Cargando…
Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation
Relative cerebral blood volume (rCBV) is a magnetic resonance imaging biomarker that is used to differentiate progression from pseudoprogression in patients with glioblastoma multiforme, the most common primary brain tumor. However, calculated rCBV depends considerably on the software used. Automati...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Grapho Publications, LLC
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5217187/ https://www.ncbi.nlm.nih.gov/pubmed/28066810 http://dx.doi.org/10.18383/j.tom.2016.00172 |
_version_ | 1782492057682575360 |
---|---|
author | Korfiatis, Panagiotis Kline, Timothy L. Kelm, Zachary S. Carter, Rickey E. Hu, Leland S. Erickson, Bradley J. |
author_facet | Korfiatis, Panagiotis Kline, Timothy L. Kelm, Zachary S. Carter, Rickey E. Hu, Leland S. Erickson, Bradley J. |
author_sort | Korfiatis, Panagiotis |
collection | PubMed |
description | Relative cerebral blood volume (rCBV) is a magnetic resonance imaging biomarker that is used to differentiate progression from pseudoprogression in patients with glioblastoma multiforme, the most common primary brain tumor. However, calculated rCBV depends considerably on the software used. Automating all steps required for rCBV calculation is important, as user interaction can lead to increased variability and possible inaccuracies in clinical decision-making. Here, we present an automated tool for computing rCBV from dynamic susceptibility contrast-magnetic resonance imaging that includes leakage correction. The entrance and exit bolus time points are automatically calculated using wavelet-based detection. The proposed tool is compared with 3 Food and Drug Administration-approved software packages, 1 automatic and 2 requiring user interaction, on a data set of 43 patients. We also evaluate manual and automated white matter (WM) selection for normalization of the cerebral blood volume maps. Our system showed good agreement with 2 of the 3 software packages. The intraclass correlation coefficient for all comparisons between the same software operated by different people was >0.880, except for FuncTool when operated by user 1 versus user 2. Little variability in agreement between software tools was observed when using different WM selection techniques. Our algorithm for automatic rCBV calculation with leakage correction and automated WM selection agrees well with 2 out of the 3 FDA-approved software packages. |
format | Online Article Text |
id | pubmed-5217187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Grapho Publications, LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-52171872017-01-06 Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation Korfiatis, Panagiotis Kline, Timothy L. Kelm, Zachary S. Carter, Rickey E. Hu, Leland S. Erickson, Bradley J. Tomography Research Articles Relative cerebral blood volume (rCBV) is a magnetic resonance imaging biomarker that is used to differentiate progression from pseudoprogression in patients with glioblastoma multiforme, the most common primary brain tumor. However, calculated rCBV depends considerably on the software used. Automating all steps required for rCBV calculation is important, as user interaction can lead to increased variability and possible inaccuracies in clinical decision-making. Here, we present an automated tool for computing rCBV from dynamic susceptibility contrast-magnetic resonance imaging that includes leakage correction. The entrance and exit bolus time points are automatically calculated using wavelet-based detection. The proposed tool is compared with 3 Food and Drug Administration-approved software packages, 1 automatic and 2 requiring user interaction, on a data set of 43 patients. We also evaluate manual and automated white matter (WM) selection for normalization of the cerebral blood volume maps. Our system showed good agreement with 2 of the 3 software packages. The intraclass correlation coefficient for all comparisons between the same software operated by different people was >0.880, except for FuncTool when operated by user 1 versus user 2. Little variability in agreement between software tools was observed when using different WM selection techniques. Our algorithm for automatic rCBV calculation with leakage correction and automated WM selection agrees well with 2 out of the 3 FDA-approved software packages. Grapho Publications, LLC 2016-12 /pmc/articles/PMC5217187/ /pubmed/28066810 http://dx.doi.org/10.18383/j.tom.2016.00172 Text en © 2016 The Authors. Published by Grapho Publications, LLC https://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Articles Korfiatis, Panagiotis Kline, Timothy L. Kelm, Zachary S. Carter, Rickey E. Hu, Leland S. Erickson, Bradley J. Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation |
title | Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation |
title_full | Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation |
title_fullStr | Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation |
title_full_unstemmed | Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation |
title_short | Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation |
title_sort | dynamic susceptibility contrast-mri quantification software tool: development and evaluation |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5217187/ https://www.ncbi.nlm.nih.gov/pubmed/28066810 http://dx.doi.org/10.18383/j.tom.2016.00172 |
work_keys_str_mv | AT korfiatispanagiotis dynamicsusceptibilitycontrastmriquantificationsoftwaretooldevelopmentandevaluation AT klinetimothyl dynamicsusceptibilitycontrastmriquantificationsoftwaretooldevelopmentandevaluation AT kelmzacharys dynamicsusceptibilitycontrastmriquantificationsoftwaretooldevelopmentandevaluation AT carterrickeye dynamicsusceptibilitycontrastmriquantificationsoftwaretooldevelopmentandevaluation AT hulelands dynamicsusceptibilitycontrastmriquantificationsoftwaretooldevelopmentandevaluation AT ericksonbradleyj dynamicsusceptibilitycontrastmriquantificationsoftwaretooldevelopmentandevaluation |