Progress towards Patient-Specific, Spatially-Continuous Radiobiological Dose Prescription and Planning in Prostate Cancer IMRT: An Overview

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).

Impact of neoadjuvant androgen deprivation therapy on magnetic resonance imaging features in prostate cancer before radiotherapy

“…This challenges the use of MRI, after neoadjuvant hormonal therapy, for RT target delineation. There is a growing interest in the use of advanced imaging for dose prescription and planning [14] . For MRI, image texture analysis has been suggested as a supporting tool to separate tumour from normal tissue [15] , even in cases with low contrast between tumour and surrounding tissue [13] .…”

Biologically Targeted Radiation Therapy: Incorporating Patient-Specific Hypoxia Data Derived from Quantitative Magnetic Resonance Imaging

“…As a relatively high cumulative acute grade 2 genitourinary toxicity of 34% at 90 days post-treatment was reported for the hypo-FLAME [ 4 ], further dose escalation to the entire tumour volume using standard treatment planning methods may not be possible. To assess the tissue-sparing effect of the hypoxia-targeting BiRT approach [ 6 ], a hypoxia DE protocol (Method 3) was devised under the assumption that the same hypoxia information was available. To the authors’ knowledge, there is no published data on the level of DE required to combat hypoxia in ultra-hypofractionated treatment of PCa.…”

“…In addition to hypoxia modelling, the TCP model used in this study has further limitations in describing tumour radiation response. In this study we have chosen to use our previously validated TCP model [ 36 ], a model that we have used in a number of subsequent biologically targeted radiotherapy studies [ 6 , 35 , 54 ]. As in our previous studies, cell-to-cell communication, intrafraction repair and accelerated repopulation were excluded.…”

“…Rotational uncertainties were not considered, and shift-invariance of the dose distribution was assumed. Equations [ 1 ], [ 2 ] and [ 5 ] were modified to form Equations [ 6 ] and [ 7 ].…”

“…Biologically targeted RT has, up until recent times, not been widely practised due to the inability to spatially map tumour characteristics. Quantitative imaging, however, has demonstrated an ability to define pathological and physiological features of tissue at the voxel-level and hence the potential to provide patient-level input parameters for a biological approach to treatment planning [ 6 ]. In the review article of Sun et al for example, it was demonstrated that machine learning methods can be used to define spatial maps of tumour cell density and regions of high and low grade disease [ 7 ].…”