Health technology assessment to employ COVID-19 serological tests as companion diagnostics in the vaccination campaign against SARS-CoV-2.

OBJECTIVES: In scenarios of vaccine scarcity or contexts of organizational complexity, it is necessary to define prioritization strategies for allocating vaccine doses in compliance with the criterion of equity and efficiency of health resources. In this context, the COVIDIAGNOSTIX project, based on the health technology assessment (HTA), assessed the role of SARS-CoV-2 serological tests as a companion diagnostic in the definition of the vaccination strategies for the vaccine administration. To guarantee evidence support for health policy choices, two different vaccine strategies were analyzed, one based on administering the vaccine booster dose to the entire population (VACCINE strategy) and the other based on allocation criteria (TEST&VACCINE strategy). METHODS: The decision-oriented HTA (DoHTA) method, integrated with specific modeling and simulation techniques, helped define the perimeter to make health policy choices. RESULTS: The processing of the scores attributed to the key performance indicators concerning all the evaluation domains shows a performance of 94.34% for the TEST&VACCINE strategy and 83.87% for the VACCINE strategy. CONCLUSIONS: TEST&VACCINE strategy can be the most advantageous in various scenarios due to greater speed from an operational and an economic point of view. The assessment schemes defined by COVIDIAGNOSTIX (i.e., technologies/intended use/settings) can easily and quickly be exported and adapted to respond to similar health "policy questions".

COVIDIAGNOSTIX: health technology assessment of serological tests for SARS-CoV-2 infection.

OBJECTIVE: In vitro diagnostic tests for SARS-COV-2, also known as serological tests, have rapidly spread. However, to date, mostly single-center technical and diagnostic performance's assessments have been carried out without an intralaboratory validation process and a health technology assessment (HTA) systematic approach. Therefore, the rapid HTA for evaluating antibody tests for SARS-COV-2 was applied. METHODS: The use of rapid HTA is an opportunity to test innovative technology. Unlike traditional HTA (which evaluates the benefits of new technologies after being tested in clinical trials or have been applied in practice for some time), the rapid HTA is performed during the early stages of developing new technology. A multidisciplinary team conducted the rapid HTA following the HTA Core Model® (version 3.0) developed by the European Network for Health Technology Assessment. RESULTS: The three methodological and analytical steps used in the HTA applied to the evaluation of antibody tests for SARS-COV-2 are reported: the selection of the tests to be evaluated; the research and collection of information to support the adoption and appropriateness of the technology; and the preparation of the final reports and their dissemination. Finally, the rapid HTA of serological tests for SARS-CoV-2 is summarized in a report that allows its dissemination and communication. CONCLUSIONS: The rapid-HTA evaluation method, in addition to highlighting the characteristics that differentiate the tests from each other, guarantees a timely and appropriate evaluation, becoming a tool to create a direct link between science and health management.

HEALTH TECHNOLOGY ASSESSMENT METHODS GUIDELINES FOR MEDICAL DEVICES: HOW CAN WE ADDRESS THE GAPS? THE INTERNATIONAL FEDERATION OF MEDICAL AND BIOLOGICAL ENGINEERING PERSPECTIVE.

OBJECTIVES: Current health technology assessment (HTA) methods guidelines for medical devices may benefit from contributions by biomedical and clinical engineers. Our study aims to: (i) review and identify gaps in the current HTA guidelines on medical devices, (ii) propose recommendations to optimize the impact of HTA for medical devices, and (iii) reach a consensus among biomedical engineers on these recommendations. METHODS: A gray literature search of HTA agency Web sites for assessment methods guidelines on devices was conducted. The International Federation of Medical and Biological Engineers (IFMBE) then convened a structured focus group, with experts from different fields, to identify potential gaps in the current HTA guidelines, and to develop recommendations to fill these perceived gaps. The thirty recommendations generated from the focus group were circulated in a Delphi survey to eighty-five biomedical and clinical engineers. RESULTS: Thirty-two panelists, from seventeen countries, participated in the Delphi survey. The responses showed a strong agreement on twenty-seven of thirty recommendations. Some uncertainties remain about the methods to accurately assess the effectiveness and safety, and interoperability of a medical device with other devices or within the clinical setting. CONCLUSIONS: As medical devices differ from drug therapies, current HTA methods may not accurately reflect the conclusions of their assessment. Recommendations informed by the focus group discussions and Delphi survey responses aimed to address the perceived gaps, and to provide a more integrated approach in medical device assessments in combining engineering with other perspectives, such as clinical, economic, patient, human factors, ethical, and environmental.

Experimental application of Business Process Management technology to manage clinical pathways: a pediatric kidney transplantation follow up case.

BACKGROUND: To test the application of Business Process Management technology to manage clinical pathways, using a pediatric kidney transplantation as case study, and to identify the benefits obtained from using this technology. METHODS: Using a Business Process Management platform, we implemented a specific application to manage the clinical pathway of pediatric patients, and monitored the activities of the coordinator in charge of the case management during a 6-month period (from June 2015 to November 2015) using two methodologies: the traditional procedure and the one under study. RESULTS: The application helped physicians and nurses to optimize the amount of time and resources devoted to management purposes. In particular, time reduction was close to 60%. In addition, the reduction of data duplication, the integrated event management and the efficient data collection improved the quality of the service. CONCLUSIONS: The use of Business Process Management technology, usually related to well-defined processes with high management costs, is an established procedure in multiple environments; its use in healthcare, however, is innovative. The use of already accepted clinical pathways is known to improve outcomes. The combination of these two techniques, well established in their respective areas of application, could represent a revolution in clinical pathway management. The study has demonstrated that the use of this technology in a clinical environment, using a proper architecture and identifying a well-defined process, leads to real benefits in terms of resources optimization and quality improvement.

A comparative cost analysis of robotic-assisted surgery versus laparoscopic surgery and open surgery: the necessity of investing knowledgeably.

BACKGROUND: Robotic surgery has been proposed as a minimally invasive surgical technique with advantages for both surgeons and patients, but is associated with high costs (installation, use and maintenance). The Health Technology Assessment Unit of the Bambino Gesù Children's Hospital sought to investigate the economic sustainability of robotic surgery, having foreseen its impact on the hospital budget METHODS: Break-even and cost-minimization analyses were performed. A deterministic approach for sensitivity analysis was applied by varying the values of parameters between pre-defined ranges in different scenarios to see how the outcomes might differ. RESULTS: The break-even analysis indicated that at least 349 annual interventions would need to be carried out to reach the break-even point. The cost-minimization analysis showed that robotic surgery was the most expensive procedure among the considered alternatives (in terms of the contribution margin). CONCLUSIONS: Robotic surgery is a good clinical alternative to laparoscopic and open surgery (for many pediatric operations). However, the costs of robotic procedures are higher than the equivalent laparoscopic and open surgical interventions. Therefore, in the short run, these findings do not seem to support the decision to introduce a robotic system in our hospital.

[Exposure to hand-arm vibrations in orthopaedic plaster room: risk management]. / Esposizione a vibrazioni mano-braccio nel personale di sala gessi: risk management.

BACKGROUND: In hospitals, the use of vibrating tools, such as oscillating saws to cut plaster, can expose the staff to hand-arm vibrations. OBJECTIVES: The aim of the study was to assess the exposure of workers to vibrations in the plaster room and then  identify the most appropriate  intervention for  prevention and protection to be implemented in order to minimize  exposure and  protect  workers' health, considering different individual hyper-susceptibility conditions. METHODS: Four different models of plaster saws were examined for the evaluation.  Various measurements were made in normal working conditions of the operators. RESULTS AND CONCLUSIONS: The values of acceleration and noise detected on the instruments  were  in line with those reported in the literature. The preventive measure adopted (replacing plaster saws currently used in the hospital with similar ones with lower vibration emission) was an adequate means of protection. Health surveillance activities  recorded a higher level of wellbeing, both environmentally and individually and, specifically, an increased protection level for the hyper-susceptibility conditions observed during health checks of exposed personnel  which will be monitored regularly by the Occupational Health Service.

Decision-Oriented Health Technology Assessment: One Step Forward in Supporting the Decision-Making Process in Hospitals.

OBJECTIVES: This article outlines the Decision-Oriented Health Technology Assessment: a new implementation of the European network for Health Technology Assessment Core Model, integrating the multicriteria decision-making analysis by using the analytic hierarchy process to introduce a standardized methodological approach as a valued and shared tool to support health care decision making within a hospital. METHODS: Following the Core Model as guidance (European network for Health Technology Assessment. HTA core model for medical and surgical interventions. Available from: http://www.eunethta.eu/outputs/hta-core-model-medical-and-surgical-interventions-10r. [Accessed May 27, 2014]), it is possible to apply the analytic hierarchy process to break down a problem into its constituent parts and identify priorities (i.e., assigning a weight to each part) in a hierarchical structure. Thus, it quantitatively compares the importance of multiple criteria in assessing health technologies and how the alternative technologies perform in satisfying these criteria. The verbal ratings are translated into a quantitative form by using the Saaty scale (Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci 2008;1:83-98). An eigenvectors analysis is used for deriving the weights' systems (i.e., local and global weights' system) that reflect the importance assigned to the criteria and the priorities related to the performance of the alternative technologies. RESULTS: Compared with the Core Model, this methodological approach supplies a more timely as well as contextualized evidence for a specific technology, making it possible to obtain data that are more relevant and easier to interpret, and therefore more useful for decision makers to make investment choices with greater awareness. CONCLUSIONS: We reached the conclusion that although there may be scope for improvement, this implementation is a step forward toward the goal of building a "solid bridge" between the scientific evidence and the final decision maker's choice.

Adopting European Network for Health Technology Assessments (EunetHTA) core model for diagnostic technologies for improving the accuracy and appropriateness of blood gas analyzers' assessment.

BACKGROUND: Point-of-care testing (POCT) is a successful methodology for meeting clinical expectations of rapid and accurate results. Scientific literature has moreover highlighted and confirmed the necessity of individuating the best technological solution, in accordance with clinical requirements and contextualized to the whole health organization, where it will be implemented. Health Technology Assessment (HTA) can assist in reaching an appropriate and contextualized decision on a health technology. The aim of this study is to adapt a HTA core model for improving the evaluation of a POCT technology: blood gas analyzers. METHODS: The European Network for Health Technology Assessment (EUnetHTA) core model for diagnostic technologies was applied for evaluating globally marketed blood gas analyzers. Evaluation elements were defined according to available literature and validated using the Delphi method. RESULTS: A HTA model of 71 issues, subdivided into 26 topics and 10 domains, was obtained by interviewing 11 healthcare experts over two rounds of Delphi questionnaires. Ten context parameters were identified in order to define the initial scenario from which the technology assessment was to begin. CONCLUSIONS: The model presented offers a systematic and objective structure for the evaluation of blood gas analyzers, which may play a guidance role for healthcare operators approaching the evaluation of such technologies thus improving, in a contextualized fashion, the appropriateness of purchasing.

Semiautomated external defibrillators for in-hospital early defibrillation: a comparative study.

OBJECTIVES: Semiautomated external defibrillators (AEDs) should be considered as a means to facilitate in-hospital early defibrillation (IHED) in areas where advanced life support rescuers are not readily available. In this study, we aimed to develop a checklist and a measurement protocol to evaluate and compare AEDs by assessing factors that may affect IHED. METHODS: A clinical and technical comparison of six AEDs was performed. Technical specifications were analyzed, while an emergency team evaluated ergonomics and appropriateness for IHED at Bambino Gesù Children's Hospital. A measurement protocol was implemented, which aimed to assess the ability of defibrillators to recognize shockable and nonshockable rhythms, accuracy of delivered energy, and charging time. RESULTS: Designs of AEDs differed in several features which influence their appropriateness for IHED. Some units showed poor ergonomics and instructions/feedback for cardiopulmonary resuscitation. Differences between defibrillators in recognizing shockable and nonshockable rhythms emerged for polymorphic ventricular tachycardia waveforms and when the frequency and amplitude of input signals varied. Tests for accuracy revealed poor performances at low and high impedance levels for most AEDs. Notably, differences greater than 20 seconds were found in the time from power-on to "ready for discharge." CONCLUSIONS: The approach we used to assess AEDs allowed us to evaluate their appropriateness with respect to the organizational context, to measure their parameters, and to compare models. Results showed that ergonomics and/or performances (timing and accuracy) could be improved in each device.

Are the variations in ECG morphology associated to different blood glucose levels? implications for non-invasive glucose monitoring for T1D paediatric patients.

AIMS: Recent clinical trials and real-world studies highlighted those variations in ECG waveforms and HRV recurrently occurred during hypoglycemic and hyperglycemic events in patients with diabetes. However, while several studies have been carried out for adult age, there is lack of evidence for paediatric patients. The main aim of the study is to identify the correlations of variations in ECG Morphology waveforms with blood glucose levels in a paediatric population. METHODS: T1D paediatric patients who use CGM were enrolled. They wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glucose metrics, ECG parameters and HRV features were collected, and Wilcoxon rank-sum test and Spearman's correlation analysis were used to explore if different levels of blood glucose were associated to ECG morphological changes. RESULTS: Results showed that hypoglycaemic events in paediatric patients with T1D are strongly associated with variations in ECG morphology and HRV. CONCLUSIONS: Results showed the opportunity of using the ECG as a non-invasive adding instrument to monitor the hypoglycaemic events through the integration of the ECG continuous information with CGM data. This innovative approach represents a promising step forward in diabetes management, offering a more comprehensive and effective means of detecting and responding to critical changes in glucose levels.

Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol.

Purpose: Paediatric Type 1 Diabetes (T1D) patients are at greater risk for developing severe hypo and hyperglycaemic events due to poor glycaemic control. To reduce the risk of adverse events, patients need to achieve the best possible glycaemic management through frequent blood glucose monitoring with finger prick or Continuous Glucose Monitoring (CGM) systems. However, several non-invasive techniques have been proposed aiming at exploiting changes in physiological parameters based on glucose levels. The overall objective of this study is to validate an artificial intelligence (AI) based algorithm to detect glycaemic events using ECG signals collected through non-invasive device. Methods: This study will enrol T1D paediatric participants who already use CGM. Participants will wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glycaemic measurements driven through ECG variables are the main outcomes. Data collected will be used to design, develop and validate the personalised and generalized classifiers based on a deep learning (DL) AI algorithm, able to automatically detect hypoglycaemic events by using few ECG heartbeats recorded with wearable devices. Results: Data collection is expected to be completed approximately by June 2023. It is expected that sufficient data will be collected to develop and validate the AI algorithm. Conclusion: This is a validation study that will perform additional tests on a larger diabetes sample population to validate the previous pilot results that were based on four healthy adults, providing evidence on the reliability of the AI algorithm in detecting glycaemic events in paediatric diabetic patients in free-living conditions. Trial registration: ClinicalTrials.gov identifier: NCT03936634. Registered on 11 March 2022, retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT05278143?titles=AI+for+Glycemic+Events+Detection+Via+ECG+in+a+Pediatric+Population&draw=2&rank=1. Supplementary information: The online version contains supplementary material available at 10.1007/s12553-022-00719-x.

A simulation model estimates lifetime health and economic outcomes of screening prediabetes using the 1-h plasma glucose.

AIMS: The current method to diagnose impaired glucose tolerance (IGT) is based on the 2-h plasma glucose (2-hPG) value during a 75-g oral glucose tolerance test (OGTT). Robust evidence demonstrates that the 1-h post-load plasma glucose (1-hPG) ≥ 8.6 mmol/L in those with normal glucose tolerance is highly predictive of type 2 diabetes (T2D), micro and macrovascular complications and mortality. The aim of this study was to conduct a health economic analysis to estimate long-term cost-effectiveness of using the 1-hPG compared to the 2-hPG for screening and assessing the risk of diabetes over 35 years. The main outcome was cost per quality-adjusted life year (QALY) gained. METHODS: A Monte Carlo-based Markov simulation model was developed to forecast long-term effects of two screening strategies with regards to clinical and cost-effectiveness outcomes. The base case model included 20,000 simulated patients over 35-years follow-up. Transition probabilities on disease progression, mortality, effects on preventive treatments and complications were retrieved from landmark diabetes studies. Direct medical costs were sourced from published literature and inflated to 2019 Euros. RESULTS: In the lifetime analysis, the 1-hPG was projected to increase the number of years free from disease (2 years per patient); to delay the onset of T2D (1 year per patient); to reduce the incidence of T2D complications (0·6 RR-Relative Risk per patient) and to increase the QALY gained (0·58 per patient). Even if the 1-hPG diagnostic method resulted in higher initial costs associated with preventive treatment, long-term diabetes-related costs as well as complications costs were reduced leading to a lifetime saving of - 31225719.82€. The incremental cost-effectiveness ratio was - 8214.7€ per each QALY gained for the overall population. CONCLUSIONS: Screening prediabetes with the 1-hPG is feasible and cost-effective resulting in reduced costs per QALY. Notwithstanding, the higher initial costs of testing with the 1-hPG compared to the 2-hPG due to incremental preventive intervention, long-term diabetes and complications costs were reduced projecting an overall cost saving of - 8214.7€ per each QALY gained.

AI and High-Grade Glioma for Diagnosis and Outcome Prediction: Do All Machine Learning Models Perform Equally Well?

Radiomic models outperform clinical data for outcome prediction in high-grade gliomas (HGG). However, lack of parameter standardization limits clinical applications. Many machine learning (ML) radiomic models employ single classifiers rather than ensemble learning, which is known to boost performance, and comparative analyses are lacking in the literature. We aimed to compare ML classifiers to predict clinically relevant tasks for HGG: overall survival (OS), isocitrate dehydrogenase (IDH) mutation, O-6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, epidermal growth factor receptor vIII (EGFR) amplification, and Ki-67 expression, based on radiomic features from conventional and advanced magnetic resonance imaging (MRI). Our objective was to identify the best algorithm for each task. One hundred fifty-six adult patients with pathologic diagnosis of HGG were included. Three tumoral regions were manually segmented: contrast-enhancing tumor, necrosis, and non-enhancing tumor. Radiomic features were extracted with a custom version of Pyradiomics and selected through Boruta algorithm. A Grid Search algorithm was applied when computing ten times K-fold cross-validation (K=10) to get the highest mean and lowest spread of accuracy. Model performance was assessed as AUC-ROC curve mean values with 95% confidence intervals (CI). Extreme Gradient Boosting (xGB) obtained highest accuracy for OS (74,5%), Adaboost (AB) for IDH mutation (87.5%), MGMT methylation (70,8%), Ki-67 expression (86%), and EGFR amplification (81%). Ensemble classifiers showed the best performance across tasks. High-scoring radiomic features shed light on possible correlations between MRI and tumor histology.

Spatial Stability of Functional Networks: A Measure to Assess the Robustness of Graph-Theoretical Metrics to Spatial Errors Related to Brain Parcellation.

There is growing interest in studying human brain connectivity and in modelling the brain functional structure as a network. Brain network creation requires parcellation of the cerebral cortex to define nodes. Parcellation might be affected by possible errors due to inter- and intra-subject variability as a consequence of brain structural and physiological characteristics and shape variations related to ageing and diseases, acquisition noise, and misregistration. These errors could induce a knock-on effect on network measure variability. The aim of this study was to investigate spatial stability, a measure of functional connectivity variations induced by parcellation errors. We simulated parcellation variability with random small spatial changes and evaluated its effects on twenty-seven graph-theoretical measures. The study included subjects from three public online datasets. Two brain parcellations were performed using FreeSurfer with geometric atlases. Starting from these, 100 new parcellations were created by increasing the area of 30% of parcels, reducing the area of neighbour parcels, with a rearrangement of vertices. fMRI data were filtered with linear regression, CompCor, and motion correction. Adjacency matrices were constructed with 0.1, 0.2, 0.3, and 0.4 thresholds. Differences in spatial stability between datasets, atlases, and threshold were evaluated. The higher spatial stability resulted for Characteristic-path-length, Density, Transitivity, and Closeness-centrality, and the lower spatial stability resulted for Bonacich and Katz. Multivariate analysis showed a significant effect of atlas, datasets, and thresholds. Katz and Bonacich centrality, which was subject to larger variations, can be considered an unconventional graph measure, poorly implemented in the clinical field and not yet investigated for reliability assessment. Spatial stability (SS) is affected by threshold, and it decreases with increasing threshold for several measures. Moreover, SS seems to depend on atlas choice and scanning parameters. Our study highlights the importance of paying close attention to possible parcellation-related spatial errors, which may affect the reliability of functional connectivity measures.

Health Technology Assessment of Intensive Care Ventilators for Pediatric Patients.

This paper is aimed at addressing all the critical aspects linked to the implementation of intensive care ventilators in a pediatric setting, highlighting the most relevant technical features and describing the methodology to conduct health technology assessment (HTA) for supporting the decision-making process. Four ventilator models were included in the assessment process. A decision-making support tool (DoHTA method) was applied. Twenty-eight Key Performance Indicators (KPIs) were identified, defining the safety, clinical effectiveness, organizational, technical, and economic aspects. The Performance scores of each ventilator have been measured with respect to KPIs integrated with the total cost of ownership analysis, leading to a final rank of the four possible technological solutions. The final technologies' performance scores reflected a deliver valued, contextualized, and shared outputs, detecting the most performant technological solution for the specific hospital context. HTA results had informed and supported the pediatric hospital decision-making process. This study, critically identifying the pros and cons of innovative features of ventilators and the evaluation criteria and aspects to be taken into account during HTA, can be considered as a valuable proof of evidence as well as a reliable and transferable method for conducting decision-making processes in a hospital context.

Correction to: Clinical needs and technical requirements for ventilators for COVID-19 treatment critical patients: an evidence-based comparison for adult and pediatric age.

[This corrects the article DOI: 10.1007/s12553-020-00467-w.].

Clinical needs and technical requirements for ventilators for COVID-19 treatment critical patients: an evidence-based comparison for adult and pediatric age.

The spread of severe acute respiratory syndrome coronavirus 2, taking on pandemic proportions, is placing extraordinary and unprecedented demands on healthcare systems worldwide. The increasing number of critical patients who, experiencing respiratory failure from acute respiratory distress syndrome, need respiratory support, has been leading countries to race against time in arranging new Intensive Care Units (ICUs) and in finding affordable and practical solutions to manage patients in each stage of the disease. The simultaneous worldwide emergency caused serious problems for mechanical ventilators supply. This chaotic scenario generated, indeed, a frenetic race to buy life-saving ventilators. However, the variety of mechanical ventilators designs, together with the limitations in time and resources, make the decision-making processes on ventilators procurement crucial and not counterbalanced by the evaluation of devices quality. This paper aimed at offering an overview of how evidence-based approach for health technologies evaluation, might provide support during Corona Virus Disease 2019 (COVID-19) pandemic in ICUs management and critical equipment supply. We compared and combined all the publicly available indications on the essential requirements that ICU ventilators might meet to be considered acceptable for treating COVID-19 patients in severe to critical illnesses. We hope that the critical analysis of these data might help readers to understand how structured decision-making processes based on evidence, evaluating the safety and effectiveness of a given medical device and the effects of its introduction in a healthcare setting, are able to optimize time and resources allocation that should be considered essential, especially during pandemic period.

Robotic Technology in Pediatric Neurorehabilitation. A Pilot Study of Human Factors in an Italian Pediatric Hospital.

The introduction of robotic neurorehabilitation among the most recent technologies in pediatrics represents a new opportunity to treat pediatric patients. This study aims at evaluating the response of physiotherapists, patients and their parents to this new technology. The study considered the outcomes of technological innovation in physiotherapists (perception of the workload, satisfaction), as well as that in patients and their parents (quality of life, expectations, satisfaction) by comparing the answers to subjective questionnaires of those who made use of the new technology with those who used the traditional therapy. A total of 12 workers, 46 patients and 47 parents were enrolled in the study. Significant differences were recorded in the total workload score of physiotherapists who use the robotic technology compared with the traditional therapy (p < 0.001). Patients reported a higher quality of life and satisfaction after the use of the robotic neurorehabilitation therapy. The parents of patients undergoing the robotic therapy have moderately higher expectations and satisfaction than those undergoing the traditional therapy. In this pilot study, the robotic neurorehabilitation technique involved a significant increase in the patients' and parents' expectations. As it frequently happens in the introduction of new technologies, physiotherapists perceived a greater workload. Further studies are needed to verify the results achieved.

Direction selectivity of simple cells in the primary visual cortex: comparison of two alternative mathematical models. I: response to drifting gratings.

Two models of a single hypercolumn in the primary visual cortex are presented, and used for the analysis of direction selectivity in simple cells. The two models differ as to the arrangement of inhibitory connections: in the first ("antiphase model") inhibition is in phase opposition with excitation, but with a similar orientation tuning; in the second ("in-phase model"), inhibition is in phase with excitation, but with broader orientation tuning. Simulation results, performed by using drifting gratings with different orientations, and different spatial and temporal frequencies, show that both models are able to explain the origin of direction preference of simple cells.

Supporting clinical engineering in Italy: results of a survey conducted by the AIIC.

This article presents the outcomes of a survey developed and conducted by the Italian Association of Clinical Engineers (AIIC) in 2010 [1]. The AIIC, affiliated with the International Federation for Medical and Biological Engineering (IFMBE) since 2003, conducted this in-depth survey to investigate the educational profile of clinical engineers (CEs) as well as the activities and organization of clinical engineering departments (CEDs) in Italy. The survey consisted of a six-section questionnaire designed by the AIIC Board, which was based on other previous international surveys of CEDs. The questionnaire was sent to the AIIC members and to the most important Italian health-care organizations.