The Future of Imaging Biomarkers in Radiologic Practice: Proceedings of the Thirteenth Annual ACR Forum

Krishnaraj, Arun; Weinreb, Jeffrey C.; Ellenbogen, Paul H.; Allen, Bibb; Norbash, Alexander; Kazerooni, Ella A.

doi:10.1016/j.jacr.2013.08.017

Cited by 10 publications

(6 citation statements)

References 3 publications

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“…Recent publications demonstrate that there is an increased recognition of the value of at least exporting images that are the result of research processing applications in DICOM format, so that they can be used to support various activities essential for imaging biomarker development (Krishnaraj et al, 2014). Such activities include consistently "tagging" analysis results to compare analyses done at different centers on different cohorts using different analysis tools (Waterton & Pylkkanen, 2012), supporting archival and distribution of the analysis results in a manner that enables indexing and secondary analysis (Chan et al, 2014) and transfer to and visualization of the analysis results in clinical systems in which metadata for patient identification and study management is required (Clark et al, 2013;Moore et al, 2015).…”

Section: Interoperable Communication Of Analysis Results Between Resementioning

confidence: 99%

Peer Review #2 of "DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research (v0.2)"

2016

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Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We develop the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM®) international standard and free open source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive. Supporting tools for data analysis and DICOM conversion were made available as free open source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

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Section: Interoperable Communication Of Analysis Results Between Resementioning

confidence: 99%

Peer Review #2 of "DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research (v0.2)"

2016

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“…Precision medicine aims to identify subgroups of patients with similar disease characteristics so that the safest and most effective or cost-effective treatment can be selected for individual patients. Expanding the role of imaging to include acquisition of data that allow these subgroups to be identified as part of routine diagnosis constitutes a major opportunity for radiology to contribute significantly to this new era (3). Both PET and MRI offer specific advantages for engaging with this opportunity, and the potential benefits of combining PET and MRI assessments for precision medicine have been highlighted by image-based prognostic nomograms proposed for patients with cervical cancer (4).…”

Section: Functional and Molecular Imaging In The Era Of Precision Canmentioning

confidence: 99%

Additional Clinical Value for PET/MRI in Oncology: Moving Beyond Simple Diagnosis

2018

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Initial clinical research comparing the diagnostic performance of PET/MRI and PET/CT has largely shown equivalent diagnostic capabilities for these modalities in oncology. These uncertainties about the magnitude of diagnostic benefit are compounded by the considerable health economic challenges associated with clinical implementation. Therefore, there is a need to identify ways to extend the use of this technology beyond simple diagnosis so that PET/MRI can add sufficient clinical value beyond PET/CT or MRI alone and become a cost-effective imaging modality in clinical practice. A major advantage of PET/MRI over other imaging modalities is the ability to generate multiple quantitative images from a single examination. This article describes how a multiparametric PET/MRI approach not only can add clinical value through contributing to precision medicine but also can establish PET/MRI as a potentially cost-effective imaging modality in oncology.

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“…It is crucial to address variability in methods before attempting to qualify QI biomarkers for broad clinical use (82). Finally, QI biomarker research output from academic radiology is currently hampered by the lack of training among radiologists in advanced clinical research techniques (83); the academic radiology community is addressing this deficiency through programs such as the AUR GE-Radiology Research Academic Fellowship (GERRAF) program, but additional initiatives would be beneficial.…”

Section: The Role Of Academic Radiology In Qi Biomarker Researchmentioning

confidence: 99%

Methods and Challenges in Quantitative Imaging Biomarker Development

Abramson

Burton

et al. 2015

Academic Radiology

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Academic radiology is poised to play an important role in the development and implementation of quantitative imaging (QI) tools. This manuscript, drafted by the Association of University Radiologists (AUR) Radiology Research Alliance (RRA) Quantitative Imaging Task Force, reviews current issues in QI biomarker research. We discuss motivations for advancing QI, define key terms, present a framework for QI biomarker research, and outline challenges in QI biomarker development. We conclude by describing where QI research and development is currently taking place and discussing the paramount role of academic radiology in this rapidly evolving field.

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The Future of Imaging Biomarkers in Radiologic Practice: Proceedings of the Thirteenth Annual ACR Forum

Cited by 10 publications

References 3 publications

Peer Review #2 of "DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research (v0.2)"

Peer Review #2 of "DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research (v0.2)"

Additional Clinical Value for PET/MRI in Oncology: Moving Beyond Simple Diagnosis

Methods and Challenges in Quantitative Imaging Biomarker Development

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