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PurposeThe quality of medical physics education is heterogenous across training programs, despite its importance in radiation oncology (RO) residency training. We present the results of a pilot series of free high-yield physics educational videos covering 4 topics chosen from the American Society for Radiation Oncology core curriculum.Methods and materialsScripting and storyboarding of videos were iterative processes performed by 2 ROs and 6 medical physicists, with animations created by a university broadcasting specialist. Current RO residents and those who had graduated after 2018 were recruited through social media and e-mail with an aim of 60 participants. Two validated surveys were adapted for use and were completed after each video as well as a final overall assessment. Content was released sequentially after completion of the survey instruments for each prior video. All videos were created and released within 1 year of project initiation with a duration of 9 to 11 minutes.ResultsThere were 169 enrollees for the pilot from across the world, 211% of the targeted cohort size. Of these, 154 met eligibility criteria and received the first video. One hundred eight enrollees initiated the series and 85 completed the pilot, resulting in a 78% completion rate. Participants reported improved understanding and confidence applying the knowledge learned in the videos (median score 4 out of 5). All participants reported that the use of graphic animation improved understanding across all videos. Ninety-three percent agreed with a need for additional resources geared specifically toward RO residents and 100% would recommend these videos to other residents. Use metrics revealed the average watch time was 7 minutes (range, 6:17-7:15).ConclusionsThe high-yield educational physics video pilot series was successful in developing videos that were effective in teaching RO physics concepts.

Objective. To lay the foundation for automated knowledge-based brachytherapy treatment planning using 3D dose estimations, we describe an optimization framework to convert brachytherapy dose distributions directly into dwell times (DTs).Approach. A dose rate kernelḋ(r,θ,φ)was produced by exporting 3D dose for one dwell position from the treatment planning system and normalizing by DT. By translating and rotating this kernel to each dwell position, scaling by DT and summing over all dwell positions, dose was computed (Dcalc). We used a Python-coded COBYLA optimizer to iteratively determine the DTs that minimize the mean squared error betweenDcalcand reference doseDref, computed using voxels withDref80%-120% of prescription. As validation of the optimization, we showed that the optimizer replicates clinical plans whenDref= clinical dose in 40 patients treated with tandem-and-ovoid (T&O) or tandem-and-ring (T&R) and 0-3 needles. Then we demonstrated automated planning in 10 T&O usingDref= dose predicted from a convolutional neural network developed in past work. Validation and automated plans were compared to clinical plans using mean absolute differences (MAD=1N∑n=1Nabsxn-xn) over all voxels (xn= Dose,N= #voxels) and DTs (xn= DT,N= #dwell positions), mean differences (MD) in organD2ccand high-risk CTV D90 over all patients (where positive indicates higher clinical dose), and mean Dice similarity coefficients (DSC) for 100% isodose contours.Main results. Validation plans agreed well with clinical plans (MADdose= 1.1%, MADDT= 4 s or 0.8% of total plan time,D2ccMD = -0.2% to 0.2% and D90 MD = -0.6%, DSC = 0.99). For automated plans, MADdose= 6.5% and MADDT= 10.3 s (2.1%). The slightly higher clinical metrics in automated plans (D2ccMD = -3.8% to 1.3% and D90 MD = -5.1%) were due to higher neural network dose predictions. The overall shape of the automated dose distributions were similar to clinical doses (DSC = 0.91).Significance. Automated planning with 3D dose predictions could provide significant time savings and standardize treatment planning across practitioners, regardless of experience.

PurposeIn the U.S., the percentage of youth in need of evidence-based mental health practices (EBPs) who receive them (i.e., coverage rate) is low. We know little about what influences coverage rates. In 2010, the Los Angeles County Department of Mental Health (LACDMH) launched a reimbursement-driven implementation of multiple EBPs in youth mental health care. This study examines two questions: (1) What was the coverage rate of EBPs delivered three years following initial implementation? (2) What factors are associated with the coverage rates?MethodsTo assess coverage rates of publicly insured youth, we used LACDMH administrative claims data from July 1, 2013 to June 30, 2014 and estimates of the size of the targeted eligible youth population from the 2014 American Community Survey (ACS). The unit of analysis was clinic service areas (n = 254). We used Geographic Information Systems and an OLS regression to assess community and clinic characteristics related to coverage.ResultsThe county coverage rate was estimated at 17%, much higher than national estimates. The proportion of ethnic minorities, individuals who are foreign-born, adults with a college degree within a geographic area were negatively associated with clinic service area coverage rates. Having more therapists who speak a language other than English, providing care outside of clinics, and higher proportion of households without a car were associated with higher coverage rates.ConclusionHeterogeneity in municipal mental health record type and availability makes it difficult to compare the LACDMH coverage rate with other efforts. However, the LACDMH initiative has higher coverage than published national rates. Having bilingual therapists and providing services outside the clinic was associated with higher coverage. Even with higher coverage, inequities persisted.

PurposeThe Federal Aviation Administration quantifies hazardous attitudes (HAs) among pilots using a scale. HAs have been linked to aviation risk. We assessed the influence of HAs and other factors in treatment decision making in radiation oncology (RO).Methods and materialsAn anonymous survey was sent to 809 radiation oncologists in US cities housing the top 25 cancer centers. The survey included an HA scale adapted for RO and presented 9 cases assessing risk-tolerant radiation therapy prescribing habits and compliance with the American Society for Radiation Oncology's Choosing Wisely recommendations. Demographic and treatment decision data were dichotomized to identify factors associated with prescribing habits using univariable and multivariable (MVA) logistic regression analyses.ResultsA total of 139 responses (17.1%) were received, and 103 were eligible for analysis. Among respondents, 40% were female, ages were evenly distributed, and 83% were in academics. Median scores for all attitudes (macho, anti-authority, worry, resignation, and impulsivity) were below the aviation thresholds for hazard and data from surgical specialties. On MVA, responders >50 years old with >5 years' experience were 4.45 times more likely to recommend risk-tolerant radiation (P = .016). Macho attitude was negatively associated with Choosing Wisely compliant treatments (odds ratio [OR], 0.12; P = .001). Physicians who reported having previously retreated the supraclavicular fossa without complication were more likely to recommend retreatment in medically unfit patients if they felt the complication was avoided owing to careful planning (OR, 5.2; P = .008).ConclusionsTo our knowledge, this represents the first study analyzing physician attitudes in RO and their effect on self-reported treatment decisions. This work suggests that attitude may be among the factors that influence risk-tolerant prescribing practices and compliance with Choosing Wisely recommendations.

Substantial efforts have been dedicated to understanding, assessing, and managing suicide risk in youth broadly. However, little attention has been focused specifically on autistic youth and youth with intellectual disability. Because emergency departments are an essential point of suicide-related care, we used the National Emergency Department Sample databases to explore differences in prevalence of U.S. emergency department visits with a suicidal ideation or intentional self-inflicted injury ICD-9 diagnostic code by autistic youth, youth with intellectual disability, and youth without these diagnoses (i.e. the comparison group). Emergency department visits with a suicidal ideation or intentional self-inflicted injury diagnosis were more prevalent in autistic youth (5.1%) and youth with intellectual disability (6.6%) than in the comparison group (1.2%). Similar results were found when examining visits with a suicidal ideation diagnosis and with an intentional self-inflicted injury diagnosis separately. Prevalence of these emergency department visits increased more from 2006 to 2014 in autistic youth and in youth with intellectual disability than in the comparison group and were correlated with common and distinct sociodemographic and clinical factors across groups. Results suggest autistic youth and youth with intellectual disability may be uniquely vulnerable to suicide risk, highlighting the urgency of addressing suicidality and self-harm in these groups, particularly within emergency department settings.

PurposeThe use of interstitial needles, combined with intracavitary applicators, enables customized dose distributions and is beneficial for complex cases, but increases procedure time. Overall, applicator selection is not standardized and depends on physician expertise and preference. The purpose of this study is to determine whether dose prediction models can guide needle supplementation decision-making for cervical cancer.Materials and methodsIntracavitary knowledge-based models for organ-at-risk (OAR) dose estimation were trained and validated for tandem-and-ring/ovoids (T&R/T&O) implants. Models were applied to hybrid cases with 1-3 implanted needles to predict OAR dose without needles. As a reference, 70/67 hybrid T&R/T&O cases were replanned without needles, following a standardized procedure guided by dose predictions. If a replanned dose exceeded the dose objective, the case was categorized as requiring needles. Receiver operating characteristic (ROC) curves of needle classification accuracy were generated. Optimal classification thresholds were determined from the Youden Index.ResultsNeedle supplementation reduced dose to OARs. However, 67%/39% of replans for T&R/T&O met all dose constraints without needles. The ROC for T&R/T&O models had an area-under-curve of 0.89/0.86, proving high classification accuracy. The optimal threshold of 99%/101% of the dose limit for T&R/T&O resulted in classification sensitivity and specificity of 78%/86% and 85%/78%.ConclusionsNeedle supplementation reduced OAR dose for most cases but was not always required to meet standard dose objectives, particularly for T&R cases. Our knowledge-based dose prediction model accurately identified cases that could have met constraints without needle supplementation, suggesting that such models may be beneficial for applicator selection.

PurposeCurrently, there is a lack of patient-specific tools to guide brachytherapy planning and applicator choice for cervical cancer. The purpose of this study is to evaluate the accuracy of organ-at-risk (OAR) dose predictions using knowledge-based intracavitary models, and the use of these models and clinical data to determine the dosimetric differences of tandem-and-ring (T&R) and tandem-and-ovoids (T&O) applicators.Materials and methodsKnowledge-based models, which predict organ D2cc, were trained on 77/75 cases and validated on 32/38 for T&R/T&O applicators. Model performance was quantified using ΔD2cc=D2cc,actual-D2cc,predicted, with standard deviation (σ(ΔD2cc)) representing precision. Model-predicted applicator dose differences were determined by applying T&O models to T&R cases, and vice versa, and compared to clinically-achieved D2cc differences. Applicator differences were assessed using a Student's t-test (p < 0.05 significant).ResultsValidation T&O/T&R model precision was 0.65/0.55 Gy, 0.55/0.38 Gy, and 0.43/0.60 Gy for bladder, rectum and sigmoid, respectively, and similar to training. When applying T&O/T&R models to T&R/T&O cases, bladder, rectum and sigmoid D2cc values in EQD2 were on average 5.69/2.62 Gy, 7.31/6.15 Gy and 3.65/0.69 Gy lower for T&R, with similar HRCTV volume and coverage. Clinical data also showed lower T&R OAR doses, with mean EQD2 D2cc deviations of 0.61 Gy, 7.96 Gy (p < 0.01) and 5.86 Gy (p < 0.01) for bladder, rectum and sigmoid.ConclusionsAccurate knowledge-based dose prediction models were developed for two common intracavitary applicators. These models could be beneficial for standardizing and improving the quality of brachytherapy plans. Both models and clinical data suggest that significant OAR sparing can be achieved with T&R over T&O applicators, particularly for the rectum.

PurposeThe purpose of this study is to explore knowledge-based organ-at-risk dose estimation for intracavitary brachytherapy planning for cervical cancer. Using established external-beam knowledge-based dose-volume histogram (DVH) estimation methods, we sought to predict bladder, rectum, and sigmoid D2cc for tandem and ovoid treatments.Methods and materialsA total of 136 patients with loco-regionally advanced cervical cancer treated with 456 (356:100 training:validation ratio) CT-based tandem and ovoid brachytherapy fractions were analyzed. Single fraction prescription doses were 5.5-8 Gy with dose criteria for the high-risk clinical target volume, bladder, rectum, and sigmoid. DVH estimations were obtained by subdividing training set organs-at-risk into high-risk clinical target volume boundary distance subvolumes and computing cohort-averaged differential DVHs. Full DVH estimation was then performed on the training and validation sets. Model performance was quantified by ΔD2cc = D2cc(actual)-D2cc(predicted) (mean and standard deviation). ΔD2cc between training and validation sets were compared with a Student's t test (p < 0.01 significant). Categorical variables (physician, fraction-number, total fractions, and case complexity) that might explain model variance were examined using an analysis of variance test (Bonferroni-corrected p < 0.01 threshold).ResultsTraining set deviations were bladder ΔD2cc = -0.04 ± 0.61 Gy, rectum ΔD2cc = 0.02 ± 0.57 Gy, and sigmoid ΔD2cc = -0.05 ± 0.52 Gy. Model predictions on validation set did not statistically differ: bladder ΔD2cc = -0.02 ± 0.46 Gy (p = 0.80), rectum ΔD2cc = -0.007 ± 0.47 Gy (p = 0.53), and sigmoid ΔD2cc = -0.07 ± 0.47 Gy (p = 0.70). The only significant categorical variable was the attending physician for bladder and rectum ΔD2cc. CONCLUSION: A simple boundary distance-driven knowledge-based DVH estimation exhibited promising results in predicting critical brachytherapy dose metrics. Future work will examine the utility of these predictions for quality control and automated brachytherapy planning.

PurposeTo provide insight into the types of questions asked to medical physicists by patients during one-on-one physicist-patient consults at one institution.Materials and methodsMedical physicists trained in patient communication techniques met with patients to provide an overview of the treatment planning and delivery processes, discuss the patient's treatment plan, and answer any technical questions. From August 2016 to December 2019, 152 physicist-patient consults were conducted. In the initial months of the study (August 2016-December 2017), following each physicist-patient consult, all patient questions were documented by the physicists. For the remaining time period (January 2018-December 2019), any newly encountered questions were periodically added to the list. The questions were compiled into a comprehensive list and organized into categories.ResultsThere were a total of 88 unique patient questions. These questions fit into four topical categories. Fifty-four questions (61.4%) were in the "Treatment Planning and Delivery Questions" category, 15 questions (17.1%) were in the "General Radiation Questions or Concerns" category, 13 questions (14.8%) were in the "Safety and Quality Assurance Questions" category, and 6 questions (6.8%) were in the "Medical Questions" category. Overall, patients were primarily concerned about how radiation works, the treatment planning and delivery processes, and what is being done to keep them safe throughout their treatment.ConclusionPhysicist-patient consults provided an opportunity to address the technical aspects of radiation therapy with patients in greater detail. The fact that patient questions could be conveniently grouped into only four topical categories indicates that it may be straightforward for other medical physicists to prepare for effectively addressing technical questions during physicist-patient consults.