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Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation

OBJECTIVES: Dynamic contrast-enhanced MR images can be analyzed through the application of a wide range of kinetic models. This process is prone to variability and a lack of standardization that can affect the measured metrics. There is a need for customized digital reference objects (DROs) for the...

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Autores principales: Gill, Andrew B., Gallagher, Ferdia A., Graves, Martin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The British Institute of Radiology. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10321261/
https://www.ncbi.nlm.nih.gov/pubmed/37191274
http://dx.doi.org/10.1259/bjr.20220976
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author Gill, Andrew B.
Gallagher, Ferdia A.
Graves, Martin J.
author_facet Gill, Andrew B.
Gallagher, Ferdia A.
Graves, Martin J.
author_sort Gill, Andrew B.
collection PubMed
description OBJECTIVES: Dynamic contrast-enhanced MR images can be analyzed through the application of a wide range of kinetic models. This process is prone to variability and a lack of standardization that can affect the measured metrics. There is a need for customized digital reference objects (DROs) for the validation of DCE-MRI software packages that undertake kinetic model analysis. DROs are currently available only for a small subset of the kinetic models commonly applied to DCE-MRI data. This work aimed to address this gap. METHODS: Code was written in the MATLAB programming environment to generate customizable DROs. This modular code allows the insertion of a plug-in to describe the kinetic model to be tested. We input our generated DROs into three commercial and open-source analysis packages and assessed the agreement of kinetic model parameter values output with the ‘ground-truth’ values used in the DRO generation. RESULTS: For the five kinetic models tested, the concordance correlation coefficient values were >98%, indicating excellent agreement of the results with ‘ground-truth’. CONCLUSIONS: Testing our DROs on three independent software packages produced concordant results, strongly suggesting our DRO generation code is correct. This implies that our DROs can be used to validate other third party software for the kinetic model analysis of DCE-MRI data. ADVANCES IN KNOWLEDGE: This work extends published work of others to allow customized generation of test objects for any applied kinetic model and allows the incorporation of B(1) mapping into the DRO for application at higher field strengths.
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spelling pubmed-103212612023-07-06 Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation Gill, Andrew B. Gallagher, Ferdia A. Graves, Martin J. Br J Radiol Full Paper OBJECTIVES: Dynamic contrast-enhanced MR images can be analyzed through the application of a wide range of kinetic models. This process is prone to variability and a lack of standardization that can affect the measured metrics. There is a need for customized digital reference objects (DROs) for the validation of DCE-MRI software packages that undertake kinetic model analysis. DROs are currently available only for a small subset of the kinetic models commonly applied to DCE-MRI data. This work aimed to address this gap. METHODS: Code was written in the MATLAB programming environment to generate customizable DROs. This modular code allows the insertion of a plug-in to describe the kinetic model to be tested. We input our generated DROs into three commercial and open-source analysis packages and assessed the agreement of kinetic model parameter values output with the ‘ground-truth’ values used in the DRO generation. RESULTS: For the five kinetic models tested, the concordance correlation coefficient values were >98%, indicating excellent agreement of the results with ‘ground-truth’. CONCLUSIONS: Testing our DROs on three independent software packages produced concordant results, strongly suggesting our DRO generation code is correct. This implies that our DROs can be used to validate other third party software for the kinetic model analysis of DCE-MRI data. ADVANCES IN KNOWLEDGE: This work extends published work of others to allow customized generation of test objects for any applied kinetic model and allows the incorporation of B(1) mapping into the DRO for application at higher field strengths. The British Institute of Radiology. 2023-07-01 2023-05-25 /pmc/articles/PMC10321261/ /pubmed/37191274 http://dx.doi.org/10.1259/bjr.20220976 Text en © 2023 The Authors. Published by the British Institute of Radiology https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License http://creativecommons.org/licenses/by/4.0/ (https://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 Full Paper
Gill, Andrew B.
Gallagher, Ferdia A.
Graves, Martin J.
Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation
title Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation
title_full Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation
title_fullStr Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation
title_full_unstemmed Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation
title_short Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation
title_sort open source code for the generation of digital reference objects for dynamic contrast-enhanced mri analysis software validation
topic Full Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10321261/
https://www.ncbi.nlm.nih.gov/pubmed/37191274
http://dx.doi.org/10.1259/bjr.20220976
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