51. Improved calibration of mass stopping power in low density tissue for a proton pencil beam algorithm
- Author
-
Mark A. Hill, Mike Partridge, Daniel R Warren, and Ken Peach
- Subjects
Lung Neoplasms ,Proton ,Quantitative Biology::Tissues and Organs ,Physics::Medical Physics ,Monte Carlo method ,Nuclear magnetic resonance ,Carcinoma, Non-Small-Cell Lung ,Calibration ,Proton Therapy ,Stopping power (particle radiation) ,Humans ,Radiology, Nuclear Medicine and imaging ,Proton therapy ,Physics ,Range (particle radiation) ,Radiological and Ultrasound Technology ,Phantoms, Imaging ,Radiotherapy Planning, Computer-Assisted ,Radiotherapy Dosage ,Function (mathematics) ,Computational physics ,Tomography ,Tomography, X-Ray Computed ,Monte Carlo Method ,Algorithms - Abstract
Dose distributions for proton therapy treatments are almost exclusively calculated using pencil beam algorithms. An essential input to these algorithms is the patient model, derived from x-ray computed tomography (CT), which is used to estimate proton stopping power along the pencil beam paths. This study highlights a potential inaccuracy in the mapping between mass density and proton stopping power used by a clinical pencil beam algorithm in materials less dense than water. It proposes an alternative physically-motivated function (the mass average, or MA, formula) for use in this region. Comparisons are made between dose-depth curves calculated by the pencil beam method and those calculated by the Monte Carlo particle transport code MCNPX in a one-dimensional lung model. Proton range differences of up to 3% are observed between the methods, reduced to
- Published
- 2015