Perfusion in ENT imaging

AbstractPerfusion MRI is an essential part of characterizing salivary gland tumors. The shape of the curves can provide a guide as to the type of lesion: benign (ascending plateau) or malignant (descending plateau), and can also occasionally strongly suggest a histological type such as a Warthin tumor (intense, rapid contrast enhancement with washout>30%). Perfusion imaging (CT or MRI) for other head and neck tumors is currently being developed and is being assessed. It should be a tool to assist in choosing the most appropriate initial treatment (chemotherapy, radiotherapy or surgery) and should also allow poor responders to conservative treatment to be identified and recurrences to be detected in post-treatment damaged tissues. Aims: (a) to determine when to perform perfusion MRI; (b) to determine the type of perfusion to carry out: CT, T1-weighted MRI; (c) to determine how to position the region of interest to plot the perfusion curve; (d) to know how to interpret MRI curves for salivary gland tumors; (e) to know how to interpret the information obtained from perfusion CT or MRI for the upper aerodigestive tract

Intraparotid Kimura disease

SummaryIntroductionIntraparotid locations are extremely rare in Kimura disease, especially in Europe.Case reportA 31-year-old man presented with intraparotid Kimura disease, managed by parotidectomy.Discussion/conclusionThe case was analyzed in the light of a review of the literature, focusing on the diagnostic and anatomopathologic problems encountered, and the physiopathology and treatment of this pathology. Any parotid mass found in a patient of Far-Eastern origin showing hypereosinophilia should suggest a diagnosis of intraparotid Kimura disease

GIS and spatial data analysis: Converging perspectives

We take as our starting point the state of geographic information systems (GIS) and spatial data analysis 50 years ago when regional science emerged as a new field of enquiry. In the late 1950s and 1960s advances in computing technology were making possible forms of automated cartography that in due course would lead to th

Multiple Causation and the Measurement of Unemployment

The establishment of appropriate policy measures for fighting unemployment has always been difficult since causes of unemployment are hard to identify. This paper analyses an approach used mainly in the 1960s and 1970s in economics, in which classification is used as a way to deal with such a complex, multiple causal phenomenon like unemployment. The method is based on decomposing unemployment into classes of unemployment and the measurement of each of these classes by reference to stable, measurable macroeconomic relationships like the Phillips curve and the Beveridge curve. In this way economists were able to ‘diagnose’ unemployment and make policy recommendations for fighting unemployment without making explicit reference to the underlying singular causes of unemployment

Capital Stock and Unemployment: Searching for the Missing Link

This paper examines the proposition that capital stock relative to aggregate output has been an important variable in the determination of the Non-Accelerating Inflation Rate of Unemployment (NAIRU) over the last four decades. The authors present new empirical evidence that lends strong support to the claim that the aggregate capital-output ratio, the real price of imports, and aggregate capacity utilization were determinants of the NAIRU during the period. The same evidence also shows that technical progress and changes in long-term unemployment did not affect the NAIRU. We believe this evidence suggests that, insofar as the aggregate capital-output ratio is affected by changes in real interest rates, the stance of monetary policy is one determinant of the NAIRU

Agent-Based Modeling of a Non-tâtonnement Process for the Scarf Economy: The Role of Learning

In this paper, we propose a meta-learning model to hierarchically integrate individual learning and social learning schemes. This meta-learning model is incorporated into an agent-based model to show that Herbert Scarf’s famous counterexample on Walrasian stability can become stable in some cases under a non-tâtonnement process when both learning schemes are involved, a result previously obtained by Herbert Gintis. However, we find that the stability of the competitive equilibrium depends on how individuals learn—whether they are innovators (individual learners) or imitators (social learners), and their switching frequency (mobility) between the two. We show that this endogenous behavior, apart from the initial population of innovators, is mainly determined by the agents’ intensity of choice. This study grounds the Walrasian competitive equilibrium based on the view of a balanced resource allocation between exploitation and exploration. This balance, achieved through a meta-learning model, is shown to be underpinned by a behavioral/psychological characteristic