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Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer

In this work, the two compartment exchange model and two compartment uptake model were applied to obtain quantitative perfusion parameters in rectum carcinoma and the results were compared to those obtained by the deconvolution algorithm. Eighteen patients with newly diagnosed rectal carcinoma under...

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Autores principales: Gaa, Tanja, Neumann, Wiebke, Sudarski, Sonja, Attenberger, Ulrike I., Schönberg, Stefan O., Schad, Lothar R., Zöllner, Frank G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5607266/
https://www.ncbi.nlm.nih.gov/pubmed/28931946
http://dx.doi.org/10.1038/s41598-017-12194-w
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author Gaa, Tanja
Neumann, Wiebke
Sudarski, Sonja
Attenberger, Ulrike I.
Schönberg, Stefan O.
Schad, Lothar R.
Zöllner, Frank G.
author_facet Gaa, Tanja
Neumann, Wiebke
Sudarski, Sonja
Attenberger, Ulrike I.
Schönberg, Stefan O.
Schad, Lothar R.
Zöllner, Frank G.
author_sort Gaa, Tanja
collection PubMed
description In this work, the two compartment exchange model and two compartment uptake model were applied to obtain quantitative perfusion parameters in rectum carcinoma and the results were compared to those obtained by the deconvolution algorithm. Eighteen patients with newly diagnosed rectal carcinoma underwent 3 T MRI of the pelvis including a T(1) weighted dynamic contrastenhanced (DCE) protocol before treatment. Mean values for Plasma Flow (PF), Plasma Volume (PV) and Mean Transit Time (MTT) were obtained for all three approaches and visualized in parameter cards. For the two compartment models, Akaike Information Criterion (AIC) and [Formula: see text] were calculated. Perfusion parameters determined with the compartment models show results in accordance with previous studies focusing on rectal cancer DCE-CT (PF(2CX) = 68 ± 44 ml/100 ml/min, PF(2CU) = 55 ± 36 ml/100 ml/min) with similar fit quality (AIC:169 ± 81/179 ± 77, [Formula: see text] :10 ± 12/9 ± 10). Values for PF are overestimated whereas PV and MTT are underestimated compared to results of the deconvolution algorithm. Significant differences were found among all models for perfusion parameters as well as between the AIC and [Formula: see text] values. Quantitative perfusion parameters are dependent on the chosen tracer kinetic model. According to the obtained parameters, all approaches seem capable of providing quantitative perfusion values in DCE-MRI of rectal cancer.
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spelling pubmed-56072662017-09-24 Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer Gaa, Tanja Neumann, Wiebke Sudarski, Sonja Attenberger, Ulrike I. Schönberg, Stefan O. Schad, Lothar R. Zöllner, Frank G. Sci Rep Article In this work, the two compartment exchange model and two compartment uptake model were applied to obtain quantitative perfusion parameters in rectum carcinoma and the results were compared to those obtained by the deconvolution algorithm. Eighteen patients with newly diagnosed rectal carcinoma underwent 3 T MRI of the pelvis including a T(1) weighted dynamic contrastenhanced (DCE) protocol before treatment. Mean values for Plasma Flow (PF), Plasma Volume (PV) and Mean Transit Time (MTT) were obtained for all three approaches and visualized in parameter cards. For the two compartment models, Akaike Information Criterion (AIC) and [Formula: see text] were calculated. Perfusion parameters determined with the compartment models show results in accordance with previous studies focusing on rectal cancer DCE-CT (PF(2CX) = 68 ± 44 ml/100 ml/min, PF(2CU) = 55 ± 36 ml/100 ml/min) with similar fit quality (AIC:169 ± 81/179 ± 77, [Formula: see text] :10 ± 12/9 ± 10). Values for PF are overestimated whereas PV and MTT are underestimated compared to results of the deconvolution algorithm. Significant differences were found among all models for perfusion parameters as well as between the AIC and [Formula: see text] values. Quantitative perfusion parameters are dependent on the chosen tracer kinetic model. According to the obtained parameters, all approaches seem capable of providing quantitative perfusion values in DCE-MRI of rectal cancer. Nature Publishing Group UK 2017-09-20 /pmc/articles/PMC5607266/ /pubmed/28931946 http://dx.doi.org/10.1038/s41598-017-12194-w Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gaa, Tanja
Neumann, Wiebke
Sudarski, Sonja
Attenberger, Ulrike I.
Schönberg, Stefan O.
Schad, Lothar R.
Zöllner, Frank G.
Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer
title Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer
title_full Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer
title_fullStr Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer
title_full_unstemmed Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer
title_short Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer
title_sort comparison of perfusion models for quantitative t1 weighted dce-mri of rectal cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5607266/
https://www.ncbi.nlm.nih.gov/pubmed/28931946
http://dx.doi.org/10.1038/s41598-017-12194-w
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