2 research outputs found

    Rak żołądka — opis przypadku

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    The article presents the case of an 80-year-old patient admitted to the Department of Gastroenterology, Internal Medicine and Dietetics in Poznań for the diagnosis of anaemia. The paper contains a short description of gastric cancer, etiology, diagnostics with an emphasis on a number of information particularly useful for family medicine doctors and treatment. The aim of the study is to emphasize the need for a multifaceted and multidisciplinary approach to a patient with a history of cancer.W artykule przedstawiono przypadek 80-letniego pacjenta przyjętego do Kliniki Gastroenterologii, Dietetyki i Chorób Wewnętrznych w Poznaniu w celu diagnostyki niedokrwistości. W pracy zawar to krótką charakterystykę raka żołądka, etiologię, diagnostykę z naciskiem na wiele informacji szczególnie przydatnych dla lekarzy medycyny rodzinnej, oraz leczenie. Celem pracy jest podkreślenie konieczności wieloaspektowego i wielodyscyplinarnego podejścia do pacjenta z wywiadem chorób nowotworowych

    The Usefulness of MRI Dynamic Flow Sequences in Differentiating High- and Low-Flow Vascular Malformations

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    Peripheral arteriovenous malformations (PVMs) can be classified into high-flow malformations (HFVMs) and low-flow malformations (LFVMs). Adequate distinguishment is crucial for therapeutic decision and can be done using dynamic contrast-enhanced MRI (DCE-MRI). The main aim of this retrospective study was to determine the diagnostic value of quantitative DCE-MRI ratios for differentiation between HFVM and LFVM, their optimal cut-off points, and predictive values. DCE-MRI time-resolved angiography with stochastic trajectory (TWIST) examinations of 90 patients with PVMs were included [28 HFVM (31%), 62 LFVM (69%)]. The measurements of artery-lesion time, maximum lesion enhancement, slope of the enhancement curve, and maximum percentage increase of signal intensity (SI) were obtained. The optimal cut-offs for HFVMs calculated using the Youden index were: for slope of enhancement curve 662% (sensitivity of 68%, specificity of 69%). To summarize, DCE-MRI is very valuable for differentiation between HFVM and LFVM, especially if quantitative measurements are done
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