Poster Poster Program Therapy Physics

Scimoca™ Monte Carlo Benchmarking of the Cybercomm™ Reference Beam Data for Cyberknife® Commissioning

Abstract
Purpose

Reference beam data (RBD) is an efficient means to facilitate rapid and high quality linac and treatment planning system commissioning. We assessed the quality and reproducibility of the CyberComm™ RBD for CyberKnife® by creating a benchmark Monte Carlo (MC) beam model for the SciMoCa™ quality assurance (QA) product.

Methods

RBD was collected from 12 twinned CyberKnife linacs for all three collimator types (MLC, cone, variable cone), using the PTW MicroDiamond detector. The data was assessed and averaged with tolerances designed to meet clinical planning needs, guided by input from CyberKnife key opinion leaders. A MC virtual source model was created to match Depth-Dose-Curves (DDC) and output factors (OF) of the RBD (MLC). Beam models for the cone collimators were identical except for the collimator transport modules. Linac head and collimator geometries were derived from construction drawings. Agreement of MC simulations with RBD and customer measurements was assessed.

Results

The MC simulations reached an accuracy of a mean absolute deviation (MAD) of 0.23% for DDC of all MLC fields between 15.4 mm to 115.0 mm size, and a MAD of 0.17% for the OF, respectively. The average Gamma pass rate for dose deviation 0.5% / distance to agreement 0.5 mm for all cross-profiles was 99.6%. Agreement for the smallest fields < 10 mm was affected by small-field sensitivity of the MicroDiamond detector. The RBD-beam model matched the customer data well to within 20 keV deviation of the maximum energy. Small field OF (< 10 mm) were affected by variations of the focal spot radius in the order of 0.04 mm.

Conclusion

The CyberComm™ RBD shows very high internal consistency compared to a high-definition MC simulation. The RBD can be reproduced on customer linacs to an exacting standard, with minimal tweaking of the beam model only for small field OFs.

People

Related

Similar sessions

Poster Poster Program
Jul 19 · 07:00
Python-Based Automation Framework for Annual Machine QA Data Archiving In Qatrack+

Annual water-tank measurements help ensure beam characteristics remain consistent with commissioning baselines. However, the lack of a standardized processing workflow and decentralized data storage makes it difficult to analyze...

Syed Bilal Ahmad, PhD
Therapy Physics 0 people interested
Poster Poster Program
Jul 19 · 07:00
User Expectations and Current Availability of HDR Brachytherapy Audits In Europe

The aim of this work was to evaluate the need to implement more dosimetric audits in high‐dose‐rate brachytherapy (HDR-BT) in Europe and to identify which characteristics such audits should meet according to users.

Javier Vijande, PhD Laura Oliver Cañamás
Therapy Physics 0 people interested