Pretreatment texture analysis of routine MR images and shape analysis of the diffusion tensor for prediction of volumetric response after radiosurgery for meningioma.

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ID: 109832
2018
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Abstract
OBJECTIVEThe goal of this study was to identify parameters from routine T1- and T2-weighted MR sequences and diffusion tensor imaging (DTI) that best predict the volumetric changes in a meningioma after treatment with Gamma Knife radiosurgery (GKRS).METHODSIn 32 patients with meningioma, routine MRI and DTI data were measured before GKRS. A total of 78 parameters derived from first-level texture analysis of the pretreatment MR images, including calculation of the mean, SD, 2.5th and 97.5th percentiles, and kurtosis and skewness of data in histograms on a voxel-wise basis, were correlated with lesion volume change after a mean follow-up period of 3 years (range 19.5-63.3 months).RESULTSSeveral DTI-derived parameters correlated significantly with a meningioma volume change. The parameter that best predicted the results of GKRS was the 2.5th percentile value of the smallest eigenvalue (L3) of the diffusion tensor (correlation coefficient 0.739, p ≤ 0.001), whereas among the non-DTI parameters, only the SD of T2-weighted images correlated significantly with a tumor volume change (correlation coefficient 0.505, p ≤ 0.05, after correction for family-wise errors using false-detection-rate correction).CONCLUSIONSDTI-derived data had a higher correlation to shrinkage of meningioma volume after GKRS than data from T1- and T2-weighted image sequences. However, if only routine MR images are available, the SD of T2-weighted images can be used to predict control or possible progression of a meningioma after GKRS.
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speckter2018pretreatmentjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal journal of neurosurgery
Year 2018
DOI
10.3171/2018.7.GKS181327
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