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Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting

OBJECTIVE: Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and...

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Autores principales: Eidel, Oliver, Neumann, Jan-Oliver, Burth, Sina, Kieslich, Pascal J., Jungk, Christine, Sahm, Felix, Kickingereder, Philipp, Kiening, Karl, Unterberg, Andreas, Wick, Wolfgang, Schlemmer, Heinz-Peter, Bendszus, Martin, Radbruch, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965093/
https://www.ncbi.nlm.nih.gov/pubmed/27467557
http://dx.doi.org/10.1371/journal.pone.0160250
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author Eidel, Oliver
Neumann, Jan-Oliver
Burth, Sina
Kieslich, Pascal J.
Jungk, Christine
Sahm, Felix
Kickingereder, Philipp
Kiening, Karl
Unterberg, Andreas
Wick, Wolfgang
Schlemmer, Heinz-Peter
Bendszus, Martin
Radbruch, Alexander
author_facet Eidel, Oliver
Neumann, Jan-Oliver
Burth, Sina
Kieslich, Pascal J.
Jungk, Christine
Sahm, Felix
Kickingereder, Philipp
Kiening, Karl
Unterberg, Andreas
Wick, Wolfgang
Schlemmer, Heinz-Peter
Bendszus, Martin
Radbruch, Alexander
author_sort Eidel, Oliver
collection PubMed
description OBJECTIVE: Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and cellularity values of stereotactic biopsies of glioblastoma patients using a new postprocessing approach including trajectory analysis and automatic nuclei counting. MATERIALS AND METHODS: Thirty-seven patients with newly diagnosed glioblastomas were enrolled in this study. ADC maps were acquired preoperatively at 3T and coregistered to the intraoperative MRI that contained the coordinates of the biopsy trajectory. 561 biopsy specimens were obtained; corresponding cellularity was calculated by semi-automatic nuclei counting and correlated to the respective preoperative ADC values along the stereotactic biopsy trajectory which included areas of T1-contrast-enhancement and necrosis. RESULTS: There was a weak to moderate inverse correlation between ADC and cellularity in glioblastomas that varied depending on the approach towards statistical analysis: for mean values per patient, Spearman’s ρ = -0.48 (p = 0.002), for all trajectory values in one joint analysis Spearman’s ρ = -0.32 (p < 0.001). The inverse correlation was additionally verified by a linear mixed model. CONCLUSIONS: Our data confirms a previously reported inverse correlation between ADC and tumor cellularity. However, the correlation in the current article is weaker than the pooled correlation of comparable previous studies. Hence, besides cell density, other factors, such as necrosis and edema might influence ADC values in glioblastomas.
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spelling pubmed-49650932016-08-18 Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting Eidel, Oliver Neumann, Jan-Oliver Burth, Sina Kieslich, Pascal J. Jungk, Christine Sahm, Felix Kickingereder, Philipp Kiening, Karl Unterberg, Andreas Wick, Wolfgang Schlemmer, Heinz-Peter Bendszus, Martin Radbruch, Alexander PLoS One Research Article OBJECTIVE: Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and cellularity values of stereotactic biopsies of glioblastoma patients using a new postprocessing approach including trajectory analysis and automatic nuclei counting. MATERIALS AND METHODS: Thirty-seven patients with newly diagnosed glioblastomas were enrolled in this study. ADC maps were acquired preoperatively at 3T and coregistered to the intraoperative MRI that contained the coordinates of the biopsy trajectory. 561 biopsy specimens were obtained; corresponding cellularity was calculated by semi-automatic nuclei counting and correlated to the respective preoperative ADC values along the stereotactic biopsy trajectory which included areas of T1-contrast-enhancement and necrosis. RESULTS: There was a weak to moderate inverse correlation between ADC and cellularity in glioblastomas that varied depending on the approach towards statistical analysis: for mean values per patient, Spearman’s ρ = -0.48 (p = 0.002), for all trajectory values in one joint analysis Spearman’s ρ = -0.32 (p < 0.001). The inverse correlation was additionally verified by a linear mixed model. CONCLUSIONS: Our data confirms a previously reported inverse correlation between ADC and tumor cellularity. However, the correlation in the current article is weaker than the pooled correlation of comparable previous studies. Hence, besides cell density, other factors, such as necrosis and edema might influence ADC values in glioblastomas. Public Library of Science 2016-07-28 /pmc/articles/PMC4965093/ /pubmed/27467557 http://dx.doi.org/10.1371/journal.pone.0160250 Text en © 2016 Eidel et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Eidel, Oliver
Neumann, Jan-Oliver
Burth, Sina
Kieslich, Pascal J.
Jungk, Christine
Sahm, Felix
Kickingereder, Philipp
Kiening, Karl
Unterberg, Andreas
Wick, Wolfgang
Schlemmer, Heinz-Peter
Bendszus, Martin
Radbruch, Alexander
Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting
title Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting
title_full Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting
title_fullStr Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting
title_full_unstemmed Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting
title_short Automatic Analysis of Cellularity in Glioblastoma and Correlation with ADC Using Trajectory Analysis and Automatic Nuclei Counting
title_sort automatic analysis of cellularity in glioblastoma and correlation with adc using trajectory analysis and automatic nuclei counting
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965093/
https://www.ncbi.nlm.nih.gov/pubmed/27467557
http://dx.doi.org/10.1371/journal.pone.0160250
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