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Spondylodiscitis is an infection of the intervertebral disc, the adjacent vertebral body, and/or contiguous structures due to the introduction of infectious agent, usually by the hematogenous route. Imaging is crucial in assessing bacterial and tubercular spondylodiscitis, as well as their associated complications. Magnetic resonance imaging in particular can clearly depict osteo-structural changes in the vertebral body and the associated disc, as well as any soft-tissue complications, such as paravertebral abscess and/or epidural abscess, improving disease characterization and helping to recognize the agent involved. Nevertheless, other non-infectious diseases may mimic imaging appearances of spondylodiscitis and one should be aware of these conditions when interpreting MR images, which include Modic type I degenerative changes, ankylosing spondylitis, acute Schmorl’s node, porotic fractures, and spinal neuropathy arthropathy. This pictorial review aims at describing imaging findings of bacterial and non-bacterial spondylodiscitis, complications, and those pathologies that mimic these infections.

The CT manifestation of COVID-19 patients is now well known and essentially reflects pathological changes in the lungs. Actually, there is insufficient knowledge on the long-term outcomes of this new disease, and several chest CTs might be necessary to evaluate the outcomes. The aim of this study is to evaluate the radiation dose for chest CT scans in COVID-19 patients compared to a cohort with pulmonary infectious diseases at the same time of the previous year to value if there is any modification of exposure dose. The analysis of our data shows an increase in the overall mean dose in COVID-19 patients compared with non-COVID-19 patients. In our results, the higher dose increase occurs in the younger age groups (+86% range 21–30 years and +67% range 31–40 years). Our results show that COVID-19 patients are exposed to a significantly higher dose of ionizing radiation than other patients without COVID infectious lung disease, and especially in younger age groups, although some authors have proposed the use of radiotherapy in these patients, which is yet to be validated. Our study has limitations: the use of one CT machine in a single institute and a limited number of patients.

Distributed power converters represent a technical solution to improve the performance of large or utility-scale photovoltaic (PV) plants. Unfortunately, evaluation of the yield obtained in large PV fields by using distributed converters is a difficult task because of recurring partial unavailability, inaccuracy of power analyzers, operating constraints imposed by the Power Plant Controller and so on. To overcome such issues in real operating scenarios, a new modeling strategy has been introduced and validated in terms of computational complexity and accuracy. This approach is based on the state-space averaging technique which is applied to large PV plants with multiple conversion stages by performing some elaborations in order to get a final integrated model. The new modeling strategy has been tested in MatLab Simulink environment using data coming from a 300 MW PV plant located in Brazil representing the case study of this work. In this plant, one subfield is equipped with central inverters while another is with string inverters. The proposed model, whose accuracy is in the range from 2.2 to 2.7% with respect to the measured energy, effectively supports data analysis leading to a consistent performance assessment for the distributed conversion system. Final results highlight that string inverters ensure a gain of about 2% in terms of produced energy.