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Evaluation of Radiotherapy Plan Robustness: A Systematic Literature Review.

S Kim¹, D Bernstein¹, A Taylor¹

¹The Institute of Cancer Research, 123 Old Brompton Road, SW7 3RP, UK; The Royal Marsden NHS Foundation Trust, 203 Fulham Road, SW3 6JJ, UK.

Clinical Oncology (Royal College of Radiologists (Great Britain))

|October 14, 2025

Summary

Evaluating radiotherapy treatment plan robustness is crucial due to complex plans and reduced margins. Current methods vary, lacking consensus, but combining dose-volume histogram (DVH)-based and voxel-based metrics is recommended for improved safety.

Keywords:

Geometric uncertainties plan robustness radiotherapy treatment plan evaluation

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Area of Science:

Radiotherapy
Medical Physics
Radiation Oncology

Background:

Modern radiotherapy employs conformal and complex treatment plans.
Reduced safety margins and hypofractionation increase vulnerability to geometric uncertainties.
Evaluating treatment plan robustness is essential for safe and effective radiotherapy delivery.

Purpose of the Study:

To provide a comprehensive overview of current practices for assessing treatment plan robustness.
To identify common methods and uncertainties considered in robustness evaluations.
To highlight the need for standardized approaches in radiotherapy plan assessment.

Main Methods:

Systematic literature review of studies evaluating plan robustness up to July 2025.
Analysis of 225 publications meeting inclusion criteria from an initial 287.
Categorization of robustness evaluation methods into dose-volume histogram (DVH)-based, voxel-based, and radiobiological metrics.

Main Results:

Proton therapy was the focus of most studies (173/225).
Setup and range uncertainties were most commonly considered.
Methods varied, with DVH-based visualization being frequent, alongside voxel-based and radiobiological metrics.

Conclusions:

No international consensus currently exists for evaluating radiotherapy plan robustness.
A combination of DVH-based and spatially informative voxel-based metrics is recommended.
Standardized frameworks and integrated software tools are needed for clinical adoption.