Journal of Applied Clinical Medical Physics最新文献

Purpose: This study aimed to evaluate the impact of collimator angle, ball bearing (BB) phantom position, and field size on the accuracy of Winston-Lutz (WL) test-derived radiation isocenters.

Methods: WL tests were performed on four TrueBeam linear accelerators. Fifty-six images (eight gantry angles multiplied by seven collimator angles) were acquired for each WL test. Images with different sets of collimator angles were used to compute the radiation isocenters. The resulting radiation isocenters were correlated with the collimator angles. Then, the BB position and radiation field size were varied for the subsequent WL tests. The calculated BB shifts were compared with the known shifts, and the radiation isocenters were compared between different field sizes.

Results: The use of a single collimator angle led to errors of as much as 0.4 mm in the calculated radiation isocenters. Systematic differences were observed between the radiation isocenters derived with collimator angle 0° and those derived with 90° and/or 270°. A commonly used opposing collimator angle pair, 90° and 270°, resulted in a vertical 0.1 mm offset of the radiation isocenters toward the ceiling. Oblique opposite or mixed collimator angles yielded radiation isocenter errors less than 0.1 mm. The BB shifts derived from WL tests were less than 0.1 mm from the known shifts. The radiation isocenters varied by less than 0.1 mm between field sizes ranging from 2 × 2 cm² to 20 × 20 cm².

Conclusions: Oblique opposing collimator angle pairs should be considered to minimize errors in localizing radiation isocenters. Uncertainty in BB positioning could be eliminated if the BB is used as a static reference point in space. The field size had no significant effect on the radiation isocenters. With careful design of WL test parameters and image processing, it is possible to achieve a precision of 0.1 mm in localizing radiation isocenters using WL tests.

This review article aims to provide an overview of accident models and incident analysis techniques in the context of radiation oncology. Accident models conceptualize the mechanisms through which accidents occur. Chain-of-event models and systemic models are two main categories of accident models and differ in how accident causation is portrayed. Chain-of-event models focus on the linear sequence of events leading up to an accident, whereas systemic models emphasize the nonlinear relationships between the components in a complex system. The article then introduces various incident analysis techniques, including root cause analysis (RCA), London Protocol, AcciMap, and Causal Analysis Based on Systems Theory (CAST), which are based on these accident models.  The techniques based on the chain-of-event model can be effective in identifying causal factors, safety interventions, and improving safety.  The other techniques based on the systemic models inherently facilitate an examination of how the influence of personal conditions, environmental conditions, and information exchange between different aspects of a system contributed to an accident.  To improve incident analysis, it is essential to translate unsafe human behavior into decision-making flaws and the underlying contextual factors. Where resources allow, it is also crucial to systematically link frontline contributions to organizational and societal aspects of the system and incorporate expertise in safety science and human factors into the analysis team.  The article also touches on related concepts such as Perrow's Normal Accident Theory (NAT), Functional Resonance Analysis Method (FRAM), and Bowtie Analysis, which are not based on specific accident models but have been used for safety improvement in radiation oncology. Overall, different incident analysis techniques have strengths and weaknesses. Taking a systems approach to incident analysis requires a shift from linear thinking to a more nuanced understanding of complex systems. However, the approach also brings unique value and can help improve safety as radiation oncology further gains complexity.

Background: Accurate delineation of organs at risk (OARs) is crucial yet time-consuming in the radiotherapy treatment planning workflow. Modern artificial intelligence (AI) technologies had made automation of OAR contouring feasible. This report details a single institution's experience in evaluating two commercial auto-contouring software tools and making well-informed decisions about their clinical adoption.

Methods: A cohort of 36 patients previously treated at our institution were selected for the software performance assessment. Fifty-eight OAR structures from seven disease sites were automatically segmented with each tool. Five radiation oncologists with different specialties qualitatively scored the automatic OAR contours' clinical usability by a 4-level scale (0-3), termed as quality score (QS), representing from "0: not usable" to "3: directly usable for a clinic." Additionally, quantitative comparison with clinically approved contours using Dice similarity coefficient (DSC) and the 95% Hausdorff distance (HD95) was performed in complement to QS from physicians.

Result: Software A achieved an average QS of 2.17 ± 0.69, comparable to Software B's average QS of 2.17 ± 0.72. Software B performed better with more OARs (42 vs. 37) that required minor or no modification than Software A. Major modifications were needed for 13 out of 58 automated contours from both tools. Both DSC and HD95 scores for the two tools were comparable to each other, with DSC: 0.67 ± 0.23 versus 0.66 ± 0.21 and HD95: 13.07 ± 15.84 versus 15.55 ± 18.45 for Software A and Software B, respectively. Correlation coefficients between the physician score and the quantitative metrics suggested that the contouring results from Software A aligned more closely with the physician's evaluations.

Conclusion: Based on our study, either software tool could produce clinically acceptable contours for about 65% of the OAR structures. However, further refinement is necessary for several challenging OARs to improve model performance.

Background: Various methods exist to correct for intrafraction motion (IFM) of the prostate during radiotherapy. We sought to characterize setup corrections in our practice informed by the TrueBeam Advanced imaging package, and analyze factors associated with IFM.

Methods: 132 men received radiation therapy for prostate cancer with a volumetric modulated arc therapy technique. All patients underwent planning CT immediately following transrectal placement of 3 fiducial markers. The most common RT course was 20 fractions (range: 17-44). Triggered kV images were acquired every 15 seconds over 2-3 full arcs using an onboard imaging system. IFM correction was considered when if any two fiducial markers in a single kV image were observed to be outside beyond a 3 mm tolerance margin. A manual 2D/3D match was performed using the fiducial markers from the single triggered kV image to obtain a suggested couch shift. Shift data for three (x, y, z) planes were extracted from the record and verify system and expressed as a single 3-dimensional translation. Shift percent (SP) was defined as the number of instances of an intrafraction correction divided by the total number of fractions for a given patient.

Results: Over 2659 fractions of radiation, IFM was observed and corrected for 582 times across 463 (17%) fractions, and at least one shift was made over the course of treatment in 77% of men. Univariate analysis revealed that larger rectal volume or width, smaller prostate volume, and use of ADT were associated with SP > 20% (p < 0.05). Men with a rectal width >3.6 cm were more likely to have IFM corrected (SP > 20% 47% vs 18%, p = 0.0016). On multivariate analysis, only rectal volume and width were associated with IFM.

Conclusions: In this cohort study, 17% of fractions were interrupted to apply at least one couch shift. Men treated with shorter courses of therapy, such as stereotactic body radiation therapy, or men at high risk for IFM (e.g. larger rectal size) may warrant more careful consideration regarding the implications of IFM.

Introduction: This paper describes a method to improve gantry-dependent beam steering for Elekta traveling wave linear accelerators by applying the measured and filtered beam servo corrections to the existing lookup table (LUT). Beam steering has a direct influence on the treatment accuracy by affecting the beam symmetry and position. The presented method provides an improved LUT with respect to the default Elekta method to reduce treatment delivery interruptions. These interruptions are known to contribute to unwanted intrafraction motion and longer treatment times.

Methods: Compared to the default method of the manufacturer, this new method takes both clockwise and counterclockwise rotation to compensate for magnetic hysteresis as well as previous configuration and noise filtering into account. The improved method to determine the lookup table uses service graphing information from the linac without the need for additional symmetry information. The clinical configuration of the flattened beam energies remains untouched during the data record.

Results: This method results in a configuration where the gantry-dependent steering is optimized over the full arc with optimal balance in the hysteresis and minimizing the effect of errors in the steering values. This method is a less error-prone process compared to the methodology described in previous research, still achieving a reduction of interruption of about 60 percent compared to the Elekta method.

Conclusion: This study shows a simplified way to optimize linac stability with improved LUT. The optimized LUT results in a lower number of interruptions, preventing downtime, and a lower risk of intrafraction motion due to longer treatment time.

Background: Conventional approaches for emergent or expedited palliative radiotherapy (RT) involve the application of cumbersome vendor-provided solutions and/or multiple patient appointments to complete the RT workflow within a compressed timeframe.

Purpose: This report delineates the clinical development of an in-house, semi-automated Cone-beam computed tomography (CBCT)-based simulation-free platform for expedited palliative RT on conventional linacs, intended to supplant existing techniques employed at this institution.

Methods: The internal software, termed SimFree Wizard (SFW), was engineered utilizing a C#-based application programming interface integrated within the treatment planning system (TPS). Generated scripts were compiled as stand-alone executables, with a graphical user interface (GUI) customized via an integrated development environment. The platform was conceived as a framework for accelerated CBCT-based RT, bypassing the requirement for standard simulation imaging. SFW employs full automation where feasible to minimize user intervention, supplemented by graphical instructions for tasks requiring manual execution. During development, relevant temporal metrics from 10 end-to-end tests for palliative spine RT were quantified. User feedback was solicited via a simple questionnaire assessing the overall platform usability. Automated in-house secondary verification software was developed for validation of the TPS-calculated monitor units (MUs).

Results: The mean duration for workflow execution was 41:42 ± 3:18 [mm:ss] (range ∼37-46 min). SFW satisfactorily generated simple, multi-field CBCT-based 3D treatment plans within seconds following delineation of the desired treatment area. User feedback indicated enhanced usability compared to previously employed solutions. Validation of the secondary verification software demonstrated accurate results for palliative spine RT and other simple cases wherein the dose calculation point resides in a predominantly homogenous medium.

Conclusion: A novel in-house solution for expedited CBCT-based RT was successfully developed, facilitating completion of the entire workflow within approximately 1-hour or less for simple palliative/emergent scenarios. Overall, this application is expected to improve the quality and safety of palliative RT while greatly reducing workflow duration, thereby improving access to palliative care.