Central diabetes insipidus and pituitary stalk thickening in adults: Distinction of neoplastic from non-neoplastic lesions

Context: Association of central diabetes insipidus (CDI) and pituitary stalk thickening (PST) may have several etiologies (including malignancies) and differential diagnosis remains often difficult. Objective: The purpose of this study was to identify which clinical, biochemical or radiological features could help clinicians to make an etiological diagnosis, especially distinguishing neoplastic from non-neoplastic pituitary stalk lesions. Design and methods: We retrospectively analyzed clinical, biochemical, radiological and histological data of 38 adult patients diagnosed with CDI and PST of proven etiology. Results: Of the 38 pituitary stalk lesions included, 11 (29%) were neoplastic. A histopathological diagnosis was obtained in 22/38 (58%) patients. The three most frequently observed etiologies of PST were neuroinfundibulitis (34%), germinoma (21%) and histiocytosis (18%). Pituitary stalk thickness was larger for neoplastic lesions, particularly germinomas. Male gender and a very young age were statistically associated with a risk of germinoma. At least one anterior pituitary deficit was observed in nearly 60% of patients. Patients with neoplastic PST were more affected by multiple anterior pituitary dysfunction than patients with benign PST. A high serum prolactin level was individually the best predictor of a neoplastic origin (90% sensitivity and 60% specificity for a serum prolactin level 1.27-fold above the normal upper limit (ULN)). Conclusion: We confirm a relatively high risk of malignancy in adult patients presenting with the association of CDI and PST. Young age, male gender, a very large thickening of the stalk, multiple anterior pituitary deficits and prolactin above 1.3× ULN increase the likelihood of a neoplastic origin.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

From Propositional Satisfiability to Satisfiability Modulo Theories

Abstract. In this paper we present a review of SAT-based approaches for building scalable and efficient decision procedures for quantifier-free first-order logic formulas in one or more decidable theories, known as Satisfiability Modulo Theories (SMT) problems. As applied to different system verification problems, SMT problems comprise of different theories including fragments of elementary theory of numbers, the theory of arrays, the theory of list structures, etc. In this paper we focus on different DPLL-style satisfiability procedures for decidable fragments of the theory of integers. Leveraging the advances made in SAT solvers in the past decade, we introduce several SAT-based SMT solving methods that in many applications have outperformed classical decision methods. Aside from the classical method of translating the SMT formula to a purely Boolean problem, in recent methods, a SAT solver is utilized to serve as the “glue ” that ties together the different theory atoms and forms the basis for reasoning and learning within and across them. Several methods have been developed to provide a combination framework for implications to flow through the theory solvers and to possibly activate other theory atoms based on the current assignments. Similarly, conflict-based learning is also extended to enable the creation of learned clauses comprising of the combination of theory atoms. Additional methods unique to one or more types of theory atoms have also been proposed that learn more expressive constraints and significantly increase the pruning power of these combination schemes. We will describe several combination strategies and their impact on scalability and performance of the overall solver in different settings and applications.

A Fast Linear-Arithmetic Solver for DPLL(T)

We present a new Simplex-based linear arithmetic solver that can be integrated efficiently in the DPLL(T) framework. The new solver improves over existing approaches by enabling fast backtracking, supporting a priori simplification to reduce the problem size, and providing an efficient form of theory propagation. We also present a new and simple approach for solving strict inequalities. Experimental results show substantial performance improvements over existing tools that use other Simplex-based solvers in DPLL(T) decision procedures. The new solver is even competitive with state-of-the-art tools specialized for the difference logic fragment