Parallel transmission RF pulse design with strict temperature constraints.

RF safety in parallel transmission (pTx) is generally ensured by imposing specific absorption rate (SAR) limits during pTx RF pulse design. There is increasing interest in using temperature to ensure safety in MRI. In this work, we present a local temperature correlation matrix formalism and apply it to impose strict constraints on maximum absolute temperature in pTx RF pulse design for head and hip regions. Electromagnetic field simulations were performed on the head and hip of virtual body models. Temperature correlation matrices were calculated for four different exposure durations ranging between 6 and 24 min using simulated fields and body-specific constants. Parallel transmission RF pulses were designed using either SAR or temperature constraints, and compared with each other and unconstrained RF pulse design in terms of excitation fidelity and safety. The use of temperature correlation matrices resulted in better excitation fidelity compared with the use of SAR in parallel transmission RF pulse design (for the 6 min exposure period, 8.8% versus 21.0% for the head and 28.0% versus 32.2% for the hip region). As RF exposure duration increases (from 6 min to 24 min), the benefit of using temperature correlation matrices on RF pulse design diminishes. However, the safety of the subject is always guaranteed (the maximum temperature was equal to 39°C). This trend was observed in both head and hip regions, where the perfusion rates are very different.

Geographic Variation in Otolaryngologist Intranasal Steroid Prescribing Patterns Among Medicare Beneficiaries.

BACKGROUND: Intranasal corticosteroids (INCS) are a commonly prescribed medication to treat various rhinological conditions. However, no prior studies have looked at factors and patterns that influence the rates of INCS prescriptions among Medicare beneficiaries in the United States. OBJECTIVE: This study aims to describe the patterns of INCS prescriptions by otolaryngologists for Medicare beneficiaries in the United States between 2013 and 2017. METHODS: Data on the most common INCS prescriptions by otolaryngologists for Medicare beneficiaries were obtained from the 2013 to 2017 Medicare Provider Utilization and Payment Data: Physician and Other Supplier Public Use File (PUF) and the Part D Public Use Files from the Centers for Medicare and Medicaid Services (CMS). INCS prescriptions were analyzed by cost, state, provider, and regional temperature. State temperature data was collected through the National Centers for Environmental Information. RESULTS: From 2013 to 2017, the total claims per beneficiary for fluticasone, mometasone, and triamcinolone combined increased from 2.31 to 2.39. Combined cost/beneficiary was similar for mometasone and triamcinolone at 102.47 and 103.60 respectively, while it was much lower for fluticasone at 39.12. There was a strong correlation between otolaryngology providers per beneficiary in each state and total claims per state with a correlation coefficient of .79. Additionally, comparing the average state temperature to the claims/beneficiary yielded a moderately strong correlation coefficient of .44, suggesting that temperature was a possible factor for INCS prescription patterns. CONCLUSIONS: INCS prescriptions by otolaryngologists and the number of INCS beneficiaries have increased between 2013 and 2017. Over the same time period, the costs of fluticasone and triamcinolone have decreased while the cost of mometasone increased. Total providers by state correlated with claims per state. Additionally, average annual temperature was positively correlated with INCS claims per beneficiary in each state.

Predictive Modeling of Machining Temperatures with Force⁻Temperature Correlation Using Cutting Mechanics and Constitutive Relation.

Elevated temperature in the machining process is detrimental to cutting tools-a result of the effect of thermal softening and material diffusion. Material diffusion also deteriorates the quality of the machined part. Measuring or predicting machining temperatures is important for the optimization of the machining process, but experimental temperature measurement is difficult and inconvenient because of the complex contact phenomena between tools and workpieces, and because of restricted accessibility during the machining process. This paper presents an original analytical model for fast prediction of machining temperatures at two deformation zones in orthogonal cutting, namely the primary shear zone and the tool⁻chip interface. Temperatures were predicted based on a correlation between force and temperature using the mechanics of the cutting process and material constitutive relation. Minimization of the differences between calculated material flow stresses using a mechanics model and a constitutive model yielded an estimate of machining temperatures. Experimental forces, cutting condition parameters, and constitutive model constants were inputs, while machining forces were easily measurable by a piezoelectric dynamometer. Machining temperatures of AISI 1045 steel were predicted under various cutting conditions to demonstrate the predictive capability of each presented model. Close agreements were observed by verifying them against documented values in the literature. The influence of model inputs and computational efficiency were further investigated. The presented model has high computational efficiency that allows real-time prediction and low experimental complexity, considering the easily measurable input variables.