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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-8199055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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