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Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging

Purpose: This study aimed to assess the relationship between mean kurtosis (MK) and mean diffusivity (MD) values from whole-brain diffusion kurtosis imaging (DKI) parametric maps in preoperative magnetic resonance (MR) images from 2016 World Health Organization Classification of Tumors of the Centra...

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Autores principales: Hempel, Johann-Martin, Brendle, Cornelia, Adib, Sasan Darius, Behling, Felix, Tabatabai, Ghazaleh, Castaneda Vega, Salvador, Schittenhelm, Jens, Ernemann, Ulrike, Klose, Uwe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199055/
https://www.ncbi.nlm.nih.gov/pubmed/34073442
http://dx.doi.org/10.3390/jcm10112325
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author Hempel, Johann-Martin
Brendle, Cornelia
Adib, Sasan Darius
Behling, Felix
Tabatabai, Ghazaleh
Castaneda Vega, Salvador
Schittenhelm, Jens
Ernemann, Ulrike
Klose, Uwe
author_facet Hempel, Johann-Martin
Brendle, Cornelia
Adib, Sasan Darius
Behling, Felix
Tabatabai, Ghazaleh
Castaneda Vega, Salvador
Schittenhelm, Jens
Ernemann, Ulrike
Klose, Uwe
author_sort Hempel, Johann-Martin
collection PubMed
description Purpose: This study aimed to assess the relationship between mean kurtosis (MK) and mean diffusivity (MD) values from whole-brain diffusion kurtosis imaging (DKI) parametric maps in preoperative magnetic resonance (MR) images from 2016 World Health Organization Classification of Tumors of the Central Nervous System integrated glioma groups. Methods: Seventy-seven patients with histopathologically confirmed treatment-naïve glioma were retrospectively assessed between 1 August 2013 and 30 October 2017. The area on scatter plots with a specific combination of MK and MD values, not occurring in the healthy brain, was labeled, and the corresponding voxels were visualized on the fluid-attenuated inversion recovery (FLAIR) images. Reversely, the labeled voxels were compared to those of the manually segmented tumor volume, and the Dice similarity coefficient was used to investigate their spatial overlap. Results: A specific combination of MK and MD values in whole-brain DKI maps, visualized on a two-dimensional scatter plot, exclusively occurs in glioma tissue including the perifocal infiltrative zone and is absent in tissue of the normal brain or from other intracranial compartments. Conclusions: A unique diffusion signature with a specific combination of MK and MD values from whole-brain DKI can identify diffuse glioma without any previous segmentation. This feature might influence artificial intelligence algorithms for automatic tumor segmentation and provide new aspects of tumor heterogeneity.
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spelling pubmed-81990552021-06-14 Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging Hempel, Johann-Martin Brendle, Cornelia Adib, Sasan Darius Behling, Felix Tabatabai, Ghazaleh Castaneda Vega, Salvador Schittenhelm, Jens Ernemann, Ulrike Klose, Uwe J Clin Med Article Purpose: This study aimed to assess the relationship between mean kurtosis (MK) and mean diffusivity (MD) values from whole-brain diffusion kurtosis imaging (DKI) parametric maps in preoperative magnetic resonance (MR) images from 2016 World Health Organization Classification of Tumors of the Central Nervous System integrated glioma groups. Methods: Seventy-seven patients with histopathologically confirmed treatment-naïve glioma were retrospectively assessed between 1 August 2013 and 30 October 2017. The area on scatter plots with a specific combination of MK and MD values, not occurring in the healthy brain, was labeled, and the corresponding voxels were visualized on the fluid-attenuated inversion recovery (FLAIR) images. Reversely, the labeled voxels were compared to those of the manually segmented tumor volume, and the Dice similarity coefficient was used to investigate their spatial overlap. Results: A specific combination of MK and MD values in whole-brain DKI maps, visualized on a two-dimensional scatter plot, exclusively occurs in glioma tissue including the perifocal infiltrative zone and is absent in tissue of the normal brain or from other intracranial compartments. Conclusions: A unique diffusion signature with a specific combination of MK and MD values from whole-brain DKI can identify diffuse glioma without any previous segmentation. This feature might influence artificial intelligence algorithms for automatic tumor segmentation and provide new aspects of tumor heterogeneity. MDPI 2021-05-26 /pmc/articles/PMC8199055/ /pubmed/34073442 http://dx.doi.org/10.3390/jcm10112325 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hempel, Johann-Martin
Brendle, Cornelia
Adib, Sasan Darius
Behling, Felix
Tabatabai, Ghazaleh
Castaneda Vega, Salvador
Schittenhelm, Jens
Ernemann, Ulrike
Klose, Uwe
Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging
title Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging
title_full Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging
title_fullStr Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging
title_full_unstemmed Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging
title_short Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging
title_sort glioma-specific diffusion signature in diffusion kurtosis imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199055/
https://www.ncbi.nlm.nih.gov/pubmed/34073442
http://dx.doi.org/10.3390/jcm10112325
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