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A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology

There is a need to develop user-friendly imaging tools estimating robust quantitative biomarkers (QIBs) from multiparametric (mp)MRI for clinical applications in oncology. Quantitative metrics derived from (mp)MRI can monitor and predict early responses to treatment, often prior to anatomical change...

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Autores principales: LoCastro, Eve, Paudyal, Ramesh, Konar, Amaresha Shridhar, LaViolette, Peter S., Akin, Oguz, Hatzoglou, Vaios, Goh, Alvin C., Bochner, Bernard H., Rosenberg, Jonathan, Wong, Richard J., Lee, Nancy Y., Schwartz, Lawrence H., Shukla-Dave, Amita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10661267/
https://www.ncbi.nlm.nih.gov/pubmed/37987347
http://dx.doi.org/10.3390/tomography9060161
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author LoCastro, Eve
Paudyal, Ramesh
Konar, Amaresha Shridhar
LaViolette, Peter S.
Akin, Oguz
Hatzoglou, Vaios
Goh, Alvin C.
Bochner, Bernard H.
Rosenberg, Jonathan
Wong, Richard J.
Lee, Nancy Y.
Schwartz, Lawrence H.
Shukla-Dave, Amita
author_facet LoCastro, Eve
Paudyal, Ramesh
Konar, Amaresha Shridhar
LaViolette, Peter S.
Akin, Oguz
Hatzoglou, Vaios
Goh, Alvin C.
Bochner, Bernard H.
Rosenberg, Jonathan
Wong, Richard J.
Lee, Nancy Y.
Schwartz, Lawrence H.
Shukla-Dave, Amita
author_sort LoCastro, Eve
collection PubMed
description There is a need to develop user-friendly imaging tools estimating robust quantitative biomarkers (QIBs) from multiparametric (mp)MRI for clinical applications in oncology. Quantitative metrics derived from (mp)MRI can monitor and predict early responses to treatment, often prior to anatomical changes. We have developed a vendor-agnostic, flexible, and user-friendly MATLAB-based toolkit, MRI-Quantitative Analysis and Multiparametric Evaluation Routines (“MRI-QAMPER”, current release v3.0), for the estimation of quantitative metrics from dynamic contrast-enhanced (DCE) and multi-b value diffusion-weighted (DW) MR and MR relaxometry. MRI-QAMPER’s functionality includes generating numerical parametric maps from these methods reflecting tumor permeability, cellularity, and tissue morphology. MRI-QAMPER routines were validated using digital reference objects (DROs) for DCE and DW MRI, serving as initial approval stages in the National Cancer Institute Quantitative Imaging Network (NCI/QIN) software benchmark. MRI-QAMPER has participated in DCE and DW MRI Collaborative Challenge Projects (CCPs), which are key technical stages in the NCI/QIN benchmark. In a DCE CCP, QAMPER presented the best repeatability coefficient (RC = 0.56) across test–retest brain metastasis data, out of ten participating DCE software packages. In a DW CCP, QAMPER ranked among the top five (out of fourteen) tools with the highest area under the curve (AUC) for prostate cancer detection. This platform can seamlessly process mpMRI data from brain, head and neck, thyroid, prostate, pancreas, and bladder cancer. MRI-QAMPER prospectively analyzes dose de-escalation trial data for oropharyngeal cancer, which has earned it advanced NCI/QIN approval for expanded usage and applications in wider clinical trials.
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spelling pubmed-106612672023-11-03 A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology LoCastro, Eve Paudyal, Ramesh Konar, Amaresha Shridhar LaViolette, Peter S. Akin, Oguz Hatzoglou, Vaios Goh, Alvin C. Bochner, Bernard H. Rosenberg, Jonathan Wong, Richard J. Lee, Nancy Y. Schwartz, Lawrence H. Shukla-Dave, Amita Tomography Article There is a need to develop user-friendly imaging tools estimating robust quantitative biomarkers (QIBs) from multiparametric (mp)MRI for clinical applications in oncology. Quantitative metrics derived from (mp)MRI can monitor and predict early responses to treatment, often prior to anatomical changes. We have developed a vendor-agnostic, flexible, and user-friendly MATLAB-based toolkit, MRI-Quantitative Analysis and Multiparametric Evaluation Routines (“MRI-QAMPER”, current release v3.0), for the estimation of quantitative metrics from dynamic contrast-enhanced (DCE) and multi-b value diffusion-weighted (DW) MR and MR relaxometry. MRI-QAMPER’s functionality includes generating numerical parametric maps from these methods reflecting tumor permeability, cellularity, and tissue morphology. MRI-QAMPER routines were validated using digital reference objects (DROs) for DCE and DW MRI, serving as initial approval stages in the National Cancer Institute Quantitative Imaging Network (NCI/QIN) software benchmark. MRI-QAMPER has participated in DCE and DW MRI Collaborative Challenge Projects (CCPs), which are key technical stages in the NCI/QIN benchmark. In a DCE CCP, QAMPER presented the best repeatability coefficient (RC = 0.56) across test–retest brain metastasis data, out of ten participating DCE software packages. In a DW CCP, QAMPER ranked among the top five (out of fourteen) tools with the highest area under the curve (AUC) for prostate cancer detection. This platform can seamlessly process mpMRI data from brain, head and neck, thyroid, prostate, pancreas, and bladder cancer. MRI-QAMPER prospectively analyzes dose de-escalation trial data for oropharyngeal cancer, which has earned it advanced NCI/QIN approval for expanded usage and applications in wider clinical trials. MDPI 2023-11-03 /pmc/articles/PMC10661267/ /pubmed/37987347 http://dx.doi.org/10.3390/tomography9060161 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
LoCastro, Eve
Paudyal, Ramesh
Konar, Amaresha Shridhar
LaViolette, Peter S.
Akin, Oguz
Hatzoglou, Vaios
Goh, Alvin C.
Bochner, Bernard H.
Rosenberg, Jonathan
Wong, Richard J.
Lee, Nancy Y.
Schwartz, Lawrence H.
Shukla-Dave, Amita
A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology
title A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology
title_full A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology
title_fullStr A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology
title_full_unstemmed A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology
title_short A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology
title_sort quantitative multiparametric mri analysis platform for estimation of robust imaging biomarkers in clinical oncology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10661267/
https://www.ncbi.nlm.nih.gov/pubmed/37987347
http://dx.doi.org/10.3390/tomography9060161
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