Abstract
Advances in imaging have enabled the identification of prostate cancer foci with an initial application to focal dose escalation, with subvolumes created with image intensity thresholds. Through quantitative imaging techniques, correlations between image parameters and tumour characteristics have been identified. Mathematical functions are typically used to relate image parameters to prescription dose to improve the clinical relevance of the resulting dose distribution. However, these relationships have remained speculative or invalidated. In contrast, the use of radiobiological models during treatment planning optimisation, termed biological optimisation, has the advantage of directly considering the biological effect of the resulting dose distribution. This has led to an increased interest in the accurate derivation of radiobiological parameters from quantitative imaging to inform the models. This article reviews the progress in treatment planning using image-informed tumour biology, from focal dose escalation to the current trend of individualised biological treatment planning using image-derived radiobiological parameters, with the focus on prostate intensity-modulated radiotherapy (IMRT).
Highlights
It is well-established that prostate cancer (PCa) exhibits high multifocality and heterogeneity [1,2,3]and yet the current standard of care for PCa with external beam radiotherapy (EBRT) still largely remains a prescription of uniform, conformal dose distribution
This article aims to review the progress in treatment planning using image-informed tumour biology, from focal dose escalation to the current trend of individualised biological treatment planning biology, from focal dose escalation to the current trend of individualised biological treatment using voxel-level, image-derived radiobiological parameters to achieve optimal treatment outcomes, planning using voxel-level, image-derived radiobiological parameters to achieve optimal treatment with the focus on prostate intensity-modulated radiotherapy (IMRT)
Schie et al [30] where a tumour probability (TP) map was used in a polynomial dose prescription function
Summary
It is well-established that prostate cancer (PCa) exhibits high multifocality and heterogeneity [1,2,3]. Tumour subvolumes with a potential relative radiation resistance were identified and prescribed an escalation dose (a “boost dose”) This initial definition of dose painting is labeled dose-painting-by-contours (DPbC) where the boost subvolume(s) within the target is created with image parameter threshold(s). DPbN requires demonstration demonstration of of correlation correlation between between imaging imaging features features and and specific specific tumour tumour biology characteristics [5,6,7]. The top row of Figure illustrates how quantitative imaging biological information to improve clinical relevance. Dose-based objectives rarely represent optimal tumour control. Of radiotherapy is to conventional dose-based objectives rarely represent optimal tumour. A the determination of voxel-level parameters, and the bottom row of Figure illustrates how the same mechanistic TCP model requires the determination of voxel-level parameters, and the bottom row of quantitative imaging might used to obtain that information.
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