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European Radiology
Published in: European Radiology 10/2019

01-10-2019 | Solid Tumor | Oncology

Image-based biomarkers for solid tumor quantification

Authors: Peter Savadjiev, Jaron Chong, Anthony Dohan, Vincent Agnus, Reza Forghani, Caroline Reinhold, Benoit Gallix

Published in: European Radiology | Issue 10/2019

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Abstract

The last few decades have witnessed tremendous technological developments in image-based biomarkers for tumor quantification and characterization. Initially limited to manual one- and two-dimensional size measurements, image biomarkers have evolved to harness developments not only in image acquisition technology but also in image processing and analysis algorithms. At the same time, clinical validation remains a major challenge for the vast majority of these novel techniques, and there is still a major gap between the latest technological developments and image biomarkers used in everyday clinical practice. Currently, the imaging biomarker field is attracting increasing attention not only because of the tremendous interest in cutting-edge therapeutic developments and personalized medicine but also because of the recent progress in the application of artificial intelligence (AI) algorithms to large-scale datasets. Thus, the goal of the present article is to review the current state of the art for image biomarkers and their use for characterization and predictive quantification of solid tumors. Beginning with an overview of validated imaging biomarkers in current clinical practice, we proceed to a review of AI-based methods for tumor characterization, such as radiomics-based approaches and deep learning.
Key Points
• Recent years have seen tremendous technological developments in image-based biomarkers for tumor quantification and characterization.
• Image-based biomarkers can be used on an ongoing basis, in a non-invasive (or mildly invasive) way, to monitor the development and progression of the disease or its response to therapy.
• We review the current state of the art for image biomarkers, as well as the recent developments in artificial intelligence (AI) algorithms for image processing and analysis.
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Metadata
Title
Image-based biomarkers for solid tumor quantification
Authors
Peter Savadjiev
Jaron Chong
Anthony Dohan
Vincent Agnus
Reza Forghani
Caroline Reinhold
Benoit Gallix
Publication date
01-10-2019
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 10/2019
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-019-06169-w

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