Radiobiology of High Dose Fractions

Jones, Bleddyn; Dale, Roger G.

doi:10.1007/978-0-85729-597-2_5

Cited by 2 publications

(2 citation statements)

References 50 publications

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“…An alternative BED method assumes that the transition from curvature to linearity is abrupt, rather than gradual, occurring at a specific fractional dose (c) followed by a constant slope at higher doses. 48 At low fraction doses (<c): E = αd + βd 2 to a limit of E=αc+βc 2 . At a dose of c, the gradient is α +2βc, given by the first differential coefficient of the latter equation, so that for doses which exceed c (i.e.…”

Section: Methodsmentioning

confidence: 99%

The evolution of practical radiobiological modelling

Jones

Dale

2018

BJR

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A summary of the key aspects of radiobiological modelling is provided, based on the theoretical and practical concepts of the linear quadratic (LQ) model, which gradually replaced other numerical approaches. The closely related biological effective dose (BED) concept is useful in many clinical applications. BED formulations in conventional photon-based radiotherapy continue to be developed, and can be extended to the now increasingly used proton and ion-beam therapy, to very low or high dose ranges, the dose rate effect, hypoxia and repopulation. Such established and new research developments will be of interest to clinicians, physicists and biologists to better understand the processes underlying radiotherapy and assist their collaborative efforts to make radiotherapy safer and more effective.

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Section: Methodsmentioning

confidence: 99%

The evolution of practical radiobiological modelling

Jones

Dale

2018

BJR

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“…Questions have, however, arisen to the relevance of the LQ model for more modern treatment regimens, such as SBRT or charged particle therapy. It has been shown that the LQ model begins to deviate significantly from experimental data beginning at or around 6–8 GyE ( 22 , 90 , 91 ). Practically speaking, this does not affect conventional treatment regimens utilizing 2–3 Gy fraction sizes; however, the LQ model may predict effects of hypofractionation regimes poorly.…”

Section: Modeling Techniquesmentioning

confidence: 99%

Big Data Analytics for Prostate Radiotherapy

2016

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Radiation therapy is a first-line treatment option for localized prostate cancer and radiation-induced normal tissue damage are often the main limiting factor for modern radiotherapy regimens. Conversely, under-dosing of target volumes in an attempt to spare adjacent healthy tissues limits the likelihood of achieving local, long-term control. Thus, the ability to generate personalized data-driven risk profiles for radiotherapy outcomes would provide valuable prognostic information to help guide both clinicians and patients alike. Big data applied to radiation oncology promises to deliver better understanding of outcomes by harvesting and integrating heterogeneous data types, including patient-specific clinical parameters, treatment-related dose–volume metrics, and biological risk factors. When taken together, such variables make up the basis for a multi-dimensional space (the “RadoncSpace”) in which the presented modeling techniques search in order to identify significant predictors. Herein, we review outcome modeling and big data-mining techniques for both tumor control and radiotherapy-induced normal tissue effects. We apply many of the presented modeling approaches onto a cohort of hypofractionated prostate cancer patients taking into account different data types and a large heterogeneous mix of physical and biological parameters. Cross-validation techniques are also reviewed for the refinement of the proposed framework architecture and checking individual model performance. We conclude by considering advanced modeling techniques that borrow concepts from big data analytics, such as machine learning and artificial intelligence, before discussing the potential future impact of systems radiobiology approaches.

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Radiobiology of High Dose Fractions

Cited by 2 publications

References 50 publications

The evolution of practical radiobiological modelling

The evolution of practical radiobiological modelling

Big Data Analytics for Prostate Radiotherapy

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