Paper
1 April 2016 Monte Carlo investigation of the dosimetric effect of the Autoscan ultrasound probe for guidance in radiotherapy
Michael Martyn, Tuathan O'Shea, Emma Harris, Jeffrey Bamber, Stephen Gilroy, Mark J. Foley
Author Affiliations +
Abstract
The aim of this study was to quantify the dosimetric effect of the AutoscanTM ultrasound probe, which is a 3D transperineal probe used for real-time tissue tracking during the delivery of radiotherapy. CT images of a solid water phantom, with and without the probe placed in contact with its surface, were obtained (0.75 mm slice width, 140 kVp). CT datasets were used for relative dose calculation in Monte Carlo simulations of a 7-field plan delivered to the phantom. The Monte Carlo software packages BEAMnrc and DOSXYZnrc were used for this purpose. A number of simulations, which varied the distance of the radiation field edge from the probe face (0 mm to 5 mm) were performed. Perineal surface doses as a function of distance from the radiation field edge, with and without the probe in place, were compared. The presence of the probe was found to result in negligible dose differences when the radiation field is not delivered through the probe. A maximum surface dose increase of ≈1% was found when the probe face to field edge distance was 0 mm. Surface doses with and without the probe in place agreed within Monte Carlo simulation uncertainty at distances ≥ 3 mm. Using data from three patient volunteers, a typical probe face to field edge distance was calculated to be ≈20 mm. Our results therefore indicate that the presence of the probe does not adversely affect a typical patient treatment, due to the relatively large probe face to field edge distance.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Martyn, Tuathan O'Shea, Emma Harris, Jeffrey Bamber, Stephen Gilroy, and Mark J. Foley "Monte Carlo investigation of the dosimetric effect of the Autoscan ultrasound probe for guidance in radiotherapy", Proc. SPIE 9790, Medical Imaging 2016: Ultrasonic Imaging and Tomography, 97900N (1 April 2016); https://doi.org/10.1117/12.2216653
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KEYWORDS
Monte Carlo methods

Computed tomography

Radiotherapy

Prostate

Ultrasonography

Data modeling

Computer simulations

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