Alpha/beta (<i>α/β</i>) ratio for prostate cancer derived from external beam radiotherapy and brachytherapy boost

Boonstra, Philip S.; Taylor, Jeremy M. G.; Smolska-Ciszewska, Beata; Behrendt, K.; Dworzecki, Tomasz; Gawkowska-Suwińska, Marzena; Białas, Brygida; Suwiński, Rafał

doi:10.1259/bjr.20150957

Cited by 12 publications

(5 citation statements)

References 26 publications

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“…However, the in vitro cell lines often have higher α/β ratios, closer to 20 (see Figs. 1 and 2) [30, 31, 34]. The relative effect of the development of radiation resistance during treatment is not strongly dependent on the initial radiosensitivity parameters.…”

Section: Resultsmentioning

confidence: 99%

Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy

Alfonso

Berk

2019

Radiat Oncol

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Background Standard radiobiology theory of radiation response assumes a uniform innate radiosensitivity of tumors. However, experimental data show that there is significant intratumoral heterogeneity of radiosensitivity. Therefore, a model with heterogeneity was developed and tested using existing experimental data to show the potential effects from the presence of an intratumoral distribution of radiosensitivity on radiation therapy response over a protracted radiation therapy treatment course. Methods The standard radiation response curve was modified to account for a distribution of radiosensitivity, and for variations in the repopulation rates of the tumor cell subpopulations. Experimental data from the literature were incorporated to determine the boundaries of the model. The proposed model was then used to show the changes in radiosensitivity of the tumor during treatment, and the effects of fraction size, α/β ratio and variation of the repopulation rates of tumor cells. Results In the presence of an intratumoral distribution of radiosensitivity, there is rapid selection of radiation-resistant cells over a course of fractionated radiation therapy. Standard treatment fractionation regimes result in the near-complete replacement of the initial population of sensitive cells with a population of more resistant cells. Further, as treatment progresses, the tumor becomes more resistant to further radiation treatment, making each fractional dose less efficacious. A wider initial distribution induces increased radiation resistance. Hypofractionation is more efficient in a heterogeneous tumor, with increased cell kill for biologically equivalent doses, while inducing less resistance. The model also shows that a higher growth rate in resistant cells can account for the accelerated repopulation that is seen during the clinical treatment of patients. Conclusions Modeling of tumor cell survival with radiosensitivity heterogeneity alters the predicted tumor response, and explains the induction of radiation resistance by radiation treatment, the development of accelerated repopulation, and the potential beneficial effects of hypofractionation. Tumor response to treatment may be better predicted by assaying for the distribution of radiosensitivity, or the extreme of the radiosensitivity, rather than measuring the initial, general radiation sensitivity of the untreated tumor.

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Section: Resultsmentioning

confidence: 99%

Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy

Alfonso

Berk

2019

Radiat Oncol

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“…The reason may be that when applying the extreme hypofractionation schedule and a relatively low

\alpha /\beta

ratio, the TCP level of the uniform dose distribution was already relatively high. In order to maintain the calculated TCPs at realistic levels, a larger

\alpha /\beta

ratio is indicated, as suggested by multiple previous studies 39,52–57 . Note that the implemented model in the present work did not include hypoxic sub‐volumes, and hypoxia was associated with tumor radioresistance and could lead to poor prognosis 66–68 .…”

Section: Discussionmentioning

confidence: 96%

“…In order to maintain the calculated TCPs at realistic levels, a larger 𝛼∕𝛽 ratio is indicated, as suggested by multiple previous studies. 39,[52][53][54][55][56][57] Note that the implemented model in the present work did not include hypoxic sub-volumes, and hypoxia was associated with tumor radioresistance and could lead to poor prognosis. [66][67][68] In the future studies, oxygen enhancement ratio (OER) will be incorporated in the TCP model [69][70][71][72] to better guide the dose redistribution for IPLs.…”

Section: Optimal Dose Prescription Generationmentioning

confidence: 99%

Patient‐specific voxel‐level dose prescription for prostate cancer radiotherapy considering tumor cell density and grade distribution

et al. 2023

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Background: In prostate radiation therapy, recent studies have indicated a benefit in increasing the dose to intraprostatic lesions (IPL) compared with standard whole gland radiation therapy. Such approaches typically aim to deliver a target dose to the IPL(s) with no deliberate effort to modulate the dose within the IPL. Prostate cancers demonstrate intra-tumor heterogeneity and hence it is hypothesized that further gains in the optimal delivery of radiation therapy can be achieved through modulation of the dose distribution within the tumor. To account for tumor heterogeneity, biologically targeted radiation therapy (BiRT) aims to utilize a voxel-wise approach to IPL dose prescription by incorporating knowledge of the spatial distribution of tumor characteristics. Purpose:The aim of this study was to develop a workflow for generating voxelwise optimal dose prescriptions that maximize patient tumor control probability (TCP), and evaluate the feasibility and benefits of applying this workflow on a cohort of 62 prostate cancer patients. Method: The source data for this proof -of -concept study included high resolution histology images annotated with tumor location and grade. Image processing techniques were used to compute voxel-level cell density distribution maps. An absolute tumor cell distribution was calculated via linearly scaling according to published estimated tumor cell numbers. For the IPLs of each patient, optimal dose prescriptions were obtained via three alternative methods for redistribution of IPL boost doses according to maximization of TCP. The radiosensitivity uncertainties were considered using a truncated log-normally distributed linear radiosensitivity parameter (𝛼 k ) and compared with Gleason pattern (GP) dependent radiosensitivity parameters that were derived based on previously published methods. An ensemble machine learning method was implemented to identify patient-specific features that predict the TCP improvement resulting from dose redistribution relative to a uniform dose distribution. Results:The Gleason pattern-dependent radiosensitivity parameters were calculated for 20 published prostate cancer 𝛼∕𝛽 ratios. Optimal voxel-level dose prescriptions were generated for all 62 PCa patients. For all dose redistribution scenarios, the optimal dose distribution always shows a higher (or equivalent) TCP level than the uniform dose distribution. The applied random forest regressor could predict patient-specific TCP improvement with low root mean square error (≤1.5%) by using total tumor number, volume of IPLs and the standard deviation of tumor cell number among all voxels.

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“…These efforts have led to changes in the standard of care in radiotherapy treatments for prostate and breast cancer [71,72]. However, the design of these trials was based on LQ-model estimations of conventional fractionation equivalence, and, hence, were limited given our current understanding and quantifiable estimation of the required biological parameters [73][74][75]. Despite encouraging results at the patient population level for a subset of these trials, it needs to be stressed that intratumor heterogeneity and the above discussed implications on temporal variation of competing tumor populations were not accounted for in these FED hyper-and hypofractionation settings.…”

Section: Current Clinical Data Utilizing Altered Fractionationmentioning

confidence: 99%

A Century of Fractionated Radiotherapy: How Mathematical Oncology Can Break the Rules

Ghaderi

Jung

Brüningk

et al. 2022

IJMS

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Radiotherapy is involved in 50% of all cancer treatments and 40% of cancer cures. Most of these treatments are delivered in fractions of equal doses of radiation (Fractional Equivalent Dosing (FED)) in days to weeks. This treatment paradigm has remained unchanged in the past century and does not account for the development of radioresistance during treatment. Even if under-optimized, deviating from a century of successful therapy delivered in FED can be difficult. One way of exploring the infinite space of fraction size and scheduling to identify optimal fractionation schedules is through mathematical oncology simulations that allow for in silico evaluation. This review article explores the evidence that current fractionation promotes the development of radioresistance, summarizes mathematical solutions to account for radioresistance, both in the curative and non-curative setting, and reviews current clinical data investigating non-FED fractionated radiotherapy.

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Alpha/beta (α/β) ratio for prostate cancer derived from external beam radiotherapy and brachytherapy boost

Abstract: Although dose inhomogeneities and other limitations may limit the scope of our findings, the data suggest caution regarding the assumptions of the α/β ratio for prostate cancer in some clinical environments.

Cited by 12 publications

References 26 publications

Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy

Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy

Patient‐specific voxel‐level dose prescription for prostate cancer radiotherapy considering tumor cell density and grade distribution

A Century of Fractionated Radiotherapy: How Mathematical Oncology Can Break the Rules

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