The primary aim of the study was to evaluate the incidence of de novo major involvement during follow-up in a cohort of patients with Behçet's syndrome (BS); the secondary aim was to analyse the epidemiological profile and the long-term outcome of those patients who developed new major involvement. Among our cohort of 120 BS patients, we evaluated all subjects who had no major organ involvement during the early years of their disease; specifically, at disease onset, the 52% of the cohort presented a prevalent mucocutaneous involvement. The primary outcomes were represented by the following: Hatemi et al. (Rheum Dis Clin North Am 39(2):245-61, 2013) the incidence of de novo major involvement during the follow-up and Hatemi et al. (Clin Exp Rheumatol 32(4 Suppl 84):S112-22, 2014) the use of immunosuppressive drugs during the follow-up. We have defined the development of de novo major involvement during the follow-up as the occurrence of severe ocular, vascular or CNS involvement after a latency period from the diagnosis of at least 3 years. Among 62 patients characterized by a mild onset of disease, we observed that after at least 3 years from the diagnosis, 21 BS patients (34%) still developed serious morbidities. Specifically, three patients developed ocular involvement, nine patients developed neurological involvement and nine patients presented vascular involvement. Comparing main epidemiological and clinical findings of the two groups, we observed that patients who developed de novo major involvement were more frequently males and younger; furthermore, 95% of these patients were characterized by a young onset of disease (p < 0.001). Being free of major organ complication in the first years of BS is not necessary a sign of a favourable outcome. Globally, the development of de novo major involvement during the coursfce of BS suggests that a tight control is strongly recommended during the course of the disease.

Background: A fair amount of microcalcifications sent for biopsy are false positives. The study investigates whether quantitative radiomic features extracted from digital breast tomosynthesis (DBT) can be an additional and useful tool to discriminate between benign and malignant BI-RADS category 4 microcalcification. Methods: This retrospective study included 252 female patients with BI-RADS category 4 microcalcifications. The patients were divided into two groups according to micro-histopathology: 126 patients with benign lesions and 126 patients with certain or possible malignancies. A total of 91 radiomic features were extracted for each patient, and the 12 most representative features were selected by using the agglomerative hierarchical clustering method. The binary classification task of the two groups was carried out by using four different machine-learning algorithms (i.e., linear support vector machine (SVM), radial basis function (RBF) SVM, logistic regression (LR), and random forest (RF)). Accuracy, sensitivity, sensibility, and the area under the curve (AUC) were calculated for each of them. Results: The best performance was achieved using the RF classifier (AUC = 0.59, 95% confidence interval 0.57–0.60; sensitivity = 0.56, 95% CI 0.54–0.58; specificity = 0.61, 95% CI 0.59–0.63; accuracy = 0.58, 95% CI 0.57–0.59). Conclusions: DBT-based radiomic analysis seems to have only limited potential in discriminating benign from malignant microcalcifications.

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