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. 2018 Mar 1;59(suppl_1):i2-i10.
doi: 10.1093/jrr/rrx092.

Selection of external beam radiotherapy approaches for precise and accurate cancer treatment

Hiroki Shirato  1   2 , Quynh-Thu Le  2   3 , Keiji Kobashi  4 , Anussara Prayongrat  1 , Seishin Takao  2   4 , Shinichi Shimizu  1   2 , Amato Giaccia  2   3 , Lei Xing  2   3 , Kikuo Umegaki  2   4
Affiliations

Selection of external beam radiotherapy approaches for precise and accurate cancer treatment

Hiroki Shirato et al. J Radiat Res. .

Abstract

Physically precise external-beam radiotherapy (EBRT) technologies may not translate to the best outcome in individual patients. On the other hand, clinical considerations alone are often insufficient to guide the selection of a specific EBRT approach in patients. We examine the ways in which to compare different EBRT approaches based on physical, biological and clinical considerations, and how they can be enhanced with the addition of biophysical models and machine-learning strategies. The process of selecting an EBRT modality is expected to improve in tandem with knowledge-based treatment planning.

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Figures

Fig. 1.
Fig. 1.
Illustration of evaluating three different EBRT in eight different aspects.
Fig. 2.
Fig. 2.
Baseline shifts during the treatment of lung cancers at the lower lung field. The incidence of the baseline shifts of 3 mm or more is shown according to the position of the lung cancer and the direction of the motion along the left–right (LR), antero–posterior (AP), and cranio–caudal (CC) axes. The figure on the left shows the accumulated incidence of the baseline shifts of the tumors in the lower left and right lung fields, respectively. The figure on the right shows the accumulated incidence of the baseline shifts of the tumors in the lower anterior lung field and the lower posterior lung field, respectively.
Fig. 3.
Fig. 3.
Concept of the statistical comparison between photon and particle beam therapy using differences in the NTCP based on the mean dose of an organ [with confidence intervals (CIs)].
Fig. 4.
Fig. 4.
Big data and machine learning systems in relation to EBRT selection.
See this image and copyright information in PMC

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