A public decision support system for the assessment of plant disease infection risk shared by Italian regions.

Integrated pest management (IPM) practices proved to be efficient in reducing pesticide use and ensuring economic farming sustainability. Digital decision support systems (DSS) to support the adoption of IPM practices from plant protection services are required by European legislation. Available DSSs used by Italian plant protection services are heterogeneous with regards to disease forecasting models, datasets for their calibration, and level of integration in operational decision-making. This study presents the MISFITS-DSS, which has been jointly developed by a public research institution and nine regional plant protection services with the objective of harmonizing data collection and decision support for Italian farmers. Participatory approach allowed designing a predictive workflow relying on specific domain expertise, in order to explicitly match actual user needs. The DSS calibration entailed the risk of grapevine downy mildew infection (5-point scale from very low to very high), and phenological observations in 2012-2017 as reference data. Process-based models of primary and secondary infections have been implemented and tested via sensitivity analysis (Morris method) under contrasting weather conditions. Hindcast simulations of grapevine phenology, host susceptibility and disease pressure were post-processed by machine-learning classifiers to predict the reference infection risk. Results indicate that IPM principles are implemented by plant protection services since years. The accurate reproduction of grapevine phenology (RMSE = 4-14 days), which drove the dynamic of host susceptibility, and the use of weather forecasts as model inputs contributed to reliably predict the reference infection risk (88% balanced accuracy). We did a pioneering effort to homogenize the methodology to deliver decision support to Italian farmers, by involving plant protection services in the DSS definition, to foster a further adoption of IPM practices.

Imaging of soft-tissue tumors.

The objective of this review is to highlight the major imaging characteristics of the main soft-tissue sarcoma histotypes observed in the group "Sarcomi" of the Istituto Oncologico Veneto in the last 5 years. A literature review was performed using PubMed and textbooks. Radiological imaging can guide the diagnosis for the subset of lesions that have typical clinical and imaging features. Soft-tissue tumors are common in clinical practice and a systematic clinical and imaging approach may guide the diagnosis.

Structured reporting using a shared indexed multilingual radiology lexicon.

PURPOSE: A system for creating structured reports (SRs) using a standardized radiology lexicon was developed and tested to facilitate automated translation of content and multidisciplinary international communications. METHODS: A database of radiology terms, RadLex developed by the Radiological Society of North America, was used to create a shared indexed multilingual radiology lexicon. A diagnostic workstation for generating structured reports (OpenEye) was implemented with a "RadLex manager" function for adding new words to the lexicon in both English and Italian. Sample reports of examinations included in the Medical Imaging Resource Center (MIRC) radiology imaging database of clinical cases were prepared using this system. The system was evaluated for teaching purposes and scientific dissemination. RESULTS: The OpenEye system was able to manage the glossary to create new SRs and manually translate existing reports containing freely worded descriptions. The OpenEye system provides instant translation from Italian into English and enables clinical cases to be published in the MIRC, while making them accessible for consultation on an international scale. CONCLUSION: The SR is advantageous compared with a freely worded report in terms of clarity and completeness of the content. Creating SRs for each clinical case enables rapid and focused analysis at multidisciplinary meetings. All our cases have been included in the MIRC database as part of a broader-based European Project for research on soft tissues sarcomas (CONTICANET).