Purpose: To investigate whether a deep learning-assisted contour (DLAC) could provide greater accuracy, inter-observer consistency, and efficiency compared with a manual contour (MC) of the clinical target volume (CTV) for non-small cell lung cancer (NSCLC) receiving postoperative radiotherapy (PORT).Materials and Methods: A deep dilated residual network was used to achieve the effective automatic contour of the CTV. Eleven junior physicians contoured CTVs on 19 patients by using both MC and DLAC methods independently. Compared with the ground truth, the accuracy of the contour was evaluated by using the Dice coefficient and mean distance to agreement (MDTA). The coefficient of variation (CV) and standard distance deviation (SDD) were rendered to measure the inter-observer variability or consistency. The time consumed for each of the two contouring methods was also compared.Results: A total of 418 CTV sets were generated. DLAC improved contour accuracy when compared with MC and was associated with a larger Dice coefficient (mean ± SD: 0.75 ± 0.06 vs. 0.72 ± 0.07, p < 0.001) and smaller MDTA (mean ± SD: 2.97 ± 0.91 mm vs. 3.07 ± 0.98 mm, p < 0.001). The DLAC was also associated with decreased inter-observer variability, with a smaller CV (mean ± SD: 0.129 ± 0.040 vs. 0.183 ± 0.043, p < 0.001) and SDD (mean ± SD: 0.47 ± 0.22 mm vs. 0.72 ± 0.41 mm, p < 0.001). In addition, a value of 35% of time saving was provided by the DLAC (median: 14.81 min vs. 9.59 min, p < 0.001).Conclusions: Compared with MC, the DLAC is a promising strategy to obtain superior accuracy, consistency, and efficiency for the PORT-CTV in NSCLC.

Purpose The personalized setting of plan parameters in the Auto‐Planning module of the Pinnacle treatment planning system (TPS) using the PlanIQ feasibility tool was evaluated for lung cancer conventional fractionated radiotherapy (CFRT). Materials and method We reviewed the records of ten patients with lung cancer who were treated with volumetric modulated arc therapy (VMAT). Three plans were designed for each patient: the clinically accepted manual plan (MP) and two automatic plans including one generated using the generic plan parameters in technique script (AP1) and the other generated using personalized plan parameters derived based on feasibility dose volume histogram (FDVH) in PlanIQ (AP2). The plans were assessed according to the dosimetric parameters, monitor units, and planning time. A plan quality metric (PQM) was defined according to the clinical requirements for plan assessment. Results AP2 achieved better lung sparing than AP1 and MP. The PQM value of AP2 (52.5 ± 14.3) was higher than those of AP1 (49.2 ± 16.2) and MP (44.8 ± 16.9) with P < 0.05. The monitor units of AP2 (585.9 ± 142.9 MU) was higher than that of AP1 (511.1 ± 136.5 MU) and lower than that of MP (632.8 ± 143.8 MU) with p < 0.05. The planning time of AP2 (33.2 ± 4.8 min) was slightly higher than that of AP1 (28.2 ± 4.0 min) and substantially lower than that of MP (72.9 ± 28.5 min) with P < 0.05. Conclusions The Auto‐Planning module of the Pinnacle system using personalized plan parameters suggested by the PlanIQ Feasibility tool provides superior quality for lung cancer plans, especially in terms of lung sparing. The time consumption of Auto‐Planning was slightly higher with the personalized parameters compared to that with the generic parameters, but significantly lower than that for the manual plan.

Background SARS-CoV-2 infection is a critical concern among health care workers (HCW). Other studies have assessed SARS-CoV-2 virus and antibodies in HCW, with disparate findings regarding risk based on role and demographics. Methods We screened 3,904 employees and clinicians for SARS-CoV-2 virus positivity and serum IgG at a major New Jersey hospital from April 28-June 30, 2020. We assessed positive tests in relation to demographic and occupational characteristics and prior COVID-19 symptoms using multivariable logistic regression models. Results Thirteen participants (0.3%) tested positive for virus and 374 (9.6%) tested positive for IgG (total positive: 381 [9.8%]). Compared to participants with no patient care duties, the odds of positive testing (virus or antibodies) were higher for those with direct patient contact: below-median patient contact, adjusted OR (aOR): 1.71, 95% CI: 1.18, 2.48); above-median patient contact aOR: 1.98, 95% CI: 1.35, 2.91. The proportion of participants testing positive was highest for phlebotomists (23.9%), maintenance/housekeeping (17.3%), dining/food services (16.9%), and interpersonal/support roles (13.7%) despite lower levels of direct patient care duties. Positivity rates were lower among doctors (7.2%) and nurses (9.1%), roles with fewer under-represented minorities. After adjusting for job role and patient care responsibilities and other factors, Black and Latinx workers had two-fold increased odds of a positive test compared to White workers. Loss of smell, taste, and fever were associated with positive testing. Conclusions The HCW categories at highest risk for SARS-CoV-2 infection include support staff and underrepresented minorities with and without patient care responsibilities. Future work is needed to examine potential sources of community and nosocomial exposure among these under-studied HCW.

The breakdown phenomena of a resistively shunted two-dimensional Josephson-junction array with a single defect driven by an external current at zero temperature are studied numerically. The nonlinear Josephson relation causes the formation of vortices at the tips of the defect at i v and thus lowers the current enhancement there. Above a higher critical current i c the vortices depin from the defect and march across the sample producing a voltage. The critical current i c is studied versus defect size. Various dynamical properties and the l-V characteristics of the array are explained in the context of vortex motion. From the observed features the critical behavior of a randomly disordered array is predicted. PACS numbers: 74.60.Jg, 05.60.+W, 74.70.Mq Breakdown phenomena in various inhomogeneous systems have been studied extensively over the past four years.*~3 The effects of the most critical defects turn out to be very important in understanding the breakdown process. Recently, Leath and Tang 4 have studied the critical current in an inhomogeneous superconducting system by looking into the current distributions in both the normal and superconducting regions utilizing the linearized Ginzburg-Landau equations. These linearized equations and the boundary conditions turn out to be similar to those of the random-resistor network problem.While the linearized problem is easier to analyze, the nonlinear effects turn out to be essential in accounting for the appearance of vortices (topological excitations) and their dissipation and therefore the breakdown of the superconducting weak-link system. In this Letter we report results of studying the breakdown process in superconducting weak-link systems with a simple defect by using resistively shunted Josephson-junction arrays. We study numerically the role of a single critical defect of varying size in the resistively shunted junction array and the dynamical properties of the vortices caused by the defect in the system, and use this to predict the behavior of randomly disordered arrays. The presence of the defect causes drastically different behavior from that previously reported by authors of numerical 5,6 and experimental 7 studies of perfect arrays.The system we studied is one in which superconducting grains are uniformly distributed in two dimensions to form the sites of a square lattice. Within our approximation each grain (site) is described by a complex superconducting order parameter A-Ao^, where A 0 is constant for all grains and

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