Court, Laurence E.

Abstract Background Burnout is a work‐related syndrome characterized by increased levels of emotional exhaustion (EE) and depersonalization (DP) along with decreased levels of personal achievement. In the healthcare setting, higher burnout levels have been associated with negative impacts on personnel, an increased risk of errors, and a decrease in the quality of delivered care. Purpose The purpose of this study was to assess the prevalence of burnout among medical physicists working in the United States. Additionally, the impact of personal and organizational features on burnout risk was examined. Methods The anonymous survey was distributed to 1962 full members of the American Association of Physicists in Medicine. The survey consisted of seven demographic questions, the validated Maslach Burnout Inventory (MBI), and an organizational assessment tool. Burnout risk was evaluated using two different scoring methods. Inferential statistics were employed to examine the relationship between burnout and personal features, such as practiced sub‐specialty, and organizational features, including the respondent's assigned facility safety score. Results A total of 337 responses were received, and 59.9% of medical physicist participants scored high on at least one burnout domain. A statistically significant association was found between the EE and DP burnout domains and personal factors, including working as a therapy medical physicist, working longer hours, and a moderate or significant impact on work‐related feelings due to the COVID‐19 pandemic. A statistically significant relationship was identified between all three burnout domains and the respondent's assigned facility safety score. Amongst therapy physicists, an inverse relationship was observed between all three burnout domains and both the teamwork and staffing constructs, as well as the open communication and punitive concerns construct. Conclusions Medical physicists in the United States are experiencing significant levels of burnout. Importantly, this study identified a link between quantitative burnout scores and facility safety, stressing the importance of addressing burnout.

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual‐energy CT (DECT) and photon‐counting detector CT (PCD‐CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD‐CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi‐energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image‐guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

Respiratory motion is traditionally assessed using tumor motion magnitude. In proton therapy, respiratory motion causes density variations along the beam path that result in uncertainties of proton range. This work has investigated the use of water‐equivalent thickness (WET) to quantitatively assess the effects of respiratory motion on calculated dose in passively scattered proton therapy (PSPT). A cohort of 29 locally advanced non‐small cell lung cancer patients treated with 87 PSPT treatment fields were selected for analysis. The variation in WET (ΔWET) along each field was calculated between exhale and inhale phases of the simulation four‐dimensional computed tomography. The change in calculated dose (ΔDose) between full‐inhale and full‐exhale phase was quantified for each field using dose differences, 3D gamma analysis, and differential area under the curve (ΔAUC) analysis. Pearson correlation coefficients were calculated between ΔDose and ΔWET. Three PSPT plans were redesigned using field angles to minimize variations in ΔWET and compared to the original plans. The median ΔWET over 87 treatment fields ranged from 1‐9 mm, while the ΔWET 95th percentile value ranged up to 42 mm. The ΔWET was significantly correlated to the ΔDose for all metrics analyzed. The patient plans that were redesigned using ΔWET analysis to select field angles were more robust to the effects of respiratory motion, as ΔAUC values were reduced by more than 60% in all three cases. The tumor motion magnitude alone does not capture the potential dosimetric error due to respiratory motion because the proton range is sensitive to the motion of all patient anatomy. The use of ΔWET has been demonstrated to identify situations where respiratory motion can impact the calculated dose. Angular analysis of ΔWET may be capable of designing radiotherapy plans that are more robust to the effects of respiratory motion.PACS number(s): 87.55.‐x

In this work we used 4D dose calculations, which include the effects of shape deformations, to investigate an alternative approach to creating the ITV. We hypothesized that instead of needing images from all the breathing phases in the 4D CT dataset to create the outer envelope used for treatment planning, it is possible to exclude images from the phases closest to the inhale phase. We used 4D CT images from 10 patients with lung cancer. For each patient, we drew a gross tumor volume on the exhale‐phase image and propagated this to the images from other phases in the 4D CT dataset using commercial image registration software. We created four different ITVs using the N phases closest to the exhale phase (where , 8, 7, 6). For each ITV contour, we created a volume‐modulated arc therapy plan on the exhale‐phase CT and normalized it so that the prescribed dose covered at least 95% of the ITV. Each plan was applied to CT images from each CT phase (phases 1–10), and the calculated doses were then mapped to the exhale phase using deformable registration. The effect of the motion was quantified using the dose to 95% of the target on the exhale phase and tumor control probability. For the three‐dimensional and 4D dose calculations of the plan where , differences in the value varied from 3% to 14%, with an average difference of 7%. For 9 of the 10 patients, the reduction in was less than 5% if eight phases were used to create the ITV. For three of the 10 patients, the reduction in the was less than 5% if seven phases were used to create the ITV. We were unsuccessful in creating a general rule that could be used to create the ITV. Some reduction (8/10 phases) was possible for most, but not all, of the patients, and the ITV reduction was small.PACS number: 87.55.D‐