Erring Characteristics of Deformable Image Registration-Based Auto-Propagation for Internal Target Volume in Radiotherapy of Locally Advanced Non-Small Cell Lung Cancer.

Purpose: Respiratory motion of locally advanced non-small cell lung cancer (LA-NSCLC) adds to the challenge of targeting the disease with radiotherapy (RT). One technique used frequently to alleviate this challenge is an internal gross tumor volume (IGTV) generated from manual contours on a single respiratory phase of the 4DCT via the aid of deformable image registration (DIR)-based auto-propagation. Through assessing the accuracy of DIR-based auto-propagation for generating IGTVs, this study aimed to identify erring characteristics associated with the process to enhance RT targeting in LA-NSCLC. Methods: 4DCTs of 19 patients with LA-NSCLC were acquired using retrospective gating with 10 respiratory phases (RPs). Ground-truth IGTVs (GT-IGTVs) were obtained through manual segmentation and union of gross tumor volumes (GTVs) in all 10 phases. IGTV auto-propagation was carried out using two distinct DIR algorithms for the manually contoured GTV from each of the 10 phases, resulting in 10 separate IGTVs for each patient per each algorithm. Differences between the auto-propagated IGTVs (AP-IGTVs) and their corresponding GT-IGTVs were assessed using Dice coefficient (DICE), maximum symmetric surface distance (MSSD), average symmetric surface distance (ASSD), and percent volume difference (PVD) and further examined in relation to anatomical tumor location, RP, and deformation index (DI) that measures the degree of deformation during auto-propagation. Furthermore, dosimetric implications due to the analyzed differences between the AP-IGTVs and GT-IGTVs were assessed. Results: Findings were largely consistent between the two algorithms: DICE, MSSD, ASSD, and PVD showed no significant differences between the 10 RPs used for propagation (Kruskal-Wallis test, ps > 0.90); MSSD and ASSD differed significantly by tumor location in the central-peripheral and superior-inferior dimensions (ps < 0.0001) while only in the central-peripheral dimension for PVD (p < 0.001); DICE, MSSD, and ASSD significantly correlated with the DI (Spearman's rank correlation test, ps < 0.0001). Dosimetric assessment demonstrated that 79% of the radiotherapy plans created by targeting planning target volumes (PTVs) derived from the AP-IGTVs failed prescription constraints for their corresponding ground-truth PTVs. Conclusion: In LA-NSCLC, errors in DIR-based IGTV propagation present to varying degrees and manifest dependences on DI and anatomical tumor location, indicating the need for personalized consideration in designing RT internal target volume.

Automated planning stage tracking and analysis through an integrated whiteboard system.

PURPOSE: One of the common challenges in delivering complex healthcare procedures such as radiation oncology is the organization and sharing of information in ways that facilitate workflow and prevent treatment delays. Within the major vendors of Oncology Information Systems (OIS) is a lack of tools and displays to assist in task timing and workflow processes. To address this issue, we developed an electronic whiteboard integrated with a local OIS to track, record, and evaluate time frames associated with clinical radiation oncology treatment planning processes. METHODS: We developed software using an R environment hosted on a local web-server at Seattle Cancer Care Alliance (SCCA) in 2017. The planning process was divided into stages, and time-stamped moves between planning stages were recorded automatically via Mosaiq (Elekta, Sweden) Quality Check Lists (QCLs). Whiteboard logs were merged with Mosaiq-extracted diagnostic factors and evaluated for significance. Interventional changes to task time expectations were evaluated for 6 months in 2021 and compared with 6 month periods in 2018 and 2019. RESULTS: Whiteboard/Mosaiq data from the SCCA show that treatment intent, number of prescriptions, and nodal involvement were main factors influencing overall time to plan completion. Contouring and Planning times were improved by 2.6 days (p<10-14) and 2.5 days (p<10-11), respectively. Overall time to plan completion was reduced by 33% (5.1 days; p<10-11). CONCLUSIONS: This report establishes the utility of real-time task tracking tools in a radiotherapy planning process. The whiteboard results provide data-driven evidence to add justification for practice change implementations.

Simulation-based learning for enhanced gynecologic brachytherapy training among radiation oncology residents.

PURPOSE: Brachytherapy is an irreplaceable component of gynecologic cancer treatment. Resident training has declined, and procedural exposure is variable. We evaluated whether simulation-based gynecologic brachytherapy training among radiation oncology residents could improve knowledge, confidence, and interest. METHODS AND MATERIALS: Before a brachytherapy workshop, radiation oncology residents without prior gynecologic brachytherapy experience completed a survey on brachytherapy knowledge, procedural confidence, plan evaluation, and quality/safety. Residents then participated in a gynecologic brachytherapy workshop. Lectures covered brachytherapy imaging and physics principles/quality assurance, followed by hands-on and individualized feedback regarding applicator selection and placement, target segmentation, and physics quality assurance. Afterward, preworkshop questions were recollected. Descriptive statistics and Fisher's exact tests were used for data analysis. RESULTS: After the workshop, resident responses regarding the learning environment and baseline knowledge questions improved overall. There was a 30% improvement in favorable responses to the learning environment statement "My residency has a formal process/curriculum to teach brachytherapy" and for baseline knowledge the greatest improvement was seen for "I am familiar with the anatomy and placement of the applicators in relation to the anatomy". "Lack of didactic or procedural training exposure" was identified as the main reason for declining brachytherapy use. Initially, 1/8 residents correctly completed the knowledge questions, and after the workshop, 6/7 (p < 0.001) residents correctly completed the questions. CONCLUSIONS: Domain-specific knowledge, procedural confidence, and brachytherapy interest improved after a gynecologic brachytherapy workshop. Integrated didactic and simulation-based brachytherapy training may serve as a valuable learning tool to augment resident knowledge, introduce practical skills, and spark resident interest in brachytherapy.

Data for erring patterns in manual delineation of PET-imaged lung lesions.

The data presented in this article characterizes the erring patterns intrinsic to manual contouring of PET positive tumor targets in the lung from twelve quantitative agreement measuring metrics, with categories related respectively to spatial overlap, pair counting, information theory, distance, and volume. The data holds the potential for the formation of new hypotheses towards improving the accuracy and precision of manual delineation of PET positive lung targets for radiation therapy.

Characterizing a deformable registration algorithm for surface-guided breast radiotherapy.

PURPOSE: Surface-guided radiation therapy (SGRT) is a nonionizing imaging approach for patient setup guidance, intra-fraction monitoring, and automated breath-hold gating of radiation treatments. SGRT employs the premise that the external patient surface correlates to the internal anatomy, to infer the treatment isocenter position at time of treatment delivery. Deformations and posture variations are known to impact the correlation between external and internal anatomy. However, the degree, magnitude, and algorithm dependence of this impact are not intuitive and currently no methods exist to assess this relationship. The primary aim of this work was to develop a framework to investigate and understand how a commercial optical surface imaging system (C-RAD, Uppsala, Sweden), which uses a nonrigid registration algorithm, handles rotations and surface deformations. METHODS: A workflow consisting of a female torso phantom and software-introduced transformations to the corresponding digital reference surface was developed. To benchmark and validate the approach, known rigid translations and rotations were first applied. Relevant breast radiotherapy deformations related to breast size, hunching/arching back, distended/deflated abdomen, and an irregular surface to mimic a cover sheet over the lower part of the torso were investigated. The difference between rigid and deformed surfaces was evaluated as a function of isocenter location. RESULTS: For all introduced rigid body transformations, C-RAD computed isocenter shifts were determined within 1 mm and 1˚. Additional translational shifts to correct for rotations as a function of isocenter location were determined with the same accuracy. For yaw setup errors, the difference in shift corrections between a plan with an isocenter placed in the center of the breast (BrstIso) and one located 12 cm superiorly (SCFIso) was 2.3 mm/1˚ in lateral direction. Pitch setup errors resulted in a difference of 2.1 mm/1˚ in vertical direction. For some of the deformation scenarios, much larger differences up to 16 mm and 7˚ in the calculated shifts between BrstIso and SCFIso were observed that could lead to large unintended gaps or overlap between adjacent matched fields if uncorrected. CONCLUSIONS: The methodology developed lends itself well for quality assurance (QA) of SGRT systems. The deformable C-RAD algorithm determined accurate shifts for rigid transformations, and this was independent of isocenter location. For surface deformations, the position of the isocenter had considerable impact on the registration result. It is recommended to avoid off-axis isocenters during treatment planning to optimally utilize the capabilities of the deformable image registration algorithm, especially when multiple isocenters are used with fields that share a field edge.

Predictors of cardiac and lung dose sparing in DIBH for left breast treatment.

This retrospective study of left breast radiation therapy (RT) investigates the correlation between anatomical parameters and dose to heart or/and left lung in deep inspiration breath-hold (DIBH) compared to free-breathing (FB) technique. Anatomical parameters of sixty-seven patients, treated with a step-and-shoot technique to 50 Gy or 50.4 Gy were included. They consisted of the cardiac contact distances in axial (CCDax) and parasagittal (CCDps) planes, and the lateral heart-to-chest distance (HCD). Correlation analysis was performed to identify predictors for heart and lung dose sparing. Paired t-test and linear regression were used for data analysis with significance level of p = 0.05. All dose metrics for heart and lung were significantly reduced with DIBH, however 21% of patients analyzed had less than 1.0 Gy mean heart dose reduction. Both FB-CCDpsdistance and FB-HCD correlated with FB mean heart dose and mean DIBH heart dose reduction. The strongest correlation was observed for the ratio of FB-CCDpsand FB-HCD with heart dose sparing. A FB-CCDps and FB-HCD model was developed to predict DIBH induced mean heart dose reduction, with 1.04 Gy per unit of FB-CCDps/FB-HCD. Variation between predicted and actual mean heart dose reduction ranged from -0.6 Gy to 0.6 Gy. In this study, FB-CCDps and FB-HCD distance served as predictors for heart dose reduction with DIBH equally, with FB-CCDps/FB-HCD as a stronger predictor. These parameters and the prediction model could be further investigated for use as a tool to better select patients who will benefit from DIBH.

Quantitative imaging: Erring patterns in manual delineation of PET-imaged lung lesions.

BACKGROUND AND PURPOSE: Uncertainty and variability in manual contouring of PET-imaged tumor targets are well recognized; however, the error patterns associated with it were little known and rarely investigated. The present study is aimed to quantitatively assess the erring patterns inherent to manual delineation of PET-imaged lung lesions in a setting with complete ground truth. MATERIALS AND METHODS: Images being used for assessment consisted of 26 synthetic PET datasets created by using the anthropomorphic Zubal phantom in conjunction with the Monte Carlo based SimSET computational package. Each dataset included one PET-positive lesion differing in shape, dimension, uptake heterogeneity, and anatomical location inside the lung. Target contours were provided by 10 raters and the contour accuracy was evaluated using 12 metrics from five categories - spatial overlap, pair counting, information theory, distance, and volume. RESULTS: In terms of spatial overlap, manual contouring results intersect substantially with the ground truth whereas tend to oversegment the lesions. Shapes of the segmented tumor volumes are in general geometrically consistent with the ground truth but lack sensitivity in characterizing topographical details. No complete consensus could be achieved between manual contours and the ground truth for any of the given lesions being examined when assessing using pair counting- and informatics-based metrics thus indicating an intrinsic stochastic component of manual contouring. Evaluation based on metrics related to distance and volume demonstrated that it is at the borderline areas between the lesions and the normal tissues where the majority part of manual delineation errors occurred and the extent of volume being identified false positively as cancerous by the raters is appreciable. CONCLUSION: Quantification of segmentation errors associated with expert manual contouring of PET positive lesion in the lung reveals general patterns in what otherwise might be thought of as randomness. Findings from the current study may allow for the formation of new hypotheses towards improving the accuracy and precision of manual delineation of PET positive tumor targets in the lung.

Accuracy and stability of deep inspiration breath hold in gated breast radiotherapy - A comparison of two tracking and guidance systems.

PURPOSE: To characterize reproducibility of patient breath-hold positioning and compare tracking system performance for Deep Inspiration Breath Hold (DIBH) gated left breast radiotherapy. METHODS: 29 consecutive left breast DIBH patients (655 fractions) were treated under the guidance of Calypso surface beacons with audio-feedback and 35 consecutive patients (631 fractions) were treated using C-RAD Catalyst HD surface imaging with audiovisual feedback. The Calypso system tracks a centroid determined by two radio-frequency transponders, with a manually enforced institutional tolerance, while the surface image based CatalystHD system utilizes real-time biometric feedback to track a pre-selected point with an institutional tolerance enforced by the Elekta Response gating interface. DIBH motion data from Calypso was extracted to obtain the displacement of breath hold marker in ant/post direction from a set-zero reference point. Ant/post point displacement data from CatalystHD was interpreted by computing the difference between raw tracking points and the center of individual gating windows. Mean overall errors were compared using Welsh's unequal variance t-test. Wilcoxon rank sum test were used for statistical analysis with P < 0.05 considered significant. RESULTS: Mean overall error for Calypso and CatalystHD were 0.33 ±â€¯1.17 mm and 0.22 ±â€¯0.43 mm, respectively, with t-test comparison P-value < 0.034. Absolute errors for Calypso and CatalystHD were 0.95 ±â€¯0.75 mm and 0.38 ±â€¯0.30 mm, respectively, with Wilcoxon rank sum test P-value <2×10-16. Average standard deviation per fraction was found to be 0.74 ±â€¯0.44 mm for Calypso patients versus 0.54 ±â€¯0.22 mm for CatalystHD. CONCLUSION: Reduced error distribution widths in overall positioning, deviation of position, and per fraction deviation suggest that the use of functionalities available in CatalystHD such as audiovisual biofeedback and patient surface matching improves accuracy and stability during DIBH gated left breast radiotherapy.

Characterization of a Bayesian network-based radiotherapy plan verification model.

PURPOSE: The current process for radiotherapy treatment plan quality assurance relies on human inspection of treatment plans, which is time-consuming, error prone and oft reliant on inconsistently applied professional judgments. A previous proof-of-principle paper describes the use of a Bayesian network (BN) to aid in this process. This work studied how such a BN could be expanded and trained to better represent clinical practice. METHODS: We obtained 51 540 unique radiotherapy cases including diagnostic, prescription, plan/beam, and therapy setup factors from a de-identified Elekta oncology information system from the years 2010-2017 from a single institution. Using a knowledge base derived from clinical experience, factors were coordinated into a 29-node, 40-edge BN representing dependencies among the variables. Conditional probabilities were machine learned using expectation maximization module using all data except a subset of 500 patient cases withheld for testing. Different classes of errors that were obtained from incident learning systems were introduced to the testing set of cases which were withheld from the dataset used for building the BN. Different sizes of datasets were used to train the network. In addition, the BN was trained using data from different length epochs as well as different eras. Its performance under these different conditions was evaluated by means of Areas Under the receiver operating characteristic Curve (AUC). RESULTS: Our performance analysis found AUCs of 0.82, 0.85, 0.89, and 0.88 in networks trained with 2-yr, 3-yr 4-yr and 5-yr windows. With a 4-yr sliding window, we found AUC reduction of 3% per year when moving the window back in time in 1-yr steps. Compared to the 4-yr window moved back by 4 yrs (2010-2013 vs 2014-2017), the largest component of overall reduction in AUC over time was from the loss of detection performance in plan/beam error types. CONCLUSIONS: The expanded BN method demonstrates the ability to detect classes of errors commonly encountered in radiotherapy planning. The results suggest that a 4-yr training dataset optimizes the performance of the network in this institutional dataset, and that yearly updates are sufficient to capture the evolution of clinical practice and maintain fidelity.

Dosimetric effects of bolus and lens shielding in treating ocular lymphomas with low-energy electrons.

Radiation therapy is an effective treatment for primary orbital lymphomas. Lens shielding with electrons can reduce the risk of high-grade cataracts in patients undergoing treatment for superficial tumors. This work evaluates the dosimetric effects of a suspended eye shield, placement of bolus, and varying electron energies. Film (GafChromic EBT3) dosimetry and relative output factors were measured for 6, 8, and 10 MeV electron energies. A customized 5-cm diameter circle electron orbital cutout was constructed for a 6 × 6-cm applicator with a suspended lens shield (8-mm diameter Cerrobend cylinder, 2.2-cm length). Point doses were measured using a scanning electron diode in a solid water phantom at depths representative of the anterior and posterior lens. Depth dose profiles were compared for 0-mm, 3-mm, and 5-mm bolus thicknesses. At 5 mm (the approximate distance of the anterior lens from the surface of the cornea), the percent depth dose under the suspended lens shield was reduced to 15%, 15%, and 14% for electron energies 6, 8, and 10 MeV, respectively. Applying bolus reduced the benefit of lens shielding by increasing the estimated doses under the block to 27% for 3-mm and 44% for 5-mm bolus for a 6 MeV incident electron beam. This effect is minimized with 8 MeV electron beams where the corresponding values were 15.5% and 18% for 3-mm and 5-mm bolus. Introduction of a 7-mm hole in 5-mm bolus to stabilize eye motion during treatment altered lens doses by about 1%. Careful selection of electron energy and consideration of bolus effects are needed to account for electron scatter under a lens shield.

Aggressive behaviour risk assessment tool for long-term care (ABRAT-L): Validation study.

This prospective cohort study was conducted to validate the usefulness of the Aggressive Behaviour Risk Assessment Tool for Long-Term Care (ABRAT-L) in predicting aggressive events. A total of 615 newly admitted residents at 22 long-term care homes in Canada were included. The risk of aggression was assessed using the six-item ABRAT-L within 24 hours of admission, and incident reports of aggressive events occurring within 30 days of admission were collected. Forty-seven residents out of 615 had one or more aggressive events (7.6%). The receiver operating characteristics analysis of ABRAT-L showed a good discriminant ability at the previously recommended cut-off score of 4, with satisfactory sensitivity and specificity. The usefulness of ABRAT-L in identifying potentially aggressive residents at the time of admission was confirmed. This validation study supports the adoption of a proactive risk assessment tool, ABRAT-L, as a part of routine admission assessments at long-term care homes.

Quantitative radiomics: Validating image textural features for oncological PET in lung cancer.

BACKGROUND AND PURPOSE: Radiomics textural features derived from PET imaging are of broad and current interest due to recent evidence of their prognostic value during cancer management. An inherent assumption is the link between these imaging features and the underlying tumoral phenotypic spatial heterogeneity. The purpose of this work was to validate this assumption for tumors within the lung through a comparison of image based textural features and the ground truth activity distribution from which the images were created. A second purpose was to assess the level at which PET imaging introduces spatial texture not present in the associated ground truth activity distribution. MATERIALS AND METHODS: 25 lung lesions were created using an anthropomorphic phantom. Ten of the lesions had a spherical shape with a uniform activity distribution. The remaining 15 had an irregular shape with a heterogeneous activity distribution. PET images were created for each lesion using Monte Carlo simulation. 79 textural features related to the gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, run length, and size zone matrices were derived from both the simulated PET images and ground truth activity maps. A comparison was made between the two datasets using statistical analysis. RESULTS: For homogenous lesions, features extracted from the PET images were largely irrelevant to the underlying uniform activity distribution. Additionally, the majority of these features assumed substantial values implying that an extensive amount of spatial texture had been introduced into the final imaging data. For heterogeneous lesions, complex trends were observed in the deviation between features extracted from PET images and those extracted from the ground truth activity maps. Moreover, the extent of both the deviation and the associated dynamic range was seen to be greatly feature-dependent. CONCLUSION: The use of image based textural features as a surrogate for tumoral phenotypic spatial heterogeneity could not be clearly validated. The association between the two is complex and a significant amount of uncertainty exist due to the introduction of incidental texture during image acquisition and reconstruction.

Utilizing simulated errors in radiotherapy plans to quantify the effectiveness of the physics plan review.

PURPOSE: The review of a radiation therapy plan by a physicist prior to treatment is a standard tool for ensuring the quality of treatments. However, little is known about how well this task is performed in practice. The goal of this study is to present a novel method to measure the effectiveness of physics plan review by introducing simulated errors into computerized "mock" treatment charts and measuring the performance of plan review by physicists. METHODS: We generated six simulated treatment charts containing multiple errors. To select errors, we compiled a list based on events from a departmental incident learning system and an international incident learning system (SAFRON). Seventeen errors with the highest scores for frequency and severity were included in the simulations included six mock treatment charts. Eight physicists reviewed the simulated charts as they would a normal pretreatment plan review, with each chart being reviewed by at least six physicists. There were 113 data points for evaluation. Observer bias was minimized using a simple error vs hidden error approach, using detectability scores for stratification. The confidence interval for the proportion of errors detected was computed using the Wilson score interval. RESULTS: Simulated errors were detected in 67% of reviews [58-75%] (95% confidence interval [CI] in brackets). Of the errors included in the simulated plans, the following error scenarios had the highest detection rates: an incorrect isocenter in DRR (93% [70-99%]), a planned dose different from the prescribed dose (92% [67-99%]) and invalid QA (85% [58-96%]). Errors with low detection rates included incorrect CT dataset (0%, [0-39%]) and incorrect isocenter localization in planning system (38% [18-64%]). Detection rates of errors from simulated charts were compared against observed detection rates of errors from a departmental incident learning system. CONCLUSIONS: It has been notoriously difficult to quantify error and safety performance in oncology. This study uses a novel technique of simulated errors to quantify performance and suggests that the pretreatment physics plan review identifies some errors with high fidelity while other errors are more challenging to detect. These data will guide future work on standardization and automation. The example process studied here was physics plan review, but this approach of simulated errors may be applied in other contexts as well and may also be useful for training and education purposes.

Quantitative Radiomics: Impact of Pulse Sequence Parameter Selection on MRI-Based Textural Features of the Brain.

Objectives: Radiomic features extracted from diverse MRI modalities have been investigated regarding their predictive and/or prognostic value in a variety of cancers. With the aid of a 3D realistic digital MRI phantom of the brain, the aim of this study was to examine the impact of pulse sequence parameter selection on MRI-based textural parameters of the brain. Methods: MR images of the employed digital phantom were realized with SimuBloch, a simulation package made for fast generation of image sequences based on the Bloch equations. Pulse sequences being investigated consisted of spin echo (SE), gradient echo (GRE), spoiled gradient echo (SP-GRE), inversion recovery spin echo (IR-SE), and inversion recovery gradient echo (IR-GRE). Twenty-nine radiomic textural features related, respectively, to gray-level intensity histograms (GLIH), cooccurrence matrices (GLCOM), zone size matrices (GLZSM), and neighborhood difference matrices (GLNDM) were evaluated for the obtained MR realizations, and differences were identified. Results: It was found that radiomic features vary considerably among images generated by the five different T1-weighted pulse sequences, and the deviations from those measured on the T1 map vary among features, from a few percent to over 100%. Radiomic features extracted from T1-weighted spin-echo images with TR varying from 360 ms to 620 ms and TE = 3.4 ms showed coefficients of variation (CV) up to 45%, while up to 70%, for T2-weighted spin-echo images with TE varying over the range 60-120 ms and TR = 6400 ms. Conclusion: Variability of radiologic textural appearance on MR realizations with respect to the choice of pulse sequence and imaging parameters is feature-dependent and can be substantial. It calls for caution in employing MRI-derived radiomic features especially when pooling imaging data from multiple institutions with intention of correlating with clinical endpoints.

Clinical Positioning Accuracy for Multisession Stereotactic Radiotherapy With the Gamma Knife Perfexion.

Multisession stereotactic radiation therapy is increasingly being seen as a preferred option for intracranial diseases in close proximity to critical structures and for larger target volumes. The objective of this study is to investigate the reproducibility of the Extend system from Elekta. A retrospective review was conducted for all patients treated with multisession Gamma Knife between July 2010 and June 2015, including both malignant and benign lesions. Eighty-four patients were treated in this 5-year span. The average residual daily setup uncertainty was 0.48 (0.19) mm. We compare measurements of setup uncertainty from the Extend system to measurements performed with a linac-based approach previously used in our center. The Extend system has significantly reduced setup uncertainty for fractionated intracranial treatments at our institution. Positive results were observed in a small population of edentulous patients. The Extend system compares favorably with other approaches to delivering intracranial stereotactic radiotherapy and is a robust, simple-to-use, and precise method for treating multisession intracranial lesions.

Quantitative imaging: Correlating image features with the segmentation accuracy of PET based tumor contours in the lung.

The purpose of this study was to investigate the correlation between image features extracted from PET images and the accuracy of manually drawn lesion contours in the lung. Such correlations are interesting in that they could potentially be used in predictive models to help guide physician contouring. In this work, 26 synthetic PET datasets were created using an anthropomorphic phantom and Monte Carlo simulation. Manual contours of simulated lesions were provided by 10 physicians. Contour accuracy was quantified using five commonly used similarity metrics which were then correlated with several features extracted from the images. Features were sub-divided into three groups using intensity, geometry, and texture as categorical descriptors. When averaged among the participants, the results showed relatively strong correlations with complexity and contrastI (r≥0.65, p<0.001), and moderate correlations with several other image features (r≥0.5, p<0.01). The predictive nature of these correlations was improved through stepwise regression and the creation of multi-feature models. Imaging features were also correlated with the standard deviation of contouring error in order to investigate inter-observer variability. Several features were consistently identified as influential including integral of mean curvature and complexity. These relationships further the understanding as to what causes variation in the contouring of PET positive lesions.

Utility of the Aggressive Behavior Risk Assessment Tool in long-term care homes.

This study was conducted to determine the utility of the Aggressive Behavior Risk Assessment Tool (ABRAT) and the Aggressive Behavior Scale (ABS) for predicting aggressive incidents among newly-admitted and existing residents of two long-term care homes in Canada. Of 316 residents, 27 had at least one aggressive incident (8.5%). Receiver operating characteristics analysis showed that the area under the curve for the ABRAT was 0.86 (95% Confidence Interval [CI], 0.81-0.92) and that for the ABS was 0.75 (95% CI, 0.64-0.85). Sensitivity and specificity at the optimal cutoff score of 2 for the ABRAT were 96.3% and 65.4%, respectively, and those for the ABS at the optimal cutoff score of 3 were 59.3% and 80.6%, respectively. The ABRAT appears to be promising for use in long-term care homes for identifying potentially aggressive residents. However, further studies are needed to test the utility of the ABRAT among newly-admitted residents.

Aggressive Behaviour Risk Assessment Tool for newly admitted residents of long-term care homes.

AIM: The aim of this study was to revise the 10-item Aggressive Behaviour Risk Assessment Tool for predicting aggressive events among residents newly admitted to long-term care homes. BACKGROUND: The original tool had acceptable sensitivity and specificity for identifying potentially aggressive patients in acute care medical-surgical units, but its usefulness in long-term care homes is unknown. DESIGN: A retrospective cohort study design was used. METHODS: All residents admitted to 25 long-term care homes in western Canada were assessed for the risk of aggression using the original tool within 24 hours of admission from January 2014 - December 2014 (n = 724). Incident reports of aggressive events occurring within 30 days of admission were collected. Multiple logistic regression and receiver operating characteristics analyses were performed. RESULTS: Fifty-three residents of 724 exhibited aggressive behaviours. The demographic variable of age less than 85 years was found to be a positive predictor of aggressive events in multivariate logistic regression model and was added to the tool. The revised six-item Aggressive Behaviour Risk Assessment Tool for Long-Term Care consists of one new item, age less than 85 years and five items from the original tool: History of physical aggression, physically aggressive/threatening, anxiety, confusion/cognitive impairment and threatening to leave. The receiver operating characteristics of the revised tool with weighted scoring showed a good discriminant ability with satisfactory sensitivity and specificity at the recommended cut-off score of 4. CONCLUSION: The revised six-item tool may be useful in identifying potentially aggressive residents newly admitted to long-term care homes.

Rounded leaf end modeling in Pinnacle VMAT treatment planning for fixed jaw linacs.

During volume-modulated arc therapies (VMAT), dosimetric errors are introduced by multiple open dynamic leaf gaps that are present in fixed diaphragm linear accelerators. The purpose of this work was to develop a methodology for adjusting the rounded leaf end modeling parameters to improve out-of-field dose agreement in SmartArc VMAT treatment plans delivered by fixed jaw linacs where leaf gap dose is not negligible. Leaf gap doses were measured for an Elekta beam modulator linac with 0.4 cm micro-multileaf collimators (MLC) using an A16 micro-ionization chamber, a MatriXX ion chamber detector array, and Kodak EDR2 film dosimetry in a solid water phantom. The MLC offset and rounded end tip radius were adjusted in the Pinnacle treatment planning system (TPS) to iteratively arrive at the optimal configuration for 6 MV and 10 MV photon energies. Improvements in gamma index with a 3%/3 mm acceptance criteria and an inclusion threshold of 5% of maximum dose were measured, analyzed, and validated using an ArcCHECK diode detector array for field sizes ranging from 1.6 to 14 cm square field arcs and Task Group (TG) 119 VMAT test cases. The best results were achieved for a rounded leaf tip radius of 13 cm with a 0.1 cm MLC offset. With the optimized MLC model, measured gamma indices ranged between 99.9% and 91.7% for square field arcs with sizes between 3.6 cm and 1.6 cm, with a maximum improvement of 42.7% for the 1.6 cm square field size. Gamma indices improved up to 2.8% in TG-119 VMAT treatment plans. Imaging and Radiation Oncology Core (IROC) credentialing of a VMAT plan with the head and neck phantom passed with a gamma index of 100%. Fine-tune adjustments to MLC rounded leaf ends may improve patient-specific QA pass rates and provide more accurate predictions of dose deposition to avoidance structures.

Electron beam energy QA - a note on measurement tolerances.

Monthly QA is recommended to verify the constancy of high-energy electron beams generated for clinical use by linear accelerators. The tolerances are defined as 2%/2 mm in beam penetration according to AAPM task group report 142. The practical implementation is typically achieved by measuring the ratio of readings at two different depths, preferably near the depth of maximum dose and at the depth corresponding to half the dose maximum. Based on beam commissioning data, we show that the relationship between the ranges of energy ratios for different electron energies is highly nonlinear. We provide a formalism that translates measurement deviations in the reference ratios into change in beam penetration for electron energies for six Elekta (6-18 MeV) and eight Varian (6-22 MeV) electron beams. Experimental checks were conducted for each Elekta energy to compare calculated values with measurements, and it was shown that they are in agreement. For example, for a 6 MeV beam a deviation in the measured ionization ratio of ± 15% might still be acceptable (i.e., be within ± 2 mm), whereas for an 18 MeV beam the corresponding tolerance might be ± 6%. These values strongly depend on the initial ratio chosen. In summary, the relationship between differences of the ionization ratio and the corresponding beam energy are derived. The findings can be translated into acceptable tolerance values for monthly QA of electron beam energies.