PurposeLeksell Gamma Knife® is a stereotactic radiosurgery system that allows fine‐grained control of the delivered dose distribution. We describe a new inverse planning approach that both resolves shortcomings of earlier approaches and unlocks new capabilities.MethodsWe fix the isocenter positions and perform sector‐duration optimization using linear programming, and study the effect of beam‐on time penalization on the trade‐off between beam‐on time and plan quality. We also describe two techniques that reduce the problem size and thus further reduce the solution time: dualization and representative subsampling.ResultsThe beam‐on time penalization reduces the beam‐on time by a factor 2–3 compared with the naïve alternative. Dualization and representative subsampling each leads to optimization time‐savings by a factor 5–20. Overall, we find in a comparison with 75 clinical plans that we can always find plans with similar coverage and better selectivity and beam‐on time. In 44 of these, we can even find a plan that also has better gradient index. On a standard GammaPlan workstation, the optimization times ranged from 2.3 to 26 s with a median time of 5.7 s.ConclusionWe present a combination of techniques that enables sector‐duration optimization in a clinically feasible time frame.

Medical imaging is an indispensable tool in radiotherapy for dose planning, image guidance and treatment monitoring. Cone beam CT (CBCT) is a low dose imaging technique with high spatial resolution capability as a direct by-product of using flat-panel detectors. However, certain issues such as x-ray scatter, beam hardening and other artifacts limit its utility to the verification of patient positioning using image-guided radiotherapy.Methods and Materials: Dual-energy (DE)-CBCT has recently demonstrated promise as an improved tool for tumor visualization in benchtop applications. It has the potential to improve soft-tissue contrast and reduce artifacts caused by beam hardening and metal. In this review, the practical aspects of developing a DE-CBCT based clinical and technical workflow are presented based on existing DE-CBCT literature and concepts adapted from the well-established library of work in DE-CT. Furthermore, the potential applications of DE-CBCT on its future role in radiotherapy are discussed.Results and Conclusions: Based on current literature and an investigation of future applications, there is a clear potential for DE-CBCT technologies to be incorporated into radiotherapy. The applications of DE-CBCT include (but are not limited to): adaptive radiotherapy, brachytherapy, proton therapy, radiomics and theranostics.

Accurate determination of collimator output factors is important for Leksell Gamma Knife radiosurgery. The new Leksell Gamma Knife Perfexion system has a completely redesigned collimator system and the collimator output factors are different from the other Leksell Gamma Knife models. In this study, a simple method was developed to validate the collimator output factors specifically for Leksell Gamma Knife Perfexion. The method uses double-shot exposures on a single film to eliminate repeated setups and the necessity to acquire dose calibration curves required for the traditional film exposure method. Using the method, the collimator output factors with respect to the 16 mm collimator were measured to be 0.929 +/- 0.009 and 0.817 +/- 0.012 for the 8 mm and the 4 mm collimator, respectively. These values are in agreement (within 2%) with the default values of 0.924 and 0.805 in the Leksell Gamma Plan treatment planning system. These values also agree with recently published results of 0.917 (8 mm collimator) and 0.818 (4 mm collimator) obtained from the traditional methods. Given the efficiency of the method, measurement and validation of the collimator output factors can be readily adopted in commissioning and quality assurance of a Leksell Gamma Knife Perfexion system.

One of the limiting factors in cone-beam CT (CBCT) image quality is system blur, caused by detector response, x-ray source focal spot size, azimuthal blurring, and reconstruction algorithm. In this work, we develop a novel iterative reconstruction algorithm that improves spatial resolution by explicitly accounting for image unsharpness caused by different factors in the reconstruction formulation. While the model-based iterative reconstruction techniques use prior information about the detector response and x-ray source, our proposed technique uses a simple measurable blurring model. In our reconstruction algorithm, denoted as simultaneous deblurring and iterative reconstruction (SDIR), the blur kernel can be estimated using the modulation transfer function (MTF) slice of the CatPhan phantom or any other MTF phantom, such as wire phantoms. The proposed image reconstruction formulation includes two regularization terms: (1) total variation (TV) and (2) nonlocal regularization, solved with a split Bregman augmented Lagrangian iterative method. The SDIR formulation preserves edges, eases the parameter adjustments to achieve both high spatial resolution and low noise variances, and reduces the staircase effect caused by regular TV-penalized iterative algorithms. The proposed algorithm is optimized for a point-of-care head CBCT unit for image-guided radiosurgery and is tested with CatPhan phantom, an anthropomorphic head phantom, and 6 clinical brain stereotactic radiosurgery cases. Our experiments indicate that SDIR outperforms the conventional filtered back projection and TV penalized simultaneous algebraic reconstruction technique methods (represented by adaptive steepest-descent POCS algorithm, ASD-POCS) in terms of MTF and line pair resolution, and retains the favorable properties of the standard TV-based iterative reconstruction algorithms in improving the contrast and reducing the reconstruction artifacts. It improves the visibility of the high contrast details in bony areas and the brain soft-tissue. For example, the results show the ventricles and some brain folds become visible in SDIR reconstructed images and the contrast of the visible lesions is effectively improved. The line-pair resolution was improved from 12 line-pair/cm in FBP to 14 line-pair/cm in SDIR. Adjusting the parameters of the ASD-POCS to achieve 14 line-pair/cm caused the noise variance to be higher than the SDIR. Using these parameters for ASD-POCS, the MTF of FBP and ASD-POCS were very close and equal to 0.7 mm which was increased to 1.2 mm by SDIR, at half maximum.

Stereotactic radiosurgery (SRS) is an effective technique to treat brain metastasis for which several inverse planning methods may be appropriate. We compare three different optimization models for segment duration optimization in SRS using Leksell Gamma Knife Icon (Elekta, Stockholm, Sweden). We investigate (1) a linear programming approach, (2) a piecewise quadratic penalty approach, and (3) an unconstrained convex moment-based penalty approach. We examine the performances of these approaches using anonymized data from 14 previously treated cases. In addition, we investigate the important modeling question of selecting weights for the objective functions where we use a simulated annealing algorithm to determine these weights for each model. The inverse plans obtained via optimization models are compared against each other and against the clinical plans. The three inverse planning models can all yield optimal treatment plans in a reasonable amount of time and the treatment plans obtained by these models meet or exceed clinical guidelines while displaying high conformity.