Constraint-adaptive MPC for linear systems:A system-theoretic framework for speeding up MPC through online constraint removal

Reducing the computation time of model predictive control (MPC) is important, especially for systems constrained by many state constraints. In this paper, we propose a new online constraint removal framework for linear systems, for which we coin the term constraint-adaptive MPC (ca-MPC). In so-called exact ca-MPC, we adapt the imposed constraints by removing, at each time-step, a subset of the state constraints in order to reduce the computational complexity of the receding-horizon optimal control problem, while ensuring that the closed-loop behavior is identical to that of the original MPC law. We also propose an approximate ca-MPC scheme in which a further reduction of computation time can be accomplished by a tradeoff with closed-loop performance, while still preserving recursive feasibility, stability, and constraint satisfaction properties. The online constraint removal exploits fast backward and forward reachability computations combined with optimality properties.</p

Simultaneous estimation of SAR, thermal diffusivity, and damping using periodic power modulation for MRgFUS quality assurance

Purpose: A crucial aspect of quality assurance in thermal therapy is periodic demonstration of the heating performance of the device. Existing methods estimate the specific absorption rate (SAR) from the temperature rise after a short power pulse, which yields a biased estimate as thermal diffusion broadens the apparent SAR pattern. To obtain an unbiased estimate, we propose a robust frequency-domain method that simultaneously identifies the SAR as well as the thermal dynamics. Methods: We propose a method consisting of periodic modulation of the FUS power while recording the response with MR thermometry (MRT). This approach enables unbiased measurements of spatial Fourier coefficients that encode the thermal response. These coefficients are substituted in a generic thermal model to simultaneously estimate the SAR, diffusivity, and damping. The method was tested using a cylindrical phantom and a 3 T clinical MR-HIFU system. Three scenarios with varying modulation strategies are chosen to challenge the method. The results are compared to the well-known power pulse technique. Results: The thermal diffusivity is estimated at 0.151 mm 2s -1 with a standard deviation of 0.01 mm 2s -1 between six experiments. The SAR estimates are consistent between all experiments and show an excellent signal-to-noise ratio (SNR) compared to the well established power pulse method. The frequency-domain method proved to be insensitive to B 0-drift and non steady-state initial temperature distributions. Conclusion: The proposed frequency-domain estimation method shows a high SNR and provided reproducible estimates of the SAR and the corresponding thermal diffusivity. The findings suggest that frequency-domain tools can be highly effective at estimating the SAR from (biased) MRT data acquired during periodic power modulation. </p

A socially interdependent choice framework for social influences in healthcare decision-making:a study protocol

OBJECTIVES: Current choice models in healthcare (and beyond) can provide suboptimal predictions of healthcare users' decisions. One reason for such inaccuracy is that standard microeconomic theory assumes that decisions of healthcare users are made in a social vacuum. Healthcare choices, however, can in fact be (entirely) socially determined. To achieve more accurate choice predictions within healthcare and therefore better policy decisions, the social influences that affect healthcare user decision-making need to be identified and explicitly integrated into choice models. The purpose of this study is to develop a socially interdependent choice framework of healthcare user decision-making.DESIGN: A mixed-methods approach will be used. A systematic literature review will be conducted that identifies the social influences on healthcare user decision-making. Based on the outcomes of a systematic literature review, an interview guide will be developed that assesses which, and how, social influences affect healthcare user decision-making in four different medical fields. This guide will be used during two exploratory focus groups to assess the engagement of participants and clarity of questions and probes. The refined interview guide will be used to conduct the semistructured interviews with healthcare professionals and users. These interviews will explore in detail which, and how, social influences affect healthcare user decision-making. Focus group and interview transcripts will be analysed iteratively using a constant comparative approach based on a mix of inductive and deductive coding. Based on the outcomes, a social influence independent choice framework for healthcare user decision-making will be drafted. Finally, the Delphi technique will be employed to achieve consensus about the final version of this choice framework.ETHICS AND DISSEMINATION: This study was approved by the Erasmus School of Health Policy and Management Research Ethics Review Committee (ESHPM, Rotterdam, The Netherlands; reference ETH2122-0666).</p

Adapting temperature predictions to MR imaging in treatment position to improve simulation-guided hyperthermia for cervical cancer

Hyperthermia treatment consists of elevating the temperature of the tumor to increase the effectiveness of radiotherapy and chemotherapy. Hyperthermia treatment planning (HTP) is an important tool to optimize treatment quality using pre-treatment temperature predictions. The accuracy of these predictions depends on modeling uncertainties such as tissue properties and positioning. In this study, we evaluated if HTP accuracy improves when the patient is imaged inside the applicator at the start of treatment. Because perfusion is a major uncertainty source, the importance of accurate treatment position and anatomy was evaluated using different perfusion values. Volunteers were scanned using MR imaging without (&amp;#x201C;planning setup&amp;#x201D;) and with the MR-compatible hyperthermia device (&amp;#x201C;treatment setup&amp;#x201D;). Temperature-based quality indicators were used to assess the differences between the standard, apparent and the optimized hyperthermia dose. We conclude that pre-treatment imaging can improve HTP predictions accuracy but also, that tissue perfusion modelling is crucial if temperature-based optimization is applied.</p

Alpine altitude climate treatment for severe and uncontrolled asthma: an EAACI position paper

Currently available European Alpine Altitude Climate Treatment (AACT) programs combine the physical characteristics of altitude with the avoidance of environmental triggers in the alpine climate and a personalized multidisciplinary pulmonary rehabilitation approach. The reduced barometric pressure, oxygen pressure, and air density, the relatively low temperature and humidity, and the increased UV radiation at moderate altitude induce several physiological and immunological adaptation responses. The environmental characteristics of the alpine climate include reduced aeroallergens such as house dust mites (HDM), pollen, fungi, and less air pollution. These combined factors seem to have immunomodulatory effects controlling pathogenic inflammatory responses and favoring less neuro-immune stress in patients with different asthma phenotypes. The extensive multidisciplinary treatment program may further contribute to the observed clinical improvement by AACT in asthma control and quality of life, fewer exacerbations and hospitalizations, reduced need for oral corticosteroids (OCS), improved lung function, decreased airway hyperresponsiveness (AHR), improved exercise tolerance, and improved sinonasal outcomes. Based on observational studies and expert opinion, AACT represents a valuable therapy for those patients irrespective of their asthma phenotype, who cannot achieve optimal control of their complex condition despite all the advances in medical science and treatment according to guidelines, and therefore run the risk of falling into a downward spiral of loss of physical and mental health. In the light of the observed rapid decrease in inflammation and immunomodulatory effects, AACT can be considered as a natural treatment that targets biological pathways

A socially interdependent choice framework for social influences in healthcare decision-making:a study protocol

OBJECTIVES: Current choice models in healthcare (and beyond) can provide suboptimal predictions of healthcare users' decisions. One reason for such inaccuracy is that standard microeconomic theory assumes that decisions of healthcare users are made in a social vacuum. Healthcare choices, however, can in fact be (entirely) socially determined. To achieve more accurate choice predictions within healthcare and therefore better policy decisions, the social influences that affect healthcare user decision-making need to be identified and explicitly integrated into choice models. The purpose of this study is to develop a socially interdependent choice framework of healthcare user decision-making.DESIGN: A mixed-methods approach will be used. A systematic literature review will be conducted that identifies the social influences on healthcare user decision-making. Based on the outcomes of a systematic literature review, an interview guide will be developed that assesses which, and how, social influences affect healthcare user decision-making in four different medical fields. This guide will be used during two exploratory focus groups to assess the engagement of participants and clarity of questions and probes. The refined interview guide will be used to conduct the semistructured interviews with healthcare professionals and users. These interviews will explore in detail which, and how, social influences affect healthcare user decision-making. Focus group and interview transcripts will be analysed iteratively using a constant comparative approach based on a mix of inductive and deductive coding. Based on the outcomes, a social influence independent choice framework for healthcare user decision-making will be drafted. Finally, the Delphi technique will be employed to achieve consensus about the final version of this choice framework.ETHICS AND DISSEMINATION: This study was approved by the Erasmus School of Health Policy and Management Research Ethics Review Committee (ESHPM, Rotterdam, The Netherlands; reference ETH2122-0666).</p

Simultaneous estimation of SAR, thermal diffusivity, and damping using periodic power modulation for MRgFUS quality assurance

AbstractPurpose: A crucial aspect of quality assurance in thermal therapy is periodic demonstration of the heating performance of the device. Existing methods estimate the specific absorption rate (SAR) from the temperature rise after a short power pulse, which yields a biased estimate as thermal diffusion broadens the apparent SAR pattern. To obtain an unbiased estimate, we propose a robust frequency-domain method that simultaneously identifies the SAR as well as the thermal dynamics.Methods: We propose a method consisting of periodic modulation of the FUS power while recording the response with MR thermometry (MRT). This approach enables unbiased measurements of spatial Fourier coefficients that encode the thermal response. These coefficients are substituted in a generic thermal model to simultaneously estimate the SAR, diffusivity, and damping. The method was tested using a cylindrical phantom and a 3 T clinical MR-HIFU system. Three scenarios with varying modulation strategies are chosen to challenge the method. The results are compared to the well-known power pulse technique.Results: The thermal diffusivity is estimated at 0.151 mm2s–1 with a standard deviation of 0.01 mm2s–1 between six experiments. The SAR estimates are consistent between all experiments and show an excellent signal-to-noise ratio (SNR) compared to the well established power pulse method. The frequency-domain method proved to be insensitive to B0-drift and non steady-state initial temperature distributions.Conclusion: The proposed frequency-domain estimation method shows a high SNR and provided reproducible estimates of the SAR and the corresponding thermal diffusivity. The findings suggest that frequency-domain tools can be highly effective at estimating the SAR from (biased) MRT data acquired during periodic power modulation

POD–Kalman filtering for improving noninvasive 3D temperature monitoring in MR-guided hyperthermia

Background: During resonance frequency (RF) hyperthermia treatment, the temperature of the tumor tissue is elevated to the range of 39–44°C. Accurate temperature monitoring is essential to guide treatments and ensure precise heat delivery and treatment quality. Magnetic resonance (MR) thermometry is currently the only clinical method to measure temperature noninvasively in a volume during treatment. However, several studies have shown that this approach is not always sufficiently accurate for thermal dosimetry in areas with motion, such as the pelvic region. Model-based temperature estimation is a promising approach to correct and supplement 3D online temperature estimation in regions where MR thermometry is unreliable or cannot be measured. However, complete 3D temperature modeling of the pelvic region is too complex for online usage. Purpose: This study aimed to evaluate the use of proper orthogonal decomposition (POD) model reduction combined with Kalman filtering to improve temperature estimation using MR thermometry. Furthermore, we assessed the benefit of this method using data from hyperthermia treatment where there were limited and unreliable MR thermometry measurements. Methods: The performance of POD–Kalman filtering was evaluated in several heating experiments and for data from patients treated for locally advanced cervical cancer. For each method, we evaluated the mean absolute error (MAE) concerning the temperature measurements acquired by the thermal probes, and we assessed the reproducibility and consistency using the standard deviation of error (SDE). Furthermore, three patient groups were defined according to susceptibility artifacts caused by the level of intestinal gas motion to assess if the POD–Kalman filtering could compensate for missing and unreliable MR thermometry measurements. Results: First, we showed that this method is beneficial and reproducible in phantom experiments. Second, we demonstrated that the combined method improved the match between temperature prediction and temperature acquired by intraluminal thermometry for patients treated for locally advanced cervical cancer. Considering all patients, the POD–Kalman filter improved MAE by 43% (filtered MR thermometry = 1.29°C, POD–Kalman filtered temperature = 0.74°C). Moreover, the SDE was improved by 47% (filtered MR thermometry = 1.16°C, POD–Kalman filtered temperature = 0.61°C). Specifically, the POD–Kalman filter reduced the MAE by approximately 60% in patients whose MR thermometry was unreliable because of the great amount of susceptibilities caused by the high level of intestinal gas motion. Conclusions: We showed that the POD–Kalman filter significantly improved the accuracy of temperature monitoring compared to MR thermometry in heating experiments and hyperthermia treatments. The results demonstrated that POD–Kalman filtering can improve thermal dosimetry during RF hyperthermia treatment, especially when MR thermometry is inaccurate.RST/Applied Radiation & Isotope