of 27.4 versus 20.7, respectively. Conclusions: The presented results show the ability of TRAMs in differentiating radiation effect and persistent tumoral lesions.
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Elsevier
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Medicine, Radiosurgery and radiation oncology, Neuro-oncology imaging
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World Neurosurgery
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10.1016/j.wneu.2020.11.114
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