Related Experiment Video
Updated: Jul 18, 2026

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
Dosimetric verification of the anisotropic analytical algorithm for radiotherapy treatment planning
Christopher M Bragg1, John Conway
1Department of Radiotherapy Physics, Weston Park Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK. Christopher.Bragg@sth.nhs.uk
Background And Purpose:
To investigate the accuracy of photon dose calculations performed by the Anisotropic Analytical Algorithm, in homogeneous and inhomogeneous media and in simulated treatment plans.
Materials And Methods:
Predicted dose distributions were compared with ionisation chamber and film measurements for a series of increasingly complex situations. Initially, simple and complex fields in a homogeneous medium were studied. The effect of inhomogeneities was investigated using a range of phantoms constructed of water, bone and lung substitute materials. Simulated treatment plans were then produced using a semi-anthropomorphic phantom and the delivered doses compared to the doses predicted by the Anisotropic Analytical Algorithm.
Results:
In a homogeneous medium, agreement was found to be within 2% dose or 2mm dta in most instances. In the presence of heterogeneities, agreement was generally to within 2.5%. The simulated treatment plan measurements agreed to within 2.5% or 2mm.
Conclusions:
The accuracy of the algorithm was found to be satisfactory at 6 and 10MV both in homogeneous and inhomogeneous situations and in the simulated treatment plans. The algorithm was more accurate than the Pencil Beam Convolution model, particularly in the presence of low density heterogeneities.
More Related Videos
05:18Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources
Published on: October 6, 2023
07:57Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
Published on: March 24, 2022