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Comparison of Two Mathematical Models of Cellularity Calculation

OBJECT: Nowadays, there is increasing evidence that functional magnetic resonance imaging (MRI) modalities, namely, diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI (DCE MRI), can characterize tumor architecture like cellularity and vascularity. Previously, two formulas based on a...

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Autores principales: Meyer, Hans Jonas, Garnov, Nikita, Surov, Alexey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Neoplasia Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884215/
https://www.ncbi.nlm.nih.gov/pubmed/29413764
http://dx.doi.org/10.1016/j.tranon.2018.01.020
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author Meyer, Hans Jonas
Garnov, Nikita
Surov, Alexey
author_facet Meyer, Hans Jonas
Garnov, Nikita
Surov, Alexey
author_sort Meyer, Hans Jonas
collection PubMed
description OBJECT: Nowadays, there is increasing evidence that functional magnetic resonance imaging (MRI) modalities, namely, diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI (DCE MRI), can characterize tumor architecture like cellularity and vascularity. Previously, two formulas based on a logistic tumor growth model were proposed to predict tumor cellularity with DWI and DCE. The purpose of this study was to proof these formulas. METHODS: 16 patients with head and neck squamous cell carcinomas were included into the study. There were 2 women and 14 men with a mean age of 57.0 ± 7.5 years. In every case, tumor cellularity was calculated using the proposed formulas by Atuegwu et al. In every case, also tumor cell count was estimated on histopathological specimens as an average cell count per 2 to 5 high-power fields. RESULTS: There was no significant correlation between the calculated cellularity and histopathologically estimated cell count by using the formula based on apparent diffusion coefficient (ADC) values. A moderate positive correlation (r=0.515, P=.041) could be identified by using the formula including ADC and V(e) values. CONCLUSIONS: The formula including ADC and V(e) values is more sensitive to predict tumor cellularity than the formula including ADC values only.
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spelling pubmed-58842152018-04-06 Comparison of Two Mathematical Models of Cellularity Calculation Meyer, Hans Jonas Garnov, Nikita Surov, Alexey Transl Oncol Original article OBJECT: Nowadays, there is increasing evidence that functional magnetic resonance imaging (MRI) modalities, namely, diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI (DCE MRI), can characterize tumor architecture like cellularity and vascularity. Previously, two formulas based on a logistic tumor growth model were proposed to predict tumor cellularity with DWI and DCE. The purpose of this study was to proof these formulas. METHODS: 16 patients with head and neck squamous cell carcinomas were included into the study. There were 2 women and 14 men with a mean age of 57.0 ± 7.5 years. In every case, tumor cellularity was calculated using the proposed formulas by Atuegwu et al. In every case, also tumor cell count was estimated on histopathological specimens as an average cell count per 2 to 5 high-power fields. RESULTS: There was no significant correlation between the calculated cellularity and histopathologically estimated cell count by using the formula based on apparent diffusion coefficient (ADC) values. A moderate positive correlation (r=0.515, P=.041) could be identified by using the formula including ADC and V(e) values. CONCLUSIONS: The formula including ADC and V(e) values is more sensitive to predict tumor cellularity than the formula including ADC values only. Neoplasia Press 2018-02-03 /pmc/articles/PMC5884215/ /pubmed/29413764 http://dx.doi.org/10.1016/j.tranon.2018.01.020 Text en © 2018 The Authors. Published by Elsevier Inc. on behalf of Neoplasia Press, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original article
Meyer, Hans Jonas
Garnov, Nikita
Surov, Alexey
Comparison of Two Mathematical Models of Cellularity Calculation
title Comparison of Two Mathematical Models of Cellularity Calculation
title_full Comparison of Two Mathematical Models of Cellularity Calculation
title_fullStr Comparison of Two Mathematical Models of Cellularity Calculation
title_full_unstemmed Comparison of Two Mathematical Models of Cellularity Calculation
title_short Comparison of Two Mathematical Models of Cellularity Calculation
title_sort comparison of two mathematical models of cellularity calculation
topic Original article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884215/
https://www.ncbi.nlm.nih.gov/pubmed/29413764
http://dx.doi.org/10.1016/j.tranon.2018.01.020
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