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01.12.2017 | Research | Ausgabe 1/2017 Open Access

Radiation Oncology 1/2017

Optimization of the prescription isodose line for Gamma Knife radiosurgery using the shot within shot technique

Zeitschrift:
Radiation Oncology > Ausgabe 1/2017
Autoren:
Perry B. Johnson, Maria I. Monterroso, Fei Yang, Eric Mellon
Wichtige Hinweise

Electronic supplementary material

The online version of this article (10.​1186/​s13014-017-0919-4) contains supplementary material, which is available to authorized users.

Abstract

Background

This work explores how the choice of prescription isodose line (IDL) affects the dose gradient, target coverage, and treatment time for Gamma Knife radiosurgery when a smaller shot is encompassed within a larger shot at the same stereotactic coordinates (shot within shot technique).

Methods

Beam profiles for the 4, 8, and 16 mm collimator settings were extracted from the treatment planning system and characterized using Gaussian fits. The characterized data were used to create over 10,000 shot within shot configurations by systematically changing collimator weighting and choice of prescription IDL. Each configuration was quantified in terms of the dose gradient, target coverage, and beam-on time. By analyzing these configurations, it was found that there are regions of overlap in target size where a higher prescription IDL provides equivalent dose fall-off to a plan prescribed at the 50% IDL. Furthermore, the data indicate that treatment times within these regions can be reduced by up to 40%. An optimization strategy was devised to realize these gains. The strategy was tested for seven patients treated for 1–4 brain metastases (20 lesions total).

Results

For a single collimator setting, the gradient in the axial plane was steepest when prescribed to the 56–63% (4 mm), 62–70% (8 mm), and 77–84% (16 mm) IDL, respectively. Through utilization of the optimization technique, beam-on time was reduced by more than 15% in 16/20 lesions. The volume of normal brain receiving 12 Gy or above also decreased in many cases, and in only one instance increased by more than 0.5 cm3.

Conclusions

This work demonstrates that IDL optimization using the shot within shot technique can reduce treatment times without degrading treatment plan quality.
Zusatzmaterial
Additional file 1: Figures S1. Multi-Gaussian fit of the data sampled from the planning system for the 8 mm collimator setting (X/Y axis above, Z axis below). Roughly 70 points were sampled for each collimator setting and direction using the line measurement tool available in the planning system. Figure S2. Dose gradient for the X/Y and Z dimensions, 16 mm collimator setting. Figure S3. Dose gradient for the X/Y and Z dimensions, 4 mm collimator setting. Figure S4. Gradient distance (factor = 0.5) in the axial plane when utilizing the shot within shot technique. Figure S5. Dose profiles in the axial dimension when using different shot within shot combinations to produce plans with the same prescription isodose diameter and similar dose gradients. The three numbers associated with each area plot are the weighting of the 4 mm, 8 mm, and 16 mm collimator settings. Figure S6. Curves representing shot within shot plans prescribed at the 50%IDL (blue) and those optimized for beam-on time (orange) and gradient distance (red). Notice the difference in the curves within the transition zones where prescribing to IDLs less than 50% minimizes the gradient distance. Because the optimization of beam-on time was designed to provide a similar gradient distance as plans prescribed at the 50% IDL, the blue and orange curves are very similar, though different in terms of beam-on time, prescription IDL, and maximum target dose. Figure S7. Twin peaks representing the time savings predicted when using shot within shot optimization. The different colors represent different similarity constraints for the gradient distance (factor = 0.5) ranging from 1 to 10%. Figure S8. Beam-on time saved using shot within shot optimization on 7 actual patients (20 lesions). The shape of the data is similar to that predicted based on phantom simulation. (DOCX 3977 kb)
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