In-silico evaluation of the effect of set-up errors on dose delivery during mouse irradiations with a Cs-137 cell irradiator-based collimator system.

Set-up errors are a problem for pre-clinical irradiators that lack imaging capabilities. The aim of this study was to investigate the impact of the potential set-up errors on the dose distribution for a mouse with a xenographic tumour irradiated with a standard Cs-137 cell irradiator equipped with an in-house lead collimator with 10 mm diameter apertures. The EGSnrc Monte-Carlo (MC) code was used to simulate the potential errors caused by displacements of the mouse in the irradiation setup.

Absorbed dose calculation for a realistic CT-derived mouse phantom irradiated with a standard Cs-137 cell irradiator using a Monte Carlo method.

Computed tomography (CT) derived Monte Carlo (MC) phantoms allow dose determination within small animal models that is not feasible with in-vivo dosimetry. The aim of this study was to develop a CT-derived MC phantom generated from a mouse with a xenograft tumour that could then be used to calculate both the dose heterogeneity in the tumour volume and out of field scattered dose for pre-clinical small animal irradiation experiments. A BEAMnrc Monte-Carlo model has been built of our irradiation system that comprises a lead collimator with a 1 cm diameter aperture fitted to a Cs-137 gamma irradiator.

A novel add-on collimator for preclinical radiotherapy applications using a standard cell irradiator: design, construction, and validation.

Purpose: Preclinical radiotherapy applications require dedicated irradiation systems which are expensive and not widely available. In this work, a clinical dual source Cs cell irradiator was adapted to deliver 1-cm diameter preclinical treatment beams using a lead and stainless steel custom-made collimator to treat one or two mice at a time.

Methods: The dosimetric characteristics of all the different components of the system (including collimator, phantoms, and radiation sources) have been simulated with EGSnrc Monte Carlo methods.