Abstract
Several challenges exist for the adoption of advanced image analysis methods in clinical routine. Imaging biomarkers not only have to be objective and reproducible, but they also have to show a clear efficacy in the detection and diagnosis of the disease and/or in the evaluation of treatment response. This efficacy must be confirmed by a close relationship with disease hallmarks, which allows them to act as surrogate indicators of relevant clinical outcomes such as the time to treatment response, the progression-free survival, the overall survival, and others. Finally, to achieve clinical integration and to expand its utility, the methodology must be cost-efficient. In this chapter, the general methodology for the development, validation, and implementation of imaging biomarkers is presented. The approach consists of a systematic methodology that allows to achieve a high precision and accuracy in the usage of imaging biomarkers, making it feasible to integrate them in automated pipelines for the generation of massive amounts of radiomic data to be used for storage in imaging biobanks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
MartĂ BonmatĂ L, Alberich-Bayarri A, GarcĂa-MartĂ G, Sanz Requena R, PĂ©rez Castillo C, Carot Sierra JM, ManjĂłn Herrera JV. Imaging biomarkers, quantitative imaging, and bioengineering. Radiologia. 2012;54:269–78.
European Society of Radiology (ESR). ESR statement on the stepwise development of imaging biomarkers. Insights Imaging. 2013;4:147–52.
MartĂ-BonmatĂ L. Introduction to the stepwise development of imaging biomarkers. In: MartĂ-BonmatĂ L, Alberich-Bayarri A, editors. Imaging biomarkers. Development and clinical integration, vol. 2; 2017. p. 27. isbn:9783319435046.
European Medicines Agency. Guidelines on bioanalytical methods validation. 21 July 2011. EMEA/CHMP/EWP/192217/2009 Rev. 1 Corr. 2.
O’Connor JP, Aboagye EO, Adams JE, et al. Consensus statement. imaging biomarkers roadmap for cancer studies. Nat Rev Clin Oncol. 2017;14(3):169–86. https://doi.org/10.1038/nrclinonc.2016.162.
European Society of Radiology (ESR). ESR position paper on imaging biobanks. Insights Imaging. 2015;6:403–10.
Alberich-Bayarri A, Hernández-Navarro R, Ruiz-MartĂnez E, GarcĂa-Castro F, GarcĂa-Juan D, MartĂ-BonmatĂ L. Development of imaging biomarkers and generation of big data. Radiol Med. 2017;122:444–8.
Neri E, Regge D. Imaging biobanks in oncology: European perspective. Future Oncol. 2017;13:433–41.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Alberich-Bayarri, A., Neri, E., MartĂ-BonmatĂ, L. (2019). Imaging Biomarkers and Imaging Biobanks. In: Ranschaert, E., Morozov, S., Algra, P. (eds) Artificial Intelligence in Medical Imaging. Springer, Cham. https://doi.org/10.1007/978-3-319-94878-2_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-94878-2_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94877-5
Online ISBN: 978-3-319-94878-2
eBook Packages: MedicineMedicine (R0)