arXiv subjects

Joakim da Silva

Publications and source records attributed to Joakim da Silva.

3 recordsLinked to original sources

arXiv2026

Cone-beam artifact reduction in Gamma Knife CBCT images using a line-arc-line scan trajectory

Objective. Gamma Knife cone-beam computed tomography (CBCT) images suffer from distinct cone-beam artifacts for some patients, due to the conical X-ray beam which is oriented to intersect the detector perpendicularly at its inferior edge. The use of an exotic scan trajectory which provides more complete sampling across the field of view than the current arc can reduce cone-beam artifacts. In this study, the feasibility of a line-arc-line scan trajectory for the Gamma Knife CBCT is assessed through a proof of concept. Approach. Using a customized research Gamma Knife, a Catphan 503 and an anthropomorphic head phantom are imaged for different exotic scan trajectories, consisting of combinations of arcs and lines. The CBCT images for each trajectory are then reconstructed with an iterative algorithm. Main results. A line-arc-line trajectory provides the largest image quality improvement among the investigated trajectories, with no noticeable cone-beam artifacts in the CBCT images: the axial interfaces between modules of the Catphan are well defined, and the superior edge of the phantom on the axial axis is sharper by 92\%, compared with the current arc trajectory. For the head CBCT images, the proposed trajectory removes most of the cone-beam artifact on the superior side of the skull, characteristic of the current Gamma Knife CBCT images. The artifact reduction also leads to a visual improvement in terms of uniformity in both phantoms. Significance. A line-arc-line CBCT scan trajectory would be feasible on the Gamma Knife with limited changes to the current configuration, and could produce images with improved image quality.

physics.med-ph↗

arXiv2026

Non-circular scan trajectories for reducing cone-beam artifacts in Gamma Knife CBCT images: a simulation study

Objective. Gamma Knife cone-beam computed tomography (CBCT) images are deteriorated by cone-beam artifacts whose magnitude increases along the superior direction. In this study, a novel scan trajectory compatible with the Gamma Knife CBCT system is optimized to reduce cone-beam artifacts, with the aim to replace the current 200-degree single-arc scan. Approach. Data sampling analysis with tomographic incompleteness maps indicates the level of undersampling across the field of view based on the geometry of the system and of a scan trajectory. Moreover, CBCT simulations are performed from a virtual phantom with disks aligned along the axial direction and from a CT reconstruction of a stereotactic end-to-end validation (STEEV) phantom. CBCT projections are simulated for a given scan trajectory through a polychromatic forward projection model with added noise and scatter, then the CBCT image is reconstructed using an iterative algorithm which minimizes weighted least squares. Main results. Both the incompleteness analysis and the CBCT simulations indicate adding lines to the current single-arc trajectory is more efficient to reduce cone-beam artifacts than adding more arcs, both in terms of number of additional projections and new artifacts. A line-arc-line trajectory with source axial steps of 3.5 mm removes virtually all cone-beam artifacts. The widths of the cone-beam artifacts created by the disks show a positive correlation between the artifact magnitude and the incompleteness value. Significance. A line-arc-line scan trajectory is promising to reduce cone-beam artifacts of the Gamma Knife CBCT images while being a compatible and reasonable trajectory for the current system design.

physics.med-ph↗

arXiv2025

A parallel algorithm for generating Pareto-optimal radiosurgery treatment plans

Using inverse planning tools to create radiotherapy treatment plans is an iterative process, where clinical trade-offs are explored by changing the relative importance of different objectives and rerunning the optimizer until a desirable plan is found. We seek to optimize hundreds of radiosurgery treatment plans, corresponding to different weightings of objectives, fast enough to incorporate interactive Pareto navigation of clinical trade-offs into the clinical workflow. We apply the alternating direction method of multipliers (ADMM) to the linear-program formulation of the optimization problem used in Lightning. We implement both a CPU and a GPU version of ADMM in Matlab and compare them to Matlab's built-in, single-threaded dual-simplex solver. The ADMM implementation is adapted to the optimization procedure used in the clinical software, with a bespoke algorithm for maximizing overlap between low-dose points for different objective weights. The method is evaluated on a test dataset consisting of 20 cases from three different indications, with between one and nine targets and total target volumes ranging from 0.66 to 52 cm3, yielding speedups of 1.6-97 and 54-1500 times on CPU and GPU, respectively, compared to simplex. Plan quality was evaluated by rerunning the ADMM optimization 20 times, each with a different random seed, for each test case and for nine objective weightings per case. The resulting clinical metrics closely mimicked those obtained when rerunning the simplex solver, verifying the validity of the method. In conclusion, we show how ADMM can be adapted for radiosurgery plan optimization, allowing hundreds of high-quality Gamma Knife treatment plans to be created in under two minutes on a single GPU, also for very large cases.

physics.med-ph↗