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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5518_Библиотеки_им_академика_М_И_Перельмана.pdf
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- •Acknowledgements
- •Author biographies
- •Bleddyn Jones
- •Joshua Moore
- •1.1.1 Straggling and fragmentation
- •1.1.2 Separation of charged particles with increasing tissue depth
- •1.1.3 Particle accelerators
- •1.2.1 Relative biological effect
- •1.2.2 Choice of the control (or reference) radiation source
- •1.1.4 Proton range uncertainties
- •1.2 Physics interacting with biology
- •References
- •2.1 Introduction
- •2.2 Background and models
- •2.2.1 The linear quadratic model
- •2.2.2 Model variants
- •2.2.3 Biological effective dose
- •2.2.4 Repopulation allowances
- •2.2.5 Biological effective dose and repopulation
- •2.2.6 BED expression of high-LET radiation
- •2.2.8 Closely spaced fractions
- •2.2.9 Hypoxia
- •2.2.10 Very low doses
- •2.2.11 Higher doses per fraction
- •2.3 The α/β ratio and its choice for modelling particle therapies
- •2.3.1 The α/β ratio
- •2.3.2 Applications of BED equations
- •2.3.3 Special considerations for particle therapy
- •References
- •3.1 Introduction
- •3.2 Surgery
- •3.3 Cytotoxic chemotherapies
- •3.4 Age and other medical conditions
- •3.5 Reductions in prescribed dose
- •3.6 Interpretation of the case histories and literature
- •3.7 Clinical trials
- •3.8 Ethical issues
- •3.9 Mixed end points
- •3.10 The importance of follow-up
- •3.11 Publication bias
- •References
- •4.1 Introduction
- •4.1.1 Treatment-planning processes
- •4.1.2 The important interaction of RBE issues with the marginal target volumes
- •4.1.3 Comparative planning studies
- •4.1.4 Trade-off situations in comparative treatment planning
- •4.1.5 How to accommodate assumed errors in RBE
- •4.1.6 The product of LET and dose
- •References
- •5.1 Introduction
- •5.2 A brief synopsis
- •5.3 Neutron therapy
- •5.4 More recent developments based on neutron studies
- •5.5 Estimation of neutron RBE from neutron energy
- •5.6 Some important conclusions
- •Appendix A
- •Appendix B
- •References
- •6.1 Introduction and background radiobiology
- •6.2 A brief history of fractionation
- •6.2.1 Radiobiology
- •6.2.2 A synopsis of clinical fractionation
- •6.3 Modelling of fractionation
- •6.3.1 LQ modelling of fractionation in high-LET radiations with inclusion of RBE
- •6.3.2 BED equations
- •6.3.4 Overall fractionation differences between low- and high-LET radiations
- •6.3.5 Boost doses
- •6.3.8 Differences in exposure times
- •6.3.9 RBE and dose per fraction: clinical implications
- •6.3.11 Taking RBE uncertainty into account in fractionation
- •6.4 The use of the linear quadratic model with large fraction sizes
- •6.5 Optimisation of fractionation using calculus methods
- •6.6 Other contributions to fractionation
- •6.7 Summary
- •References
- •7.1 Introduction
- •7.1.1 Arguments to preserve the status quo or avoid using RBE
- •7.2 Discussion
- •8.1 Introduction
- •8.2 The available experimental data and its important limitations
- •8.3 Description of the Z-specific model
- •8.3.2 Changes in the radiosensitivities with LET
- •8.3.3 Obtaining αH and βH values
- •8.4 The graphical results
- •8.4.1 Radiosensitivity data
- •8.4.2 Fits to experimental RBE data sets
- •8.4.3 Applications of the model to clinical radiobiology
- •8.6 Conclusions and what remains to be done
- •References
- •9.1 Introduction
- •9.2 RBE uncertainties
- •9.3 Description of the quantitative model
- •9.4 RBE graphical examples
- •9.6 Two clinical examples where PBT could be sub-optimal
- •9.6.1 Prostate cancer
- •9.6.2 Paediatric cancers and other radiosensitive tumours such as lymphomas
- •9.7 Prediction of tumour response from the RBE increment
- •9.8 Intensification of dose rates
- •9.9 Concluding discussion
- •10.1 Introduction
- •10.2 Methods
- •10.3 Results
- •10.3.1 Remission duration considerations
- •10.4 Discussion
- •References
- •10.5 Conclusions
- •11.1 Introduction
- •11.2 Methods
- •11.2.1 Linear quadratic model base equations
- •11.2.2 The modelling method
- •11.3 Results
- •11.4 Discussion
- •11.5 Conclusions
- •References
- •12.1 Introduction
- •12.2 Unintended treatment interruptions
- •12.2.1 Background
- •12.2.2 Treatment delays
- •12.2.3 Calculations for compensation of treatment interruptions
- •12.2.4 Calculations using a variable RBE value
- •12.2.5 Comparison of the two methods
- •12.2.6 Summary for unintended treatment gap corrections
- •12.3 Re-treatments
- •12.3.1 Background
- •References
- •13.1 Introduction
- •13.1.2 Background considerations
- •13.1.3 Brief description of methods
- •13.2 Model description
- •13.2.1 Biological effective dose equations
- •13.2.2 Assessment of BED changes after an error
- •13.2.3 Worked examples of errors and their correction
- •13.2.4 The potential impact of erroneous fractions on tumour control
- •13.3 Conclusions
- •References
- •14.1 Introduction
- •14.2 Dose escalation where circumstances permit
- •14.3 Simultaneous ‘sensitisation’ effects by new therapies
- •14.4 Sensitivity analysis of the energy-efficiency model
- •14.5.1 Simulated experiments
- •14.5.3 Priority in radiobiological experiments
- •14.6 Some untested situations
- •14.7 Conclusions
- •References

Quantitative Radiobiology for Proton Therapy
seen that the transition to progressively higher LET (represented here by the
RBE
and RBE
max
values) does influence the BED* curves, where at high doses
min
some reduction in tissue effects occur if the same dose is given. For protons the
change is relatively marginal, although dependent on the extent of increase in LET
and RBE.
The modelled examples in figures 14.5 and 14.6 do not need to include the
reduction in LET
due to the increased dose rate (a speculation introduced in
U
chapter 9), since the existing RBE parameters are now further modified by the
change in α/β ratio, which will implicitly include such an effect as well as the
radiosensitivity changes caused by very rapid oxygen depletion, which is sufficient
to oppose oxygen rediffusion into pre-existing hypoxic sites. The presence of
hypoxic areas in normal tissues may be surprising to non-radiobiologists, but
normal tissue perfusion is phasic and tissue-invasive oxygen electrode studies,
from the earliest times, have confirmed periodic hypoxia in many normal tissues,
as well as more recent perfusion studies using dynamic magnetic resonance
imaging (see Jones 2022). The effects on tumour sterilisation can be difficult to
interpret. Modelling studies using BED equations where the dose rate ranges from
very low dose rates of 0.1 Gy hr
−1
to FLASH rates, by further adaption of the
equations presented above, suggest that the therapeutic index may be best for
radiosensitive tumours, but detailed experimentation is required to determine
this. Also, the caveats listed in chapter 2 regarding naive extrapolation from
tumour experiments in animals to humans should be heeded, since they include
large differences in nuclear chromosome number, metabolic rate (and so oxygen
consumption), oxygen diffusion distances from blood vessels, tumour hypoxia
and re-oxygenation rates, cellular proliferation rates, growth fractions and overall
radiosensitivities. For example, murine tumours usually require a dose which is
around 3 times larger to achieve the same effect as in the human, and the optimum
treatment duration for fractionated treatment is much shorter in animals, often by
a factor of around 2 or more. Further examples can be found in standard
radiobiology textbooks. It is not surprising that many radiobiological ‘therapeutic advances’ found in animal experiments have failed to produce clear-cut
improvements in humans due to these factors and possibly others such as
differences in mutational characteristics, which are beyond the scope of this
chapter.
It remains to be seen whether protons and hadrons at ultra-high dose rates will be
useful in the clinic owing to their use in single fractions, the associated difficulties
with accurate dosimetry and the familiar question of if there are significant response
differences between tumours and normal tissues, especially since some slowergrowing tumour types have only slight differences in their physiology from that
found in normal tissues.
There are also significant issues to overcome in accelerator technology in order to
implement effective FLASH dose rates (Jolly et al 2020). This is a fast-moving area
of research where radiobiology, physics and careful clinical applications will be
required. The problems of clinical applications will be considerable, as FLASH
14-19

Quantitative Radiobiology for Proton Therapy
effects require use of larger dose per fraction in order to cross critical thresholds and
which will not be optimum in some tumour types.
14.6 Some untested situations
LET maps were fused with computed tomography scans over a decade ago
(Grassberger et al 2011). These LET values are based on averaged LET values
delivered from different angles to a target volume and at different times. It is not
known how relevant they are, since there are possibilities that LET radiosensitising
effects occur over very short durations of time (and are not as susceptible to
enzymatic radiation repair); the fundamental radiation processes occur over short
time windows and are complete within 2–30 ms (Wardman 2009). For the more
clustered DNA damage which occurs with higher LET, it remains to be seen if a
further dose given at an interval of, say, 5–10 min (consistent with gantry rotations
and positioning checks) will result in an additive or non-linear survival effect, as well
as on the yield of DNA and chromosomal breaks. This is an urgent question for
experimental verification using cell-survival experiments where dose is given using
such intervals.
14.7 Conclusions
There is considerable scope for experimental radiobiological studies to refine
knowledge about the relationship between LET and RBE in protons and other
heavier ions and how bioeffects can change with very high dose rates in different
tissues.
This book has covered LET-RBE modelling based on a strong experimental
evidence base that the maximum RBE for any ion will occur near to a specific LET
value of LET
with protons, where at around 30.5 keV μm
insufficient to cross a cell diameter. Such ideas need to be pursued further and
may offer a better starting point than many models based on DNA strand breaks
within a cell and tissue structure, with all of their complexities, although some
integration of various modelling approaches may be fruitful.
The aim must be to design experiments that will improve the predictive modelling
associated with particle physics applications in medicine by addressing fundamental
issues of how particle physics interacts with biosystems in a much more detailed way
than previously attempted in order to obtain more accurate and reliable parameters
than are available at the present time. The fulfilment of such a project would result in
better-understood systems for all ion-beam therapies and provide guidance towards
their optimal use.
Until that can be achieved, it will be necessary to make the best use of existing
historical radiobiological RBE data sets, and to plead for greater research funding
from governments to make particle therapies safer and more effective, either in some
more fortunate countries or by cooperative large-scale international projects based
at accessible, dedicated and reliable sites.
, determined by a combination of kinematic parameters, beginning
U
−1
the proton energy becomes
14-20

Quantitative Radiobiology for Proton Therapy
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