Scripted spot removal in PBS proton therapy planning.

BACKGROUND: It is well known in proton therapy that the relative biological effectiveness (RBE) is not constant across the entire Bragg peak, with higher RBE at the distal end of the Bragg peak due to higher linear energy transfer (LET). Treatment planning systems are moving toward LET optimization to mitigate this potentially higher biological impact at a track end. However, using a simple script, proton users can begin to simulate this process by deleting spots from critical structures during optimization. In most cases, nominal target coverage and plan robustness remain satisfactory. METHODS: In our clinic, we developed a script that allows the user to delete spots in all organs at risk (OARs) of interest for one or more treatment beams. The purpose of this script is to potentially reduce side effects by eliminating Bragg peaks within OARs. The script was first used for prostate patients where spots in the rectum and sigmoid, outside of the overlap with the target, were deleted. We then began to use the script for head and neck (H&N) and breast/chestwall patients to reduce acute side effects of the skin by removing spots in a 0.5-cm skin rind. CONCLUSIONS: By utilizing a simple script for deleting spots in critical structures, we have seen excellent clinical results thus far. We have noted reduced skin reactions for nearly all H&N and breast patients.

Validation of automated complex head and neck treatment planning with pencil beam scanning proton therapy.

BACKGROUND: Pencil beam scanning (PBS) proton therapy offers dosimetric advantages for several treatment sites, including head and neck (H&N). However, to achieve the optimal target coverage and robustness, these plans can be complex and time consuming to develop and optimize. Automating the treatment planning process can ensure a high-quality and standardized plan, reduce burden to the planner, and decrease time-to-treatment. We utilized in-house scripting to automate a four-field multi-field optimization (MFO) H&N planning technique. METHODS AND MATERIALS: Ten bilateral H&N patients were planned in RayStation v6 with a four-field modified-X beam configuration using MFO planning. Automation included creation of avoidance structures to control spot placement and development of standardized beams, PBS spot settings, robust optimization objectives, and patient-specific predicted planning constraints. Each patient was planned both with and without automation to evaluate differences in planning time, perceived effort and plan quality, plan robustness, and OAR sparing. RESULTS: On average, scripted plans required 3.2 h, compared to 4.3 h without the script. There was no difference in target coverage or plan robustness with or without automation. Automation significantly reduced mean dose to the oral cavity, parotids, esophagus, trachea, and larynx. Perceived effort was scaled from 1 (minimum effort) to 100 (maximum effort), and automation reduced perceived effort by 42% (p < 0.05). Two non-scripted plans required re-planning due to errors. CONCLUSIONS: Automation of this multi-beam, the MFO proton planning process reduced planning time and improved OAR sparing compared to the same planning process without scripting. Scripting generation of complex structures and planning objectives reduced burden on the planner. With most current treatment planning software, this automation is simple to implement and can standardize quality of care across all treatment planners.

Proton range verification in homogeneous materials through acoustic measurements.

Clinical proton beam quality assurance (QA) requires a simple and accurate method to measure the proton beam Bragg peak (BP) depth. Protoacoustics, the measurement of the pressure waves emitted by thermal expansion resulting from proton dose deposition, may be used to obtain the depth of the BP in a phantom by measuring the time-of-flight of the pressure wave. Rectangular and cylindrical phantoms of different materials (aluminum, lead, and polyethylene) were used for protoacoustic studies. Four different methods for analyzing the protoacoustic signals are compared. Data analysis shows that, for Methods 1 and 2, plastic phantoms have better accuracy than metallic ones because of the lower speed of sound. Method 3 does not require characterizing the speed of sound in the material, but it results in the largest error. Method 4 exhibits minimal error, less than 3 mm (with an uncertainty ⩽1.5 mm) for all the materials and geometries. Psuedospectral wave-equation simulations (k-Wave MATLAB toolbox) are used to understand the origin of acoustic reflections within the phantom. The presented simulations and experiments show that protoacoustic measurements may provide a low cost and simple QA procedure for proton beam range verification as long as the proper phantoms and calculation methods are used.