Development of a TOPAS Monte Carlo (MC) model extension to simulate the automatic exposure control function of a C-arm CBCT.

Purpose: Accurate simulation of organ doses in C-arm CBCT is critical for estimating personalised patient dosimetry. However, system complexities such as automatic exposure control (AEC) and the incorporation of DICOM images into simulations are challenging. The aim of this study was to develop a model for mimicking the operation of an AEC system, which maintains a constant dose to the detector through mA modulation in order to facilitate more accurate MC dosimetry models for C-arm CBCT.

Evaluating dose coverage and conformity in stereotactic ablative body radiotherapy (SABR) plans.

Purpose: Accepted conformity metrics in stereotactic ablative body radiotherapy (SABR) have significant limitations. This work aimed to develop a spatial assessment methodology that improves and automates checks of dose prescription and dose gradient from planning target volume (PTV) edge.

Methods: A Python-based script was developed to determine linear distances from the PTV edge to specified isodose, every 15 degrees on all axial slices and along the central axis in the coronal plane.

A strategy to reduce fraction number in peripheral lung stereotactic ablative body radiotherapy.

Background And Purpose: Hypo-fractionated lung Stereotactic Ablative Body Radiotherapy (SABR) has often been avoided when tumours are close to the chest wall. Our strategic objective was the reduction of fraction number, while maintaining target biological effective dose coverage without increasing chest wall toxicity (CWT) predictors.

Materials And Methods: Twenty previously treated lung SABR patients were stratified into four cohorts according to distance from PTV to the chest wall, <1 cm, <0.

Clinical treatment planning for kilovoltage radiotherapy using EGSnrc and Python.

Kilovoltage radiotherapy dose calculations are generally performed with manual point dose calculations based on water dosimetry. Tissue heterogeneities, irregular surfaces, and introduction of lead cutouts for treatment are either not taken into account or crudely approximated in manual calculations. Full Monte Carlo (MC) simulations can account for these limitations but require a validated treatment unit model, accurately segmented patient tissues and a treatment planning interface (TPI) to facilitate the simulation setup and result analysis.

Energy-dependence investigation for a range of clinically used detectors from 70 kV to 6 MV.

Purpose: Accurate measurement of out-of-field dose in radiotherapy directly impacts beam data modeling in treatment planning systems, verification of implanted electronic devices/lens/fetus dose, secondary cancer risk estimation, and organ-at-risk dose reporting. When performing out-of-field dosimetry, it is therefore imperative that the response of the detector has been well characterized. Due to the softening of the radiation beam out-of-field, many detectors will exhibit energy dependence.