Regional income inequality in Italy in the long run (1871–2001). Patterns and determinants

The chapter presents up-to-date estimates of Italy’s regional GDP, with the present borders, in ten-year benchmarks from 1871 to 2001, and proposes a new interpretative hypothesis based on long-lasting socio-institutional differences. The inverted U-shape of income inequality is confirmed: rising divergence until the midtwentieth century, then convergence. However, the latter was limited to the centrenorth: Italy was divided into three parts by the time regional inequality peaked, in 1951, and appears to have been split into two halves by 2001. As a consequence of the falling back of the south, from 1871 to 2001 we record σ-divergence across Italy’s regions, i.e. an increase in dispersion, and sluggish β-convergence. Geographical factors and the market size played a minor role: against them are both the evidence that most of the differences in GDP are due to employment rather than to productivity and the observed GDP patterns of many regions. The gradual converging of regional GDPs towards two equilibria instead follows social and institutional differences − in the political and economic institutions and in the levels of human and social capital – which originated in pre-unification states and did not die (but in part even increased) in postunification Italy.

Interobserver and intraobserver variability of apparent diffusion coefficient measurements in treated malignant hepatic lesions: measurements in the whole lesion versus in the area with the most restricted diffusion

Purpose: The increase of apparent diffusion coefficient (ADC) in treated hepatic malignancies compared to pre-therapeutic values has been interpreted as treatment success; however, the variability of ADC measurements remains unknown. Furthermore, ADC has been usually measured in the whole lesion, while measurements should be probably centered on the area with the most restricted diffusion (MRDA) as it represents potential tumoral residue. Our objective was to compare the inter/intraobserver variability of ADC measurements in the whole lesion and in MRDA. Material and methods: Forty patients previously treated with chemoembolization or radiofrequency were evaluated (20 on 1.5T and 20 on 3.0T). After consensual agreement on the best ADC image, two readers measured the ADC values using separate regions of interest that included the whole lesion and the whole MRDA without exceeding their borders. The same measurements were repeated two weeks later. Spearman test and the Bland-Altman method were used. Results: Interobserver correlation in ADC measurements in the whole lesion and MRDA was as follows: 0.962 and 0.884. Intraobserver correlation was, respectively, 0.992 and 0.979. Interobserver limits of variability (mm2/sec*10-3) were between -0.25/+0.28 in the whole lesion and between -0.51/+0.46 in MRDA. Intraobserver limits of variability were, respectively: -0.25/+0.24 and -0.43/+0.47. Conclusion: We observed a good inter/intraobserver correlation in ADC measurements. Nevertheless, a limited variability does exist, and it should be considered when interpreting ADC values of hepatic malignancies.

A realistic Computed Tomography simulator for small motion analysis of cerebral aneurysms.

This paper describes a realistic simulator for the Computed Tomography (CT) scan process for motion analysis. In fact, we are currently developing a new framework to find small motion from the CT scan. In order to prove the fidelity of this framework, or potentially any other algorithm, we present in this paper a simulator to simulate the whole CT acquisition process with a priori known parameters. In other words, it is a digital phantom for the motion analysis that can be used to compare the results of any related algorithm with the ground-truth realistic analytical model. Such a simulator can be used by the community to test different algorithms in the biomedical imaging domain. The most important features of this simulator are its different considerations to simulate the best the real acquisition process and its generality.

Validation of tissue modelization and classification techniques in T1-weighted MR brain images

We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.

3D noise power spectrum applied on clinical mdct scanners: effects of reconstruction algorithms and reconstruction filters

The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters.A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed.In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements.The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

Detection of smuggled cocaine in cargo using MDCT.

OBJECTIVE: Smuggling dissolved drugs, especially cocaine, in bottled liquids is an ongoing problem at borders. Common fluoroscopy of packages at the border cannot detect contaminated liquids. The objective of our study was to develop an MDCT screening method to detect cocaine-containing vessels that are hidden between uncontaminated ones in a shipment. MATERIALS AND METHODS: Studies were performed on three wine bottles containing cocaine solutions that were confiscated at the Swiss border. Reference values were obtained by scans of different sorts of commercially available wine and aqueous solutions of dissolved sugar. All bottles were scanned using MDCT, and data evaluation was performed by measuring the mean peak of Hounsfield units. To verify the method, simulated testing was performed. RESULTS: Using measurements of the mean peak of Hounsfield units enables the detection of dissolved cocaine in wine bottles in a noninvasive and rapid fashion. Increasing opacity corresponds well with the concentration of dissolved cocaine. Simulated testing showed that it is possible to distinguish between cocaine-contaminated and uncontaminated wine bottles. CONCLUSION: The described method is an efficacious screening method to detect cocaine-contaminated bottles that are hidden between untreated bottles in cargo. The noninvasive examination of cargo allows a questionable delivery to be tracked without arousing the suspicion of the smugglers.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

Computed tomography commissioning programmes: how to obtain a reliable MTF with an automatic approach?

The purpose of this study was to assess the spatial resolution of a computed tomography (CT) scanner with an automatic approach developed for routine quality controls when varying CT parameters. The methods available to assess the modulation transfer functions (MTF) with the automatic approach were Droege's and the bead point source (BPS) methods. These MTFs were compared with presampled ones obtained using Boone's method. The results show that Droege's method is not accurate in the low-frequency range, whereas the BPS method is highly sensitive to image noise. While both methods are well adapted to routine stability controls, it was shown that they are not able to provide absolute measurements. On the other hand, Boone's method, which is robust with respect to aliasing, more resilient to noise and provides absolute measurements, satisfies the commissioning requirements perfectly. Thus, Boone's method combined with a modified Catphan 600 phantom could be a good solution to assess CT spatial resolution in the different CT planes.

Monte Carlo simulation of a clearance box monitor used for nuclear power plant decommissioning.

When decommissioning a nuclear facility it is important to be able to estimate activity levels of potentially radioactive samples and compare with clearance values defined by regulatory authorities. This paper presents a method of calibrating a clearance box monitor based on practical experimental measurements and Monte Carlo simulations. Adjusting the simulation for experimental data obtained using a simple point source permits the computation of absolute calibration factors for more complex geometries with an accuracy of a bit more than 20%. The uncertainty of the calibration factor can be improved to about 10% when the simulation is used relatively, in direct comparison with a measurement performed in the same geometry but with another nuclide. The simulation can also be used to validate the experimental calibration procedure when the sample is supposed to be homogeneous but the calibration factor is derived from a plate phantom. For more realistic geometries, like a small gravel dumpster, Monte Carlo simulation shows that the calibration factor obtained with a larger homogeneous phantom is correct within about 20%, if sample density is taken as the influencing parameter. Finally, simulation can be used to estimate the effect of a contamination hotspot. The research supporting this paper shows that activity could be largely underestimated in the event of a centrally-located hotspot and overestimated for a peripherally-located hotspot if the sample is assumed to be homogeneously contaminated. This demonstrates the usefulness of being able to complement experimental methods with Monte Carlo simulations in order to estimate calibration factors that cannot be directly measured because of a lack of available material or specific geometries.

The impact of spatial resolution and respiratory motion on MR imaging of atherosclerotic plaque.

PURPOSE: To examine the impact of spatial resolution and respiratory motion on the ability to accurately measure atherosclerotic plaque burden and to visually identify atherosclerotic plaque composition. MATERIALS AND METHODS: Numerical simulations of the Bloch equations and vessel wall phantom studies were performed for different spatial resolutions by incrementally increasing the field of view. In addition, respiratory motion was simulated based on a measured physiologic breathing pattern. RESULTS: While a spatial resolution of > or = 6 pixels across the wall does not result in significant errors, a resolution of < or = 4 pixels across the wall leads to an overestimation of > 20%. Using a double-inversion T2-weighted turbo spin echo sequence, a resolution of 1 pixel across equally thick tissue layers (fibrous cap, lipid, smooth muscle) and a respiratory motion correction precision (gating window) of three times the thickness of the tissue layer allow for characterization of the different coronary wall components. CONCLUSIONS: We found that measurements in low-resolution black blood images tend to overestimate vessel wall area and underestimate lumen area.

Computer Aided Detection and measurement of peripheral artery disease.

Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and a fast 3D morphology operation. The CAM stage aims to accurately measure the artery diameters from the detected vessel centerline, compensating for the partial volume effect using Expectation Maximization (EM) and a Markov Random field (MRF). The system has been evaluated on phantom data and also applied to fifteen (15) CTA datasets, where the detection accuracy of stenosis was 88% and the measurement accuracy was with an 8% error.

Hind limb ischemia in rabbit model: T2-prepared versus time-of-flight MR angiography at 3 T.

PURPOSE: To prospectively compare various parameters of vessels imaged at 3 T by using time-of-flight (TOF) and T2-prepared magnetic resonance (MR) angiography in a rabbit model of hind limb ischemia. MATERIALS AND METHODS: Experiments were approved by the institutional animal care and use committee. Endovascular occlusion of the left superficial femoral artery was induced in 14 New Zealand white rabbits. After 2 weeks, MR angiography and conventional (x-ray) angiography were performed. Vessel sharpness was evaluated visually in the ischemic and nonischemic limbs, and the presence of small collateral vessels was evaluated in the ischemic limbs. Vessel sharpness was also quantified by evaluating the magnitude of signal intensity change at the vessel borders. RESULTS: The sharpness of vessels in the nonischemic limbs was similar between the TOF and the T2-prepared images. In the ischemic limbs, however, T2-prepared imaging, as compared with TOF imaging, generated higher vessel sharpness in arteries with diminished blood flow (mean vessel sharpness: 44% vs 30% for popliteal arteries, 45% vs 28% for saphenous arteries; P < .001 for both comparisons) and enabled better detection of small collateral vessels (93% vs 36% of vessels, P < .001). CONCLUSION: T2-prepared imaging can facilitate high-spatial-resolution MR angiography of small vessels with low blood flow and thus has potential as a tool for noninvasive evaluation of arteriogenic therapies, without use of contrast material. Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/2452062067/DC1.

Illusory contours: a window onto the neurophysiology of constructing perception.

Seeing seems effortless, despite the need to segregate and integrate visual information that varies in quality, quantity, and location. The extent to which seeing passively recapitulates the external world is challenged by phenomena such as illusory contours, an example of visual completion whereby borders are perceived despite their physical absence in the image. Instead, visual completion and seeing are increasingly conceived as active processes, dependent on information exchange across neural populations. How this is instantiated in the brain remains controversial. Divergent models emanate from single-unit and population-level electrophysiology, neuroimaging, and neurostimulation studies. We reconcile discrepant findings from different methods and disciplines, and underscore the importance of taking into account spatiotemporal brain dynamics in generating models of brain function and perception.