[This corrects the article DOI: 10.3389/fonc.2025.1695468.].

BACKGROUND:Intraoperative cone-beam computed tomography (CBCT) provides a valuable option for accurate three-dimensional applicator positioning in gynecologic brachytherapy, but is associated with radiation exposure and increased intervention time especially in case of repeated CBCT imaging being required for creating a sufficient implant arrangement. PURPOSE:To reduce the need for multiple CBCT scans for corresponding applicator verification, this work proposes two methods for needle path navigation, including corrections of potential bending in situ, by combining infrared tracking with planar x-ray imaging for enabling accurate intraoperative needle guidance. METHODS:An examined 200 mm brachytherapy needle was rigidly mounted on an infrared-reflective tracking tool to enable real time tracking. Two planar x-ray images, acquired from varying distinct angles, were used to determine the exact 3D position of the needle tip region via backprojection. A spline was fitted through the obtained coordinates to reconstruct the full needle path. Based on this, only a single initial CBCT scan was required to visualize the predicted needle path within this scan. Additionally, a second approach for needle prediction was presented focusing on only one planar x-ray image by incorporating prior needle bending information from the initial CBCT scan. Both methods were evaluated in preclinical studies and validated against a corresponding ground-truth obtained from CBCT. RESULTS:The proposed method considering two planar x-ray images successfully reconstructed the needle path with deviations of less than 1 mm from the CBCT reference scan, when using at least 20° offset between the x-ray image acquisitions. The single-scan approach, using prior bending information, yielded promising results with deviations at the tip of below 1.3 mm. CONCLUSIONS:Both described methods demonstrated their feasibility in preclinical studies, showing potential to improve and accelerate clinical implantation workflows by means of needle navigation in the future.

Background and purpose:Patient or treatment plan mix-ups are among the most serious patient-specific human errors in brachytherapy. However, many brachytherapy departments rely only on review by a second, independent person, which does not eliminate the risk of human failure. In this work, we developed and retrospectively evaluated an automated patient identification method based solely on the geometry of the interstitial implant in breast cancer patients. Materials and methods:The implant geometry is assessed using an electromagnetic tracking (EMT) system that provides real-time positional data of each catheter with sub-millimetre accuracy. The measured implant geometry is rigidly registered to the CT-based implant geometry associated with the clinical treatment plan. To quantitatively compare them, a similarity metric based on a distance-to-agreement (DTA) criterion (3-10 mm) and a pass rate threshold (50-95%) was used. The implants of 80 patients were included in the evaluation, resulting in 6400 patient-treatment plan combinations. Results:The classifier reliably identified patients with an area under the receiver operating characteristic (ROC) curve close to 1, highlighting an overall excellent discriminative performance. At the optimal decision threshold under the requirement of a false positive rate of 0%, it achieved a sensitivity between 94.8% and 97.5% depending on the DTA and pass rate thresholds, and an overall accuracy of 99.9%. Conclusion:Interstitial implants in breast brachytherapy are virtually unique, so determining their geometry prior to each fraction is a viable option for patient identification. The EMT-based automated technique has proven to be effective in detecting patient or treatment plan mix-ups with near-perfect accuracy.

BACKGROUND AND PURPOSE:Synthetic computed tomography (sCT) from magnetic resonance imaging (MRI) enables computed tomography (CT)-free cranial radiotherapy planning, yet no consensus exists on which head phantoms are usable for sCT quality assurance (QA). This study benchmarked head phantoms to identify the most promising candidates for cranial sCT QA and the design characteristics associated with favorable sCT-to-conventional CT agreement. MATERIALS AND METHODS:Ten head phantoms underwent clinical MRI (1.5 T) and CT imaging. Two vendor-provided sCT algorithms (2D slice-based, 3D volume-based) were applied to identical input. sCT and CT were compared using Dice similarity coefficient (DSC), 95th-percentile Hausdorff distance (HD95), CT number mean error (ME) within both a self-mask (sCT-derived) and a common-mask (CT-derived), and percentage dose deviations (%ΔD2%, %ΔD98%, %ΔDmean) across six beam configurations. Metrics were interpreted against a priori three-tier acceptance thresholds. RESULTS:Phantoms without internal skull-equivalent structures showed bone DSC ≤ 0.001 and common-mask bone ME≤ -1100 HU. Phantoms with skull-equivalent anatomy achieved bone DSC of 0.24-0.71, bone HD95 of 4.2-24.4 mm, and self-mask bone ME between -95 and +470 HU across both algorithms. Common-mask bone ME in skull-containing phantoms ranged from -198 to -1115 HU across both algorithms. Soft-tissue ME stayed within ±120 HU across skull-containing phantoms for both masks. Average absolute |%ΔDmean| was 3.2% (2D) and 3.7% (3D) without significant inter-algorithm difference (p = 0.49). CONCLUSIONS:Internal skull-equivalent anatomy is a necessary but not sufficient design characteristic; low-susceptibility and MR-compatible materials proved essential. Joint evaluation of geometric, CT number, and dose agreement was required to rank phantom performance. No phantom met all criteria simultaneously.