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Related Experiment Video

Updated: Oct 11, 2025

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

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Published on: September 4, 2017

Validation of Monte Carlo dose calculation algorithm for CyberKnife multileaf collimator.

Maude Gondré¹, Fanny Marsolat¹, Jean Bourhis²

¹Institute of Radiation Physics, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.

Journal of Applied Clinical Medical Physics

|December 1, 2021

Summary

The Monte Carlo (MC) algorithm for CyberKnife with a multileaf collimator (MLC) is clinically acceptable but underestimates dose by 1.5%. Use this algorithm cautiously in heterogeneous areas and for shallow tumors.

Keywords:

CyberKnife Monte Carlo dose algorithm commissioning multileaf collimator

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Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition

Published on: March 11, 2021

Area of Science:

Medical Physics
Radiation Oncology
Computational Dosimetry

Background:

Accurate dose calculation is crucial for effective radiation therapy.
The CyberKnife system with a multileaf collimator (MLC) requires precise dose verification.
Monte Carlo (MC) methods offer high accuracy in dose calculation.

Purpose of the Study:

To commission and validate the MC dose calculation algorithm for the CyberKnife MLC.
To assess the accuracy of the MC algorithm against measured dose distributions.
To determine the clinical applicability of the MC algorithm for treatment planning.

Main Methods:

Developed an MC model for the CyberKnife MLC within the treatment planning software (TPS).
Optimized MC parameters (maximum energy, source FWHM) by comparing calculated and measured tissue phantom ratios and profiles.
Validated the commissioned MC algorithm using ionization chambers, Gafchromic films, and patient-specific quality assurance (QA) with gamma index analysis.

Main Results:

Optimized MC parameters achieved good agreement with measurements (output factors within ±1%).
The MC model systematically underestimated dose by an average of -1.5%.
Dose underestimation increased with depth, reaching -3.0% at 15.5 cm.

Conclusions:

The commissioned MC algorithm for CyberKnife MLC is clinically acceptable.
A consistent dose underestimation of -1.5% necessitates careful application.
Recommended use in heterogeneous regions and for shallow-seated tumors to mitigate underestimation effects.