# Proton range uncertainty and the range margin

Source: https://onco.cc/terms/proton-range-uncertainty/  
OnCo record `proton-range-uncertainty` (Term). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

A proton beam stops at a depth that cannot be predicted exactly, so planners deliberately aim it a few millimetres past the tumour. At one leading centre the allowance is 3.5 per cent of the beam's range plus 1 millimetre, which for a beam reaching 20 centimetres into soft tissue means overshooting by about 8 millimetres.

## Summary

The main physical attraction of protons is that they stop: the dose peaks at the end of the track and falls almost to nothing beyond it. Where exactly the track ends depends on the stopping power of every tissue the beam passes through, which is estimated from the planning CT scan, and on set-up, anatomy on the day, beam delivery and the dose calculation. Each of these carries an error, and together they are called range uncertainty.

Planners protect the target by extending the beam's range by a margin. Paganetti's 2012 review gives the recipes in use at the time: 3.5 per cent of the range plus 1 millimetre at the Massachusetts General Hospital, 3.5 per cent plus 3 millimetres at MD Anderson, Loma Linda and the University of Pennsylvania, and 2.5 per cent plus 1.5 millimetres at the University of Florida. The MGH recipe goes back to estimates made with early-1980s CT. The review calls the resulting 8 millimetre overshoot for a 20 centimetre field 'quite substantial', and estimates that Monte Carlo dose calculation could reduce range uncertainty by several millimetres in complex geometry.

The margin matters because it spends part of the advantage protons are chosen for. Tissue just beyond the target receives dose the plan was built to avoid, and the biological effect at the end of the track is itself higher than the standard conversion factor assumes (see relative-biological-effectiveness).

## Fields

- Kind: Term
- Last checked: 2026-10-20
- Also known as: range uncertainty; proton range uncertainty; range margin
- Tags: precision; radiation

## Sources

- Paganetti, Range uncertainties in proton therapy and the role of Monte Carlo simulations (Physics in Medicine and Biology 2012): https://doi.org/10.1088/0031-9155/57/11/R99
- Full text in PubMed Central: https://pmc.ncbi.nlm.nih.gov/articles/PMC3374500/

## Connected records

- ideas: [Use LET, RBE and alpha/beta to decide when protons beat IMRT](https://onco.cc/ideas/idea-bio2-let-rbe-ab-selects-protons/)
- roadmaps: [Radiotherapy roadmap: X-rays → shaped beams → fewer fractions, particles and FLASH](https://onco.cc/roadmaps/radiation-roadmap/)
- fronts: [Radiation Therapy](https://onco.cc/fronts/radiation/)
- technologies: [In vivo dosimetry and patient-specific quality assurance](https://onco.cc/technologies/in-vivo-dosimetry/), [Pencil-beam scanning and intensity-modulated proton therapy](https://onco.cc/technologies/intensity-modulated-proton-therapy/), [Proton arc therapy](https://onco.cc/technologies/proton-arc-therapy/), [Proton therapy](https://onco.cc/technologies/proton-therapy/)
- terms: [Bragg peak](https://onco.cc/terms/bragg-peak/), [GTV, CTV and PTV (target volumes)](https://onco.cc/terms/planning-target-volume/), [Linear energy transfer (LET)](https://onco.cc/terms/linear-energy-transfer/), [Relative biological effectiveness (RBE)](https://onco.cc/terms/relative-biological-effectiveness/)
- key papers: [Bayesian adaptive randomization trial of passive scattering proton therapy and intensity-modulated photon radiotherapy for locally advanced non-small-cell lung cancer](https://onco.cc/key-papers/paper-liao-proton-vs-imrt-nsclc-jco-2018/), [Range uncertainties in proton therapy and the role of Monte Carlo simulations](https://onco.cc/key-papers/paper-paganetti-range-uncertainties-pmb-2012/), [Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer](https://onco.cc/key-papers/paper-paganetti-phys-med-biol/)

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