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Image-Based Computer-Assisted Radiation Therapy pp 357–375Cite as

Computerized Prediction of Treatment Outcomes and Radiomics Analysis

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Abstract

Imaging has been traditionally used in radiotherapy for the purposes of tumor delineation and treatment planning. Recent evidence suggests that such imaging information could be also used as biomarkers for predicting response and personalized treatment as part of an emerging field called “radiomics.” In this chapter, we discuss the application of imaging-based approaches to predict radiotherapy outcomes from single and hybrid imaging modalities. We describe the different steps involved in radiomics analysis and present examples from our own experiences. We highlight the current challenges and future potentials for image-based decision support in radiotherapy.

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Acknowledgments

Part of this work was supported by the Canadian Institutes of Health Research (CIHR) under grant MOP-136774 and by the Stuart and Barbara Padnos Research Fund (grant#G017459, University of Michigan Cancer Center). The author would like also to thank Dr. Carolyn Freeman, Mrs. Monica Serban, Mrs. Krishinima Jeyaseelan, Dr. Ives Levesque and Mr. Martin Carrier-Vallières, and Dr. Jan Seuntjens from McGill University for their collaboration on the Sarcoma Project.

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  1. Department of Radiation Oncology, Physics Division, University of Michigan, Ann Arbor, MI, 48103, USA

    Issam El Naqa PhD, DABR

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  1. Issam El Naqa PhD, DABR
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Correspondence to Issam El Naqa PhD, DABR .

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  1. Department of Health Sciences, Kyushu University, Fukuoka, Japan

    Hidetaka Arimura

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El Naqa, I. (2017). Computerized Prediction of Treatment Outcomes and Radiomics Analysis. In: Arimura, H. (eds) Image-Based Computer-Assisted Radiation Therapy. Springer, Singapore. https://doi.org/10.1007/978-981-10-2945-5_14

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