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Torben Ellegaard Lund

Mean Diffusional Kurtosis in Patients with Glioma: Initial Results with a Fast Imaging Method in a Clinical Setting

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Mean Diffusional Kurtosis in Patients with Glioma : Initial Results with a Fast Imaging Method in a Clinical Setting. / Tietze, A.; Hansen, Mikkel Bo; Østergaard, Leif; Jespersen, S. N.; Sangill, R.; Lund, T. E.; Geneser, M.; Hjelm, Mette; Hansen, Brian.

In: American Journal of Neuroradiology, Vol. 36, No. 8, 08.2015, p. 1472-1478.

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@article{a36898e6076746e6ac03a28b412009cc,
title = "Mean Diffusional Kurtosis in Patients with Glioma: Initial Results with a Fast Imaging Method in a Clinical Setting",
abstract = "Background: Diffusion Kurtosis Imaging (DKI) is a MRI technique that provides microstructural information in biological systems. Its application in clinical studies is, however, hampered by long acquisition times and heavy post-processing. We evaluate a new and fast (2 min., 46 s) DKI method with regard to glioma grading, compare it to conventional DKI and compare the diagnostic accuracy of mean kurtosis (MK{\textquoteright}) to that of the widely used mean diffusivity (MD). Material and Methods: MK{\textquoteright} and MD were measured in the contrast-enhancing tumor core, the peri-focal hyperintensity on T2FLAIR, and the contralateral normal appearing white and grey matter of 34 patients (22 high-grade, 12 low-grade gliomas). MK{\textquoteright} and MD in different grades were compared using a Wilcoxon rank-sum test. Receiver Operating Characteristic curves and the area under the curve were calculated to determine the diagnostic accuracy of MK{\textquoteright} and MD. Results: MK{\textquoteright} in the tumor core, but not MD, could differentiate high-grade from low-grade gliomas, and MK{\textquoteright} separated glioblastomas from the remaining gliomas with high accuracy (AUCMK{\textquoteright}=0.842; pMK{\textquoteright}<0.001). MK{\textquoteright} and MD identified glioblastomas in the group of high-grade gliomas with similar significance and accuracy (AUCMK{\textquoteright}=886; AUCMD=0.876; pMK{\textquoteright}=0.003; pMD=0.004). The mean MK{\textquoteright} in all tissue types was comparable to those obtained by conventional DKI. Conclusion: The DKI approach used here is considerably faster than conventional DKI methods, while yielding comparable results. It can be accommodated in clinical protocols and allows exploring the role of MK{\textquoteright} as a biomarker in determining glioma subtypes or response evaluation.",
keywords = "GAUSSIAN WATER DIFFUSION, OUTCOME PREDICTION, CEREBRAL GLIOMAS, BRAIN, TUMOR, GLIOBLASTOMA, COEFFICIENTS, BIOMARKERS, PARAMETERS, MRI",
author = "A. Tietze and Hansen, {Mikkel Bo} and Leif {\O}stergaard and Jespersen, {S. N.} and R. Sangill and Lund, {T. E.} and M. Geneser and Mette Hjelm and Brian Hansen",
year = "2015",
month = aug,
doi = "10.3174/ajnr.A4311",
language = "English",
volume = "36",
pages = "1472--1478",
journal = "American Journal of Neuroradiology",
issn = "0195-6108",
publisher = "American Society of Neuroradiology",
number = "8",

}

RIS

TY - JOUR

T1 - Mean Diffusional Kurtosis in Patients with Glioma

T2 - Initial Results with a Fast Imaging Method in a Clinical Setting

AU - Tietze, A.

AU - Hansen, Mikkel Bo

AU - Østergaard, Leif

AU - Jespersen, S. N.

AU - Sangill, R.

AU - Lund, T. E.

AU - Geneser, M.

AU - Hjelm, Mette

AU - Hansen, Brian

PY - 2015/8

Y1 - 2015/8

N2 - Background: Diffusion Kurtosis Imaging (DKI) is a MRI technique that provides microstructural information in biological systems. Its application in clinical studies is, however, hampered by long acquisition times and heavy post-processing. We evaluate a new and fast (2 min., 46 s) DKI method with regard to glioma grading, compare it to conventional DKI and compare the diagnostic accuracy of mean kurtosis (MK’) to that of the widely used mean diffusivity (MD). Material and Methods: MK’ and MD were measured in the contrast-enhancing tumor core, the peri-focal hyperintensity on T2FLAIR, and the contralateral normal appearing white and grey matter of 34 patients (22 high-grade, 12 low-grade gliomas). MK’ and MD in different grades were compared using a Wilcoxon rank-sum test. Receiver Operating Characteristic curves and the area under the curve were calculated to determine the diagnostic accuracy of MK’ and MD. Results: MK’ in the tumor core, but not MD, could differentiate high-grade from low-grade gliomas, and MK’ separated glioblastomas from the remaining gliomas with high accuracy (AUCMK’=0.842; pMK’<0.001). MK’ and MD identified glioblastomas in the group of high-grade gliomas with similar significance and accuracy (AUCMK’=886; AUCMD=0.876; pMK’=0.003; pMD=0.004). The mean MK’ in all tissue types was comparable to those obtained by conventional DKI. Conclusion: The DKI approach used here is considerably faster than conventional DKI methods, while yielding comparable results. It can be accommodated in clinical protocols and allows exploring the role of MK’ as a biomarker in determining glioma subtypes or response evaluation.

AB - Background: Diffusion Kurtosis Imaging (DKI) is a MRI technique that provides microstructural information in biological systems. Its application in clinical studies is, however, hampered by long acquisition times and heavy post-processing. We evaluate a new and fast (2 min., 46 s) DKI method with regard to glioma grading, compare it to conventional DKI and compare the diagnostic accuracy of mean kurtosis (MK’) to that of the widely used mean diffusivity (MD). Material and Methods: MK’ and MD were measured in the contrast-enhancing tumor core, the peri-focal hyperintensity on T2FLAIR, and the contralateral normal appearing white and grey matter of 34 patients (22 high-grade, 12 low-grade gliomas). MK’ and MD in different grades were compared using a Wilcoxon rank-sum test. Receiver Operating Characteristic curves and the area under the curve were calculated to determine the diagnostic accuracy of MK’ and MD. Results: MK’ in the tumor core, but not MD, could differentiate high-grade from low-grade gliomas, and MK’ separated glioblastomas from the remaining gliomas with high accuracy (AUCMK’=0.842; pMK’<0.001). MK’ and MD identified glioblastomas in the group of high-grade gliomas with similar significance and accuracy (AUCMK’=886; AUCMD=0.876; pMK’=0.003; pMD=0.004). The mean MK’ in all tissue types was comparable to those obtained by conventional DKI. Conclusion: The DKI approach used here is considerably faster than conventional DKI methods, while yielding comparable results. It can be accommodated in clinical protocols and allows exploring the role of MK’ as a biomarker in determining glioma subtypes or response evaluation.

KW - GAUSSIAN WATER DIFFUSION

KW - OUTCOME PREDICTION

KW - CEREBRAL GLIOMAS

KW - BRAIN

KW - TUMOR

KW - GLIOBLASTOMA

KW - COEFFICIENTS

KW - BIOMARKERS

KW - PARAMETERS

KW - MRI

U2 - 10.3174/ajnr.A4311

DO - 10.3174/ajnr.A4311

M3 - Journal article

C2 - 25977481

VL - 36

SP - 1472

EP - 1478

JO - American Journal of Neuroradiology

JF - American Journal of Neuroradiology

SN - 0195-6108

IS - 8

ER -