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Critical Reviews™ in Oncogenesis
SJR: 0.631 SNIP: 0.503 CiteScore™: 2.2

ISSN Imprimer: 0893-9675
ISSN En ligne: 2162-6448

Critical Reviews™ in Oncogenesis

DOI: 10.1615/CritRevOncog.2018025830
pages 93-112

Secondary Malignancies in the Era of High-Precision Radiation Therapy

Elizabeth K. Balcer-Kubiczek
Department of Radiation Oncology, Translational Radiation Sciences Division, Marlene and Stewart Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore MD 21201, U.S.A
John G. Eley
Maryland Proton Treatment Center, Department of Radiation Oncology, Division of Translational Radiation Sciences, University of Maryland School of Medicine, Baltimore, Maryland

RÉSUMÉ

Although modern radiation therapy delivers a localized distribution of ionizing energy that can be used to cure primary cancers for many patients, the inevitable radiation exposure to non-targeted normal tissue leads to a risk of a radiation-related new cancer. Modern therapies often produce a complex spectrum of secondary particles, both charged and uncharged, that must be considered both in their physical radiation transport throughout the patient and their potential to induce biological damage, which depends on the microscopic energy deposition from the cascade of primary, secondary, and downstream particles. This work summarizes the experimental data for relative biological effectiveness for particles associated with modern radiotherapy in light of their capacity to induce secondary malignancies in patients. A distinction is highlighted between the radiobiological experimental data and the coarser metrics used frequently in radiation protection. For critical assessment of the risks of secondary malignancies for patients undergoing radiation therapy, a detailed description of primary and secondary radiation fields is needed, though not routinely considered for individual patient treatments. Furthermore, not only the particle type, but also the microscopic dose and track structure, must be considered, which points to a demand for detailed physics models and high-performance computing strategies to model the risks.


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