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Background: Image‐guided radiation‐therapy (IGRT)‐based robotic radiosurgery using magnetic resonance imaging (MRI)‐only simulation could allow for improved target definition with highly conformal radiotherapy treatments. Fiducial marker (FM)‐based alignment is used with robotic radiosurgery treatments of sites such as the prostate because it aids in accurate target localization. Synthetic CT (sCT) images are generated in the MRI‐only workflow but FMs used for IGRT appear as signal voids in MRIs and do not appear in MR‐generated sCTs, hindering the ability to use sCTs for fiducial‐based IGRT. Purpose: In this study we evaluate the fiducial tracking accuracy for a novel artificial fiducial insertion method in sCT images that allows for fiducial marker tracking in robotic radiosurgery, using MRI‐only simulation imaging (MRI‐only workflow). Methods: Artificial fiducial markers were inserted into sCT images at the site of the real marker implantation as visible in MRI. Two phantoms were used in this study. A custom anthropomorphic pelvis phantom was designed to validate the tracking accuracy for a variety of artificial fiducials in an MRI‐only workflow. A head phantom containing a hidden target and orthogonal film pair inserts was used to perform end‐to‐end tests of artificial fiducial configurations inserted in sCT images. The setup and end‐to‐end targeting accuracy of the MRI‐only workflow were compared to the computed tomography (CT)‐based standard. Each phantom had six FMs implanted with a minimum spacing of 2 cm. For each phantom a bulk‐density sCT was generated, and artificial FMs were inserted at the implantation location. Several methods of FM insertion were tested including: (1) replacing HU with a fixed value (10000HU) (voxel‐burned); (2) using a representative fiducial image derived from a linear combination of fiducial templates (composite‐fiducial); (3) computationally simulating FM signal voids using a digital phantom containing FMs and inserting the corresponding signal void into sCT images (simulated‐fiducial). All tests were performed on a CyberKnife system (Accuray, Sunnyvale, CA). Treatment plans and digital‐reconstructed‐radiographs were generated from the original CT and sCTs with embedded fiducials and used to align the phantom on the treatment couch. Differences in the initial phantom alignment (3D translations/rotations) and tracking parameters between CT‐based plans and sCT‐based plans were analyzed. End‐to‐end plans for both scenarios were generated and analyzed following our clinical protocol. Results: For all plans, the fiducial tracking algorithm was able to identify the fiducial locations. The mean FM‐extraction uncertainty for the composite and simulated FMs was below 48% for fiducials in both the anthropomorphic pelvis and end‐to‐end phantoms, which is below the 70% treatment uncertainty threshold. The total targeting error was within tolerance (<0.95 mm) for end‐to‐end tests of sCT images with the composite and head‐on simulated FMs (0.26, 0.44, and 0.35 mm for the composite fiducial in sCT, head‐on simulated fiducial in sCT, and fiducials in original CT, respectively. Conclusions: MRI‐only simulation for robotic radiosurgery could potentially improve treatment accuracy and reduce planning margins. Our study has shown that using a composite‐derived or simulated FM in conjunction with sCT images, MRI‐only workflow can provide clinically acceptable setup accuracy in line with CT‐based standards for FM‐based robotic radiosurgery. [ABSTRACT FROM AUTHOR]

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With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available several approaches for automated marker-based alignment of tilt series, manual user intervention remains necessary for many datasets, thus preventing high-throughput tomography. We have developed a MATLAB-based framework integrated into the Dynamo software package for automatic detection of fiducial markers that generates a robust alignment model with minimal input parameters. This approach allows high-throughput, unsupervised volume reconstruction. This new module extends Dynamo with a large repertory of tools for tomographic alignment and reconstruction, as well as specific visualization browsers to rapidly assess the biological relevance of the dataset. Our approach has been successfully tested on a broad range of datasets that include diverse biological samples and cryo-ET modalities. [Display omitted] • Automated gold-based alignment of cryo-ET tilt series in Dynamo • Robustness validated in 356 tilt series, aligning 99.7% micrographs out of 14387 • Automated alignment shown to be suitable for high resolution subtomogram averaging Coray et al. present the software implementation of an algorithm for alignment of cryo electron tomography tilt series, necessary to correct the mechanical imperfections of data acquisition and bring all acquired micrographs to a common geometric reference. The software has been tested on different samples, assessing its robustness and accuracy. [ABSTRACT FROM AUTHOR]

Objective: Our study aims to estimate intra-fraction six-dimensional (6D) tumor motion with rotational correction and the related correlations between motions of different degrees of freedom (DoF), as well as quantify sufficient anisotropic clinical target volume (CTV) to planning target volume (PTV) margins during stereotactic body radiotherapy (SBRT) of liver cancer with fiducial tracking technique. Methods: A cohort of 12 patients who were implanted with 3 or 4 golden markers were included in this study, and 495 orthogonal kilovoltage (kV) pairs of images acquired during the first fraction were used to extract the spacial position of each golden marker. Translational and rotational motions of tumor were calculated based on the marker coordinates by using an iterative closest point (ICP) algorithm. Moreover, the Pearson product-moment correlation coefficients (r) were applied to quantify the correlations between motions with different degrees of freedom (DoFs). The population mean displacement (MP), systematic error (S) and random error (s) were obtained to calculate PTV margins based on published recipes. Results: The mean translational variability of tumors were 0.56, 1.24 and 3.38 mm in the left-right (LR, X), anterior-posterior (AP, Y), and superiorinferior (SI, Z) directions, respectively. The average rotational angles θX, θY and θZ around the three coordinate axes were 0.88, 1.24 and 1.12, respectively. (|r|>0.4) was obtainted between Y -Z, Y - θZ, Z-θZ and θX - θY. The PTV margins calculated based on 13 published recipes in X, Y, and Z directions were 1.08, 2.26 and 5.42 mm, and the 95% confidence interval (CI) of them were (0.88,1.28), (1.99,2.53) and (4.78,6.05), respectively. Conclusions: The maximum translational motion was in SI direction, and the largest correlation coefficient of Y-Z was obtained. We recommend margins of 2, 3 and 7 mm in LR, AP and SI directions, respectively. [ABSTRACT FROM AUTHOR]

Purpose: Motion management is critical for prostate stereotactic body radiotherapy (SBRT) due to its high fractional dose and proximity to organs at risk. This study seeks to quantify the advantages of MV–kV tracking over kV imaging alone through a retrospective analysis of over 300 patients who underwent prostate SBRT treatment using MV–kV tracking. Methods: An MV–kV imaging‐based fiducial tracking technique has been developed at our institute and become a standard clinical practice. This technique calculates three‐dimensional (3D) fiducial displacement in real time from orthogonal kV and MV images acquired simultaneously. The patient will be repositioned if for two consecutive MV–kV data points, the motion is larger than a tolerance of 1.5 mm in any of the lateral, superior–inferior, and/or anterior–posterior directions. This study retrospectively analyzed detected 3D motions using an MV–kV approach of 324 patients who recently underwent prostate SBRT treatments. An algorithm was developed to recover the 2D motion components as if they were detected by kV or MV imaging alone. Results: Our results indicated that out‐of‐tolerance motions were primarily limited to the range of 1.5–3 mm (>95%). The motions are primarily anterior–posterior and superior–inferior, with less than 14.8% of the occurrences in the lateral direction. Compared to out‐of‐tolerance occurrences detected by MV–kV approach, kV alone caught 46.6% of motions in all three directions, and MV alone caught 46.7%. kV alone shows an overall missing rate of 45.8% for superior–inferior motions and 38.6% for lateral motions. It is also demonstrated that the detectability of motion in specific directions greatly depends on gantry angles, as does the missing rate. Conclusions: Our study demonstrated that MV–kV imaging‐based intrafraction motion tracking is superior to single kV imaging for prostate SBRT in clinical practice. [ABSTRACT FROM AUTHOR]

Thick specimens, as encountered in cryo-scanning transmission electron tomography, offer special challenges to conventional reconstruction workflows. The visibility of features, including gold nanoparticles introduced as fiducial markers, varies strongly through the tilt series. As a result, tedious manual refinement may be required in order to produce a successful alignment. Information from highly tilted views must often be excluded to the detriment of axial resolution in the reconstruction. We introduce here an approach to tilt series alignment based on identification of fiducial particle clusters that transform coherently in rotation, essentially those that lie at similar depth. Clusters are identified by comparison of tilted views with a single untilted reference, rather than with adjacent tilts. The software, called ClusterAlign, proves robust to poor signal to noise ratio and varying visibility of the individual fiducials and is successful in carrying the alignment to the ends of the tilt series where other methods tend to fail. ClusterAlign may be used to generate a list of tracked fiducials, to align a tilt series, or to perform a complete 3D reconstruction. Tools to evaluate alignment error by projection matching are included. Execution involves no manual intervention, and adherence to standard file formats facilitates an interface with other software, particularly IMOD/etomo, tomo3d, and tomoalign. [ABSTRACT FROM AUTHOR]

Purpose: To develop an internal target volume (ITV) margin determination framework (or decision-supporting framework) for treating multiple lung metastases using CyberKnife Synchrony with intraoperatively implanted fiducial markers (IIFMs). The feasibility of using non-ideally implanted fiducial markers (a limited number and/or far from a target) for tracking-based lung stereotactic ablative radiotherapy (SABR) was investigated. Methods: In the developed margin determination framework, an optimal set of IIFMs was determined to minimize a tracking uncertainty-specific ITV (ITVtracking) margin (margin required to cover target-to-marker motion discrepancy), i.e., minimize the motion discrepancies between gross tumor volume (GTV) and the selected set of fiducial markers (FMs). The developed margin determination framework was evaluated in 17 patients with lung metastases. To automatically calculate the respiratory motions of the FMs, a template matching-based FM tracking algorithm was developed, and GTV motion was manually measured. Furthermore, during-treatment motions of the selected FMs were analyzed using log files and compared with those calculated using 4D CTs. Results: For 41 of 42 lesions in 17 patients (97.6%), an optimal set of the IIFMs was successfully determined, requiring an ITVtracking margin less than 5 mm. The template matching-based FM tracking algorithm calculated the FM motions with a sub-millimeter accuracy compared with the manual measurements. The patient respiratory motions during treatment were, on average, significantly smaller than those measured at simulation for the patient cohort considered. Conclusion: Use of the developed margin determination framework employing CyberKnife Synchrony with a limited number of IIFMs is feasible for lung SABR. [ABSTRACT FROM AUTHOR]

PurposeTo develop an internal target volume (ITV) margin determination framework (or decision-supporting framework) for treating multiple lung metastases using CyberKnife Synchrony with intraoperatively implanted fiducial markers (IIFMs). The feasibility of using non-ideally implanted fiducial markers (a limited number and/or far from a target) for tracking-based lung stereotactic ablative radiotherapy (SABR) was investigated.MethodsIn the developed margin determination framework, an optimal set of IIFMs was determined to minimize a tracking uncertainty-specific ITV (ITVtracking) margin (margin required to cover target-to-marker motion discrepancy), i.e., minimize the motion discrepancies between gross tumor volume (GTV) and the selected set of fiducial markers (FMs). The developed margin determination framework was evaluated in 17 patients with lung metastases. To automatically calculate the respiratory motions of the FMs, a template matching-based FM tracking algorithm was developed, and GTV motion was manually measured. Furthermore, during-treatment motions of the selected FMs were analyzed using log files and compared with those calculated using 4D CTs.ResultsFor 41 of 42 lesions in 17 patients (97.6%), an optimal set of the IIFMs was successfully determined, requiring an ITVtracking margin less than 5 mm. The template matching-based FM tracking algorithm calculated the FM motions with a sub-millimeter accuracy compared with the manual measurements. The patient respiratory motions during treatment were, on average, significantly smaller than those measured at simulation for the patient cohort considered.ConclusionUse of the developed margin determination framework employing CyberKnife Synchrony with a limited number of IIFMs is feasible for lung SABR.

Abstract Background Tumor motion may compromise the accuracy of liver stereotactic radiotherapy. In order to carry out a precise planning, estimating liver tumor motion during radiotherapy has received a lot of attention. Previous approach may have difficult to deal with image data corrupted by noise. The iterative closest point (ICP) algorithm is widely used for estimating the rigid registration of three-dimensional point sets when these data were dense or corrupted. In the light of this, our study estimated the three-dimensional (3D) rigid motion of liver tumors during stereotactic liver radiotherapy using reconstructed 3D coordinates of fiducials based on the ICP algorithm. Methods Four hundred ninety-five pairs of orthogonal kilovoltage (KV) images from the CyberKnife stereo imaging system for 12 patients were used in this study. For each pair of images, the 3D coordinates of fiducial markers inside the liver were calculated via geometric derivations. The 3D coordinates were used to calculate the real-time translational and rotational motion of liver tumors around three axes via an ICP algorithm. The residual error was also investigated both with and without rotational correction. Results The translational shifts of liver tumors in left-right (LR), anterior-posterior (AP),and superior-inferior (SI) directions were 2.92 ± 1.98 mm, 5.54 ± 3.12 mm, and 16.22 ± 5.86 mm, respectively; the rotational angles in left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 3.95° ± 3.08°, 4.93° ± 2.90°, and 4.09° ± 1.99°, respectively. Rotational correction decreased 3D fiducial displacement from 1.19 ± 0.35 mm to 0.65 ± 0.24 mm (P

Background: Fiducial markers are frequently used before treatment for image‐guided patient setup in radiation therapy (RT), but can also be used during treatment for image‐guided intrafraction motion detection. This report describes our implementation of automatic marker detection with periodic kV imaging (TrueBeam v2.5) to monitor and correct intrafraction motion during prostate RT. Methods: We evaluated the reproducibility and accuracy of software fiducial detection using a phantom with 3 implanted fiducial markers. Clinical implementation for patients with intraprostatic fiducials receiving volumetric modulated arc therapy (VMAT) utilized periodic on‐board kV imaging with 10 s intervals during treatment delivery. For each image, the software automatically identified fiducial locations and determined whether their distance relative to planned locations were within a 3 mm tolerance. Motion was corrected if either ≥2 fiducials in a single image or ≥1 fiducial in sequential images were out of tolerance. Results: Phantom studies demonstrated poorer performance of linear fiducials compared to collapsible fiducials, and wide variability to accurately detect fiducials across eight software settings. For any given setting, results were relatively reproducible and precise to ~0.5 mm. Across 17 patients treated with a median of 20 fractions, the software recommended a shift in 44% of fractions, and a shift was actually implemented after visual confirmation of movement greater than the 3 mm threshold in 20% of fractions. Adjustment of our approach led to improved accuracy for the latter (n = 7) patient subset. On average, table repositioning added 3.0 ± 0.3 min to patient time on table. Periodic kV imaging increased skin dose by an estimated 1 cGy per treatment arc. Conclusions: Periodic kV imaging with automatic detection of motion during VMAT prostate treatments is commercially available, and can be successfully implemented to mitigate effects of intrafraction motion with careful attention to software settings. [ABSTRACT FROM AUTHOR]

Purpose: To develop an Eclipse plug‐in (MLC_MODIFIER) that automatically modifies control points to expose fiducials obscured by MLC during VMAT, thereby facilitating tracking using periodic MV/kV imaging. Method: Three‐dimensional fiducial tracking was performed during VMAT by pairing short‐arc (3°) MV digital tomosynthesis (DTS) images to triggered kV images. To evaluate MLC_MODIFIER efficacy, two cohorts of patients were considered. For first 12 patients, plans were manually edited to expose one fiducial marker. Next for 15 patients, plans were modified using MLC_MODIFIER script. MLC_MODIFIER evaluated MLC apertures at appropriate angles for marker visibility. Angles subtended by control points were compressed and low‐dose "imaging" control points were inserted and exposed one marker with 1 cm margin. Patient's images were retrospectively reviewed to determine rate of MV registration failures. Failure categories were poor DTS image quality, MLC blockage of fiducials, or unknown reasons. Dosimetric differences in rectum, bladder, and urethra D1 cc, PTV maximum dose, and PTV dose homogeneity (PTV HI) were evaluated. Statistical significance was evaluated using Fisher's exact and Student's t test. Result: Overall MV registration failures, failures due to poor image quality, MLC blockage, and unknown reasons were 33% versus 8.9% (P < 0.0001), 8% versus 6.4% (P < 0.05), 13.6% versus 0.1% (P < 0.0001), and 7.6% versus 2.4% (P < 0.0001) for manually edited and MLC_MODIFIER plans, respectively. PTV maximum and HI increased on average from unmodified plans by 2.1% and 0.3% (P < 0.004) and 22.0% and 3.3% (P < 0.004) for manually edited and MLC_MODIFIED plans, respectively. Changes in bladder, rectum, and urethra D1CC were similar for each method and less than 0.7%. Conclusion: Increasing fiducial visibility via an automated process comprised of angular compression of control points and insertion of additional "imaging" control points is feasible. Degradation of plan quality is minimal. Fiducial detection and registration success rates are significantly improved compared to manually edited apertures. [ABSTRACT FROM AUTHOR]

Abstract: The use of stereotactic body radiation therapy is rapidly increasing among patients with lung cancer not amenable to surgery. The authors report their experience using the CyberKnife system (Accuray Inc., Sunnyvale, CA, USA) as a treatment option for synchronous cancer of oral squamous cell carcinoma and a malignant lung tumour. An 88-year-old woman with two cancers (oral and lung masses) underwent CyberKnife treatment, with fiducial gold pins implanted using bronchoscopy. Toxicity was limited, and at the 2-year follow-up the lesions had not recurred. [Copyright &y& Elsevier]

Objective: Our study aims to estimate intra-fraction six-dimensional (6D) tumor motion with rotational correction and the related correlations between motions of different degrees of freedom (DoF), as well as quantify sufficient anisotropic clinical target volume (CTV) to planning target volume (PTV) margins during stereotactic body radiotherapy (SBRT) of liver cancer with fiducial tracking technique., Methods: A cohort of 12 patients who were implanted with 3 or 4 golden markers were included in this study, and 495 orthogonal kilovoltage (kV) pairs of images acquired during the first fraction were used to extract the spacial position of each golden marker. Translational and rotational motions of tumor were calculated based on the marker coordinates by using an iterative closest point (ICP) algorithm. Moreover, the Pearson product-moment correlation coefficients ( r ) were applied to quantify the correlations between motions with different degrees of freedom (DoFs). The population mean displacement ( M P ¯ ), systematic error (Σ) and random error ( σ ) were obtained to calculate PTV margins based on published recipes., Results: The mean translational variability of tumors were 0.56, 1.24 and 3.38 mm in the left-right (LR, X ), anterior-posterior (AP, Y ), and superior-inferior (SI, Z ) directions, respectively. The average rotational angles θ X , θ Y and θ Z around the three coordinate axes were 0.88, 1.24 and 1.12, respectively. (| r |>0.4) was obtainted between Y - Z , Y - θ Z , Z - θ Z and θ X - θ Y . The PTV margins calculated based on 13 published recipes in X, Y, and Z directions were 1.08, 2.26 and 5.42 mm, and the 95% confidence interval (CI) of them were (0.88,1.28), (1.99,2.53) and (4.78,6.05), respectively., Conclusions: The maximum translational motion was in SI direction, and the largest correlation coefficient of Y - Z was obtained. We recommend margins of 2, 3 and 7 mm in LR, AP and SI directions, respectively., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sun, Dai, Xu, Guo, Su and Li.)

Fiducial tracking is a common target tracking method widely used in image-guided procedures such as radiotherapy and radiosurgery. In this paper, we present a multifiducial identification method that incorporates context information in the process. We first convert the problem into a state sequence problem by establishing a probabilistic framework based on a hidden Markov model (HMM), where prior probability represents an individual candidate's resemblance to a fiducial; transition probability quantifies the similarity of a candidate set to the fiducials' geometrical configuration; and the Viterbi algorithm provides an efficient solution. We then discuss the problem of identifying fiducials using stereo projections, and propose a special, higher order HMM, which consists of two parallel HMMs, connected by an association measure that captures the inherent correlation between the two projections. A novel algorithm, the concurrent viterbi with association (CVA) algorithm, is introduced to efficiently identify fiducials in the two projections simultaneously. This probabilistic framework is highly flexible and provides a buffer to accommodate deformations. A simple implementation of the CVA algorithm is presented to evaluate the efficacy of the framework. Experiments were carried out using clinical images acquired during patient treatments, and several examples are presented to illustrate a variety of clinical situations. In the experiments, the algorithm demonstrated a large tracking range, computational efficiency, ease of use, and robustness that meet the requirements for clinical use. [ABSTRACT FROM AUTHOR]

Intrafraction organ motion can limit the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT) due to target position uncertainty. To ensure high accuracy in beam targeting, real-time knowledge of the target location is highly desired throughout the beam delivery process. This knowledge can be gained through imaging of internally implanted radio-opaque markers with fluoroscopic or electronic portal imaging devices (EPID). In the case of MV based images, marker detection can be problematic due to the significantly lower contrast between different materials in comparison to their kV-based counterparts. This work presents a fully automated algorithm capable of detecting implanted metallic markers in both kV and MV images with high consistency. Using prior CT information, the algorithm predefines the volumetric search space without manual region-of-interest (ROI) selection by the user. Depending on the template selected, both spherical and cylindrical markers can be detected. Multiple markers can be simultaneously tracked without indexing confusion. Phantom studies show detection success rates of 100% for both kV and MV image data. In addition, application of the algorithm to real patient image data results in successful detection of all implanted markers for MV images. Near real-time operational speeds of ∼10 frames/sec for the detection of five markers in a 1024×768 image are accomplished using an ordinary PC workstation. [ABSTRACT FROM AUTHOR]