The primacy of multiparametric MRI in men with suspected prostate cancer

Background: Multiparametric MRI (mpMRI) became recognised in investigating those with suspected prostate cancer between 2010 and 2012; in the USA, the preventative task force moratorium on PSA screening was a strong catalyst. In a few short years, it has been adopted into daily urological and oncological practice. The pace of clinical uptake, born along by countless papers proclaiming high accuracy in detecting clinically significant prostate cancer, has sparked much debate about the timing of mpMRI within the traditional biopsy-driven clinical pathways. There are strongly held opposing views on using mpMRI as a triage test regarding the need for biopsy and/or guiding the biopsy pattern. Objective: To review the evidence base and present a position paper on the role of mpMRI in the diagnosis and management of prostate cancer. Methods: A subgroup of experts from the ESUR Prostate MRI Working Group conducted literature review and face to face and electronic exchanges to draw up a position statement. Results: This paper considers diagnostic strategies for clinically significant prostate cancer; current national and international guidance; the impact of pre-biopsy mpMRI in detection of clinically significant and clinically insignificant neoplasms; the impact of pre-biopsy mpMRI on biopsy strategies and targeting; the notion of mpMRI within a wider risk evaluation on a patient by patient basis; the problems that beset mpMRI including inter-observer variability. Conclusions: The paper concludes with a set of suggestions for using mpMRI to influence who to biopsy and who not to biopsy at diagnosis. Key Points: • Adopt mpMRI as the first, and primary, investigation in the workup of men with suspected prostate cancer. • PI-RADS assessment categories 1 and 2 have a high negative predictive value in excluding significant disease, and systematic biopsy may be postponed, especially in men with low-risk of disease following additional risk stratification. • PI-RADS assessment category lesions 4 and 5 should be targeted; PI-RADS assessment category lesion 3 may be biopsied as a target, as part of systematic biopsies or may be observed depending on risk stratification

Should we perform multiparametric magnetic resonance imaging of the bladder before transurethral resection of bladder? Time to reconsider the rules

We would like to congratulate Ueno and colleagues [1] on their paper on diagnostic accuracy and interobserver agreement for the new Vesical Imaging-Reporting and Data System (VI-RADS) [2] for muscle-invasive bladder cancer (MIBC) in this issue of European Urology. Their report on 74 patients who underwent multiparametric magnetic resonance imaging (mpMRI) before transurethral resection of bladder tumor (TURBT) raises great interest in the RADS (Reporting and Data Systems) era. They address the questions of reproducibility and diagnostic performance of mpMRI in the setting of bladder ca (BC), in which potential applications of this imaging technique have seen constant growth in the past decades without a definitive role having been identified

A new approach to modelling the shelf life of Gilthead seabream (Sparus aurata)

A total of 217 Gilthead seabreams were subdivided in four groups, according to four different storage conditions. All fish were evaluated by both Quality Index Method (QIM) and microbiological analysis, sampling skin, gills and flesh, separately. A QIM score predictive system was set by modelling the growth of microflora of skin, gills and flesh and coupling these predictions to each related partial QIM score (QIMSkin, QIMGills, QIMFlesh). The expression of QIM score as a function of bacterial behaviour was carried out by the employment of two coefficients. The predicted mean bacterial concentrations corresponding to the QIM score at 14 days were always near to Log 8 CFU g^{ -1} in the case of 'S' (skin) and 'G' (gills) series. Moreover, predicted QIM scores were in a good agreement with observed data, reproducing the observed mean time of rejection as well as the bacterial spoilage level (Log 8 CFU g^{ -1}), for all kinds of storage condition

Analysis of gut microbiota in rheumatoid arthritis patients. Disease-related dysbiosis and modifications induced by etanercept

A certain number of studies were carried out to address the question of how dysbiosis could affect the onset and development of rheumatoid arthritis (RA), but little is known about the reciprocal influence between microbiota composition and immunosuppressive drugs, and how this interaction may have an impact on the clinical outcome. The aim of this study was to characterize the intestinal microbiota in a groups of RA patients treatment-naïve, under methotrexate, and/or etanercept (ETN). Correlations between the gut microbiota composition and validated immunological and clinical parameters of disease activity were also evaluated. In the current study, a 16S analysis was employed to explore the gut microbiota of 42 patients affected by RA and 10 healthy controls. Disease activity score on 28 joints (DAS-28), erythrocyte sedimentation rate, C-reactive protein, rheumatoid factor, anti-cyclic citrullinated peptides, and dietary and smoking habits were assessed. The composition of the gut microbiota in RA patients free of therapy is characterized by several abnormalities compared to healthy controls. Gut dysbiosis in RA patients is associated with different serological and clinical parameters; in particular, the phylum of Euryarchaeota was directly correlated to DAS and emerged as an independent risk factor. Patients under treatment with ETN present a partial restoration of a beneficial microbiota. The results of our study confirm that gut dysbiosis is a hallmark of the disease, and shows, for the first time, that the anti-tumor necrosis factor alpha (TNF-α) ETN is able to modify microbial communities, at least partially restoring a beneficial microbiota

Modelling Bacterial Dynamics in Food Products: Role of Environmental Noise and Interspecific Competition

In this paper we review some results obtained within the context of the predictive microbiology, which is a specific field of the population dynamics. In particular we discuss three models, which exploit tools of statistical mechanics, for bacterial dynamics in food of animal origin. In the first model, the random fluctuating behaviour, experimentally meas- ured, of the temperature is considered. In the second model stochastic differential equations are introduced to take into account the influence of physical and chemical variables, such as temperature, pH and activity water, subject to deter- ministic and random variations. The third model, which is an extended version of the second one, neglects the environ- mental fluctuations, and concentrates on the role of the interspecific bacterial interactions. The comparison between expected results and observed data indicates that the presence of noise sources and interspecific bacterial interactions improves the predictive features of the models analyzed

Development of a predictive model for the shelf-life of Atlantic mackerel (Scomber scombrus)

Despite its commercial value, the shelf-life of the Atlantic mackerel (Scomber scombrus) during refrigerated storage was poorly investigated. In this regard, the Quality Index Method (QIM) was proposed as a suitable scoring system for freshness and quality sensorial estimation of fishery products. This study aims to develop a deterministic mathematical model based on dynamic temperatures conditions and a suc-cessive statistical analysis of the results obtained. This model will be exploited to predict the shelf-life of the Atlantic mackerel based on specific storage temperatures. A total of 60 fresh fishes were subdivided into two groups and respectively stored in ice for 12 days at a constant temperature of 1±0.5°C (Group A) and a fluctuating temperature ranging between 1 and 7°C (Group B). Microbiological analysis and sensory evaluation through the QIM were performed on each fish at regular time inter-vals. A critical value of 6 Log cfu/g of spoilage bacteria (mainly psychotropic) associated with a significant decay of the sensorial characteristics was exceeded after 9 days of storage for Group A and 3 days for Group B. A reliable prediction of fish freshness was obtained by modelling the QIM as a function of the spoilage bacteria behaviour. A coefficient β of correlation was determined to convert the spoilage bacteria load into a Quality Index score. The adoption of mathematical predictive models to assess microbial behaviour under different environmental conditions is an interest-ing tool for food industries to maximize production and reduce waste