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Artificial Intelligence in radiotherapy: state of the art and future directions

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Abstract

Recent advances in computing capability allowed the development of sophisticated predictive models to assess complex relationships within observational data, described as Artificial Intelligence. Medicine is one of the several fields of application and Radiation oncology could benefit from these approaches, particularly in patients’ medical records, imaging, baseline pathology, planning or instrumental data. Artificial Intelligence systems could simplify many steps of the complex workflow of radiotherapy such as segmentation, planning or delivery. However, Artificial Intelligence could be considered as a “black box” in which human operator may only understand input and output predictions and its application to the clinical practice remains a challenge. The low transparency of the overall system is questionable from manifold points of view (ethical included). Given the complexity of this issue, we collected the basic definitions to help the clinician to understand current literature, and overviewed experiences regarding implementation of AI within radiotherapy clinical workflow, aiming to describe this field from the clinician perspective.

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Authors and Affiliations

  1. Radiotherapy Department, University of Florence, Florence, Italy

    Giulio Francolini, Isacco Desideri, Giulia Stocchi, Viola Salvestrini, Lucia Pia Ciccone, Pietro Garlatti, Mauro Loi & Lorenzo Livi

  2. Radiation Oncology Unit, Oncology Department, Azienda Ospedaliero - Universitaria Careggi, University of Florence, Largo G. A. Brambilla 3, 50134, Florence, Italy

    Isacco Desideri

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  1. Giulio Francolini
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  2. Isacco Desideri
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  3. Giulia Stocchi
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Correspondence to Isacco Desideri.

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Francolini, G., Desideri, I., Stocchi, G. et al. Artificial Intelligence in radiotherapy: state of the art and future directions. Med Oncol 37, 50 (2020). https://doi.org/10.1007/s12032-020-01374-w

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