Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the m...

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Published inJournal of magnetic resonance imaging Vol. 49; no. 7; pp. e101 - e121
Main Authors Shukla‐Dave, Amita, Obuchowski, Nancy A., Chenevert, Thomas L., Jambawalikar, Sachin, Schwartz, Lawrence H., Malyarenko, Dariya, Huang, Wei, Noworolski, Susan M., Young, Robert J., Shiroishi, Mark S., Kim, Harrison, Coolens, Catherine, Laue, Hendrik, Chung, Caroline, Rosen, Mark, Boss, Michael, Jackson, Edward F.
Format Journal Article
LanguageEnglish
Published United States 01.06.2019
Subjects
DCE
DWI
MRI
quantitative imaging biomarkers
MRI
DCE
DWI
quantitative imaging biomarkers
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Abstract Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion‐weighted imaging and dynamic contrast‐enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101–e121.
AbstractList Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.
Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion‐weighted imaging and dynamic contrast‐enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101–e121.
Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.
Physiological properties of tumors can be measured both in vivo and non-invasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIB) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America’s Quantitative Imaging Biomarkers Alliance/(QIBA®). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA’s development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in magnetic resonance imaging technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability.
Author Shiroishi, Mark S.
Obuchowski, Nancy A.
Malyarenko, Dariya
Boss, Michael
Young, Robert J.
Coolens, Catherine
Shukla‐Dave, Amita
Chenevert, Thomas L.
Huang, Wei
Rosen, Mark
Jackson, Edward F.
Schwartz, Lawrence H.
Noworolski, Susan M.
Kim, Harrison
Laue, Hendrik
Chung, Caroline
Jambawalikar, Sachin
AuthorAffiliation 1 Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
11 Department of Fraunhofer MEVIS, Bremen, Germany
5 Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
9 Department of Radiology, University of Alabama at Birmingham, Birmingham AL, USA
6 Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USA
13 Department of Radiology, University of Pennsylvania, Philadelphia, USA
8 Division of Neuroradiology, Department of Radiology, University of Southern California, Los Angeles, CA, USA
10 Department of Radiation Oncology, Princess Margaret Cancer Centre, Toronto, Canada
12 Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas, USA
3 Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH, USA
2 Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
4 Department of Radiology, University of Michigan, Ann Arbor, MI, USA
14 Ap
AuthorAffiliation_xml – name: 5 Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
– name: 15 Departments of Medical Physics, Radiology, and Human Oncology, University of Wisconsin School of Medicine, Madison, WI, USA
– name: 4 Department of Radiology, University of Michigan, Ann Arbor, MI, USA
– name: 11 Department of Fraunhofer MEVIS, Bremen, Germany
– name: 1 Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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– name: 6 Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USA
– name: 3 Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH, USA
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– name: 12 Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas, USA
– name: 2 Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
– name: 7 Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
– name: 9 Department of Radiology, University of Alabama at Birmingham, Birmingham AL, USA
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/30451345$$D View this record in MEDLINE/PubMed
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DWI
quantitative imaging biomarkers
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Snippet Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic...
Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic...
Physiological properties of tumors can be measured both in vivo and non-invasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic...
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SubjectTerms DCE
DWI
MRI
quantitative imaging biomarkers
Title Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fjmri.26518
https://www.ncbi.nlm.nih.gov/pubmed/30451345
https://www.proquest.com/docview/2135635358
https://pubmed.ncbi.nlm.nih.gov/PMC6526078
Volume 49
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