Literature DB >> 22403168

Gliomas: diffusion kurtosis MR imaging in grading.

Sofie Van Cauter1, Jelle Veraart, Jan Sijbers, Ronald R Peeters, Uwe Himmelreich, Frederik De Keyzer, Stefaan W Van Gool, Frank Van Calenbergh, Steven De Vleeschouwer, Wim Van Hecke, Stefan Sunaert.   

Abstract

PURPOSE: To assess the diagnostic accuracy of diffusion kurtosis magnetic resonance imaging parameters in grading gliomas.
MATERIALS AND METHODS: The institutional review board approved this prospective study, and informed consent was obtained from all patients. Diffusion parameters-mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis, and radial and axial kurtosis-were compared in the solid parts of 17 high-grade gliomas and 11 low-grade gliomas (P<.05 significance level, Mann-Whitney-Wilcoxon test, Bonferroni correction). MD, FA, mean kurtosis, radial kurtosis, and axial kurtosis in solid tumors were also normalized to the corresponding values in contralateral normal-appearing white matter (NAWM) and the contralateral posterior limb of the internal capsule (PLIC) after age correction and were compared among tumor grades.
RESULTS: Mean, radial, and axial kurtosis were significantly higher in high-grade gliomas than in low-grade gliomas (P = .02, P = .015, and P = .01, respectively). FA and MD did not significantly differ between glioma grades. All values, except for axial kurtosis, that were normalized to the values in the contralateral NAWM were significantly different between high-grade and low-grade gliomas (mean kurtosis, P = .02; radial kurtosis, P = .03; FA, P = .025; and MD, P = .03). When values were normalized to those in the contralateral PLIC, none of the considered parameters showed significant differences between high-grade and low-grade gliomas. The highest sensitivity and specificity for discriminating between high-grade and low-grade gliomas were found for mean kurtosis (71% and 82%, respectively) and mean kurtosis normalized to the value in the contralateral NAWM (100% and 73%, respectively). Optimal thresholds for mean kurtosis and mean kurtosis normalized to the value in the contralateral NAWM for differentiating high-grade from low-grade gliomas were 0.52 and 0.51, respectively.
CONCLUSION: There were significant differences in kurtosis parameters between high-grade and low-grade gliomas; hence, better separation was achieved with these parameters than with conventional diffusion imaging parameters.

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Year:  2012        PMID: 22403168     DOI: 10.1148/radiol.12110927

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  120 in total

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Review 2.  Physics, Techniques and Review of Neuroradiological Applications of Diffusion Kurtosis Imaging (DKI).

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4.  Mono-exponential, diffusion kurtosis and stretched exponential diffusion MR imaging response to chemoradiation in newly diagnosed glioblastoma.

Authors:  Ararat Chakhoyan; Davis C Woodworth; Robert J Harris; Albert Lai; Phioanh L Nghiemphu; Linda M Liau; Whitney B Pope; Timothy F Cloughesy; Benjamin M Ellingson
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5.  The value of diffusion kurtosis magnetic resonance imaging for assessing treatment response of neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Authors:  Jing Yu; Qing Xu; Jia-Cheng Song; Yan Li; Xin Dai; Dong-Ya Huang; Ling Zhang; Yang Li; Hai-Bin Shi
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6.  Comparison of image sensitivity between conventional tensor-based and fast diffusion kurtosis imaging protocols in a rodent model of acute ischemic stroke.

Authors:  Yin Wu; Jinsuh Kim; Suk-Tak Chan; Iris Yuwen Zhou; Yingkun Guo; Takahiro Igarashi; Hairong Zheng; Gang Guo; Phillip Zhe Sun
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7.  Diffusion Kurtosis Imaging as a Tool in Neurotoxicology.

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8.  Diffusion kurtosis imaging in the characterisation of rectal cancer: utilizing the most repeatable region-of-interest strategy for diffusion parameters on a 3T scanner.

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Journal:  Eur Radiol       Date:  2018-05-24       Impact factor: 5.315

9.  Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging.

Authors:  Alicia W Yang; Jens H Jensen; Caixia C Hu; Ali Tabesh; Maria F Falangola; Joseph A Helpern
Journal:  J Magn Reson Imaging       Date:  2012-10-03       Impact factor: 4.813

Review 10.  Clinical applications for diffusion magnetic resonance imaging in radiotherapy.

Authors:  Christina Tsien; Yue Cao; Thomas Chenevert
Journal:  Semin Radiat Oncol       Date:  2014-07       Impact factor: 5.934

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