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Ray Cast/Dose Superposition algorithm for proton grid therapy
Stockholm University, Faculty of Science, Medical Radiation Physics (together with KI). (Medicinsk Strålningsfysik)
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Purpose: To develop a Ray Cast/Dose Superposition (RC/DS) algorithm for proton grid therapy. Its functionality needed to include automatic positioning of small proton pencil beams in a grid-pattern and superimposing thin beam Monte Carlo (MC) dose distribution data on a Computer Tomography (CT) density volume. The purpose was to calculate and store un-weighted volumetric dose distributions of individual proton energies for subsequent optimization.

Materials & Methods: Using the programming language Python 3.6, CT and Volume Of Interest (VOI) data of various patients and phantoms were imported. The target VOI was projected to either two or four planes, corresponding to the number of used gantry positions. Rays were then traced through the CT voxels, which were converted from Hounseld Units to density using a look up table, to calculate Water Equivalent Distance and proton energy needed to reach the proximal and distal edge of the target volume. With automated grid-pattern beam positioning, thin beam MC calculated depth dose distribution files were interpolated, scaled and superimposed on the CT volume for all beamlet positions. The algorithm reliability was tested on several CT image sets, the proton range estimation compared to a commercial TPS and the depth dose interpolation analyzed using MC simulations.

Results: The RC/DS algorithm computation time was on average around 6 hours and 30 minutes for each CT set. The dose distribution output visually conformed to target locations and maintained a grid pattern for all tested CT sets. It gave unwanted dose artifacts in situations when rays outside the beamlet center passed a significant length of low/high density regions compared to the center, which yielded dose distributions of unlikely shape. Interpolating MC dose distribution values showed comparability to true MC references of same energy, yielding results with 0.5% difference in relative range and dose.

Conclusions: The developed algorithm provides unweighted dose distributions specific for small beam proton grid therapy and has been shown to work for various setups and CT data. Un-optimized code caused longer computation times then intended but was presumed faster than MC simulations of the same setup. Efficiency and accuracy improvements are planed for in future work.

Place, publisher, year, edition, pages
2017. , p. 43
Keywords [en]
Proton Grid Therapy Treatment Radiation Dose Distribution Superpositioning Interlace Planning System Volume Effect Ray Cast Algorithm Medical Trace Plan Program Python Computer Tomography Volume Of Interest
National Category
Medical Equipment Engineering
Identifiers
URN: urn:nbn:se:su:diva-148174OAI: oai:DiVA.org:su-148174DiVA, id: diva2:1150012
Presentation
2017-10-05, Cancer centrum karolinska sjukhuset, Stockholm, 14:00 (English)
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Proton grid therapy groupAvailable from: 2019-02-21 Created: 2017-10-17 Last updated: 2019-02-21Bibliographically approved

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CiteExportLink to record
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