arXiv subjects

Alexandra Alain-Beaudoin

Publications and source records attributed to Alexandra Alain-Beaudoin.

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↗

arXiv2024

Generating Synthetic Computed Tomography for Radiotherapy: SynthRAD2023 Challenge Report

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast. Still, it lacks electron density information while cone beam CT (CBCT) lacks direct electron density calibration and is mainly used for patient positioning. Adopting MRI-only or CBCT-based adaptive radiotherapy eliminates the need for CT planning but presents challenges. Synthetic CT (sCT) generation techniques aim to address these challenges by using image synthesis to bridge the gap between MRI, CBCT, and CT. The SynthRAD2023 challenge was organized to compare synthetic CT generation methods using multi-center ground truth data from 1080 patients, divided into two tasks: 1) MRI-to-CT and 2) CBCT-to-CT. The evaluation included image similarity and dose-based metrics from proton and photon plans. The challenge attracted significant participation, with 617 registrations and 22/17 valid submissions for tasks 1/2. Top-performing teams achieved high structural similarity indices (>0.87/0.90) and gamma pass rates for photon (>98.1%/99.0%) and proton (>97.3%/97.0%) plans. However, no significant correlation was found between image similarity metrics and dose accuracy, emphasizing the need for dose evaluation when assessing the clinical applicability of sCT. SynthRAD2023 facilitated the investigation and benchmarking of sCT generation techniques, providing insights for developing MRI-only and CBCT-based adaptive radiotherapy.

physics.med-ph↗