Mastocytosis: a Rare Case of Anaphylaxis in Paediatric Age and Literature Review

The term “mastocytosis” denotes a heterogeneous group of disorders characterised by abnormal growth and accumulation of mast cells (MC) in one or more organ systems. Symptoms result from MC chemical mediator’s release, pathologic infiltration of neoplastic MC in tissues or both. Multiple molecular, genetic and chromosomal defects seem to contribute to an autonomous growth, but somatic c-kit D816V mutation is more frequently encountered, especially in systemic disease. We present a literature review of mastocytosis and a rare case report of an 18 month-old-girl with a bullous dermatosis, respiratory distress and anaphylaxis, as clinical manifestations of mastocytosis. The developments of accepted classification systems and novel useful markers allowed a re-evaluation and updating of the classification of mastocytosis. In paediatric age cutaneous forms of disease prevail and may regress spontaneously. SM is more frequently diagnosed in adults and is a persistent(clonal) disease of bone marrow. The clinical course in these patients is variable.Today diagnostic criteria for each disease variant are reasonably well defined. There are, however, peculiarities, namely in paediatric age, that makes the diagnostic approach difficult. Systemic disease may pose differential diagnostic problems resulting from multiple organ systems involvement. Coversly, the “unexplained” appearance of those symptoms with no skin lesions should raise the suspicion of MC disease. This case is reported in order to stress the clinical severity and difficult diagnostic approach that paediatric mastocytosis may assume.

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.