Endovascular management of giant visceral artery aneurysms

Endovascular management of small visceral artery aneurysms is an established treatment with satisfactory outcomes. However, when size exceeds 5 cm visceral aneurysms are considered as “giant” (giant visceral artery aneurysms or GVAAs) and management is significantly more complex. Between August 2007 and June 2019 eleven cases of GVAAs that were endovascularly treated were retrospectively reviewed and included in this single center study. Mean size was 80 mm (± 26.3 mm) x 46 mm (+ -11.8 mm). Nine of the lesions were true aneurysms, and two were pseudoaneurysms. In 8 patients, the lesion was causing compression symptoms in the surrounding organs, one patient developed a contained rupture while 2 patients were completely asymptomatic. However, all patients were hemodynamically stable at the time of treatment. Technical success was defined as immediate complete exclusion of the aneurysmal sac, and clinical success as complete relief from clinical symptoms. Follow-up was performed with CT angiography, ultrasound and clinical examination. Mean follow-up was 45 months (range 6–84). Technical and clinical success were both 91%. Complications were one lack of control of contained rupture that was subsequently operated, one case of self-limiting non-target spleen embolization and one case of splenic abscess. Three patients died, one due to the contained rupture 15 days after procedure, the other two for other causes and occurred during the long-term follow-up. This series suggests that endovascular treatment of giant visceral artery aneurysms and pseudoaneuryms is a valid minimally invasive solution with very satisfactory immediate and long-term outcomes unless the aneurysm is already ruptured. A variety of endovascular tools may be required for successful treatment

Guidelines on the diagnosis, treatment and management of visceral and renal arteries aneurysms: a joint assessment by the Italian Societies of Vascular and Endovascular Surgery (SICVE) and Medical and Interventional Radiology (SIRM)

: The objective of these Guidelines is to provide recommendations for the classification, indication, treatment and management of patients suffering from aneurysmal pathology of the visceral and renal arteries. The methodology applied was the GRADE-SIGN version, and followed the instructions of the AGREE quality of reporting checklist. Clinical questions, structured according to the PICO (Population, Intervention, Comparator, Outcome) model, were formulated, and systematic literature reviews were carried out according to them. Selected articles were evaluated through specific methodological checklists. Considered Judgments were compiled for each clinical question in which the characteristics of the body of available evidence were evaluated in order to establish recommendations. Overall, 79 clinical practice recommendations were proposed. Indications for treatment and therapeutic options were discussed for each arterial district, as well as follow-up and medical management, in both candidate patients for conservative therapy and patients who underwent treatment. The recommendations provided by these guidelines simplify and improve decision-making processes and diagnostic-therapeutic pathways of patients with visceral and renal arteries aneurysms. Their widespread use is recommended

A Markovian based approach for autonomous space systems

On-board autonomy is becoming a crucial aspect of currently developed and future space projects, especially for deep space exploration missions. In the near future, spacecrafts will be able to receive, process and achieve high-level goals even in an uncertain or dynamically varying context. This paper presents a Markovian based approach in order to model on-board autonomy mechanisms. This approach fits the three layered autonomous space systems architecture and integrates a partially observable non-homogenous Markov model for the decisional layer with a Markov decision process for the operational layer. Autonomous spacecraft reconfigurability is particularly addressed

Analysis of artificial neural network performance based on influencing factors for temperature forecasting applications

Artificial neural network (ANN)-based methods belong to one of the most growing research fields within the artificial intelligence ecosystem, and many novel contributions have been developed over the last years. They are applied in many contexts, although some 'influencing factors' such as the number of neurons, the number of hidden layers, and the learning rate can impact the performance of the resulting artificial neural network-based applications. This paper provides a deep analysis about artificial neural network performance based on such factors for real-world temperature forecasting applications. An improved back propagation algorithm for such applications is also presented. By using the results of this paper, researchers and practitioners can analyse the encountered issues when applying ANN-based models for their own specific applications with the aim of achieving better performance indexes

A Lyapunov-based version of the value iteration algorithm formulated as a discrete-time switched affine system

In this paper, we analyse the convergence properties of the Dynamic Programming Value Iteration algorithm by exploiting the stability theory of discrete-time switched affine systems. More specifically, by formulating the Value Iteration algorithm as a switched affine system, a Lyapunov-based optimal policy selection strategy is designed to guarantee the practical stabilisation of the resulting system towards an invariant set of attraction containing a given target value function. The switching control algorithm, referred to as Lyapunov-based Value Iteration algorithm, can be regarded as a convergence analysis tool and can be adopted to verify if and how such target value function can be approached by choosing from a subset of suitable stationary policies, at each time slot. The usage of the proposed algorithm in practice is also discussed. Finally, two different applications are provided to further illustrate and examine the key-aspects of the approach presented

Applying unweighted least-squares based techniques to stochastic dynamic programming: Theory and application

Big data and the curse of dimensionality are common vocabularies that researchers in different communities have recently been dealing with, e.g. dynamic programming (DP) in automatic control system society. A novel unweighted sampled based least square projection approach is proposed in this study to address the issue of the large state space in the DP optimisation problem. The method, in particular, takes into account both contraction mapping and monotonicity properties of the DP algorithm for value function approximation. Specifically, the batch of samples are gathered by uniform probability distribution at first, and an unweighted LS sub-problem in the subspace is solved. As the case study, a new Markov decision process model associated with a resource allocation problem is considered to illustrate the technique and evaluate its effectiveness. It is noted that the approach can be employed for different applications as well. Moreover, a MATLAB based software is developed to implement and examine different parts of the proposed method. Simulation examples are considered to support the results of the approach via developed software. The idea makes a connection between the recent advances in big data analysis and approximate DP as well

A system engineering tool for the optimisation of a GNSS constellation design

This paper introduces a system engineering tool for the optimisation of a generic GNSS constellation design by using Galileo as reference. The optimisation is performed by taking into account both the percentage of global coverage and the accuracy in the position determination. The tool executes the optimisation not only for nominal and ideal cases, but also for off-nominal configurations involving catastrophic or transient failures of the constellation satellites. The analysis of the GNSS robustness to failures changes considerably the number of satellites to be used per plane with respect to the original configuration designed in nominal conditions