AbstractObjectives: Overlapping decreases in extrastriatal dopamine D2/D3-receptor availability and glucose metabolism have been reported in subjects with schizophrenia. It remains unknown whether these findings are physiologically related or coincidental.Methods: To ascertain this, we used two consecutive 18F-fluorodeoxyglucose and 18F-fallypride positron emission tomography scans in 19 healthy and 25 unmedicated schizophrenia subjects. Matrices of correlations between 18F-fluorodeoxyglucose uptake and 18F-fallypride binding in voxels at the same xyz location and AFNI-generated regions of interest were evaluated in both diagnostic groups.Results:18F-fluorodeoxyglucose uptake and 18F-fallypride binding potential were predominantly positively correlated across the striatal and extrastriatal grey matter in both healthy and schizophrenia subjects. In comparison to healthy subjects, significantly weaker correlations in subjects with schizophrenia were confirmed in the right cingulate gyrus and thalamus, including the mediodorsal, lateral dorsal, anterior, and midline nuclei. Schizophrenia subjects showed decreased D2/D3-receptor availability in the hypothalamus, mamillary bodies, thalamus and several thalamic nuclei, and increased glucose uptake in three lobules of the cerebellar vermis.Conclusions: Dopaminergic system may be involved in modulation of grey matter metabolism and neurometabolic coupling in both healthy human brain and psychopathology. Hyperdopaminergic state in untreated schizophrenia may at least partly account for the corresponding decreases in grey matter metabolism. 相似文献
Graphical abstract summarizing the overall results of our study comparing reintervention for a main or central branch pulmonary artery reconstruction site and various patch materials. Autologous pericardium was associate with the lowest reintervention and was free. Multivariable analysis demonstrated lack of superiority of homograft branch patch, which clearly has a much higher cost.
AbstractObjective: To understand the origin of extremely high gonadotropin levels in a perimenopausal woman.Methods: A 52-year-old woman with a 2?months of amenorrhea followed spontaneous menstrual cycles recovery was referred to our outpatient clinic with elevated follicle-stimulating hormone (FSH, 483 mUI/ml), luteinizing hormone (LH, 475 mUI/ml) and prolactin (PRL, 173?ng/ml). She was known to take levosulpiride. The gonadotropin levels did not fit with the clinical features.Results: A gonadotroph tumor was ruled out. Further analysis confirmed constantly high FSH, LH and PRL levels. The measurements were repeated using different analytical platforms with different results. After serial dilutions, nonlinearity was present suggesting an immunoassay interference. After post-polyethylene glycol recovery, hormone levels appeared in the normal range. Anti-goat antibodies were recognized in the serum of the patient.Conclusions: This case report shows a case of falsely abnormal high gonadotropin and PRL levels in a woman during menopause transition. In the clinical practice the evaluation of gonadotropin profile is not recommended at this age, but the abnormal levels stimulated further evaluation. An interference in the assay due to anti-goat antibodies resulted in abnormally high level of FSH and LH. A strict collaboration between clinicians and the laboratory is needed, when laboratory findings do not correspond to clinical findings. 相似文献
BACKGROUND AND PURPOSE:Primary posterior fossa tumors comprise a large group of neoplasias with variable aggressiveness and short and long-term outcomes. This study aimed to validate the clinical usefulness of a radiologic decision flow chart based on previously published neuroradiologic knowledge for the diagnosis of posterior fossa tumors in children.MATERIALS AND METHODS:A retrospective study was conducted (from January 2013 to October 2019) at 2 pediatric referral centers, Children''s Hospital of Philadelphia, United States, and Great Ormond Street Hospital, United Kingdom. Inclusion criteria were younger than 18 years of age and histologically and molecularly confirmed posterior fossa tumors. Subjects with no available preoperative MR imaging and tumors located primarily in the brain stem were excluded. Imaging characteristics of the tumors were evaluated following a predesigned, step-by-step flow chart. Agreement between readers was tested with the Cohen κ, and each diagnosis was analyzed for accuracy.RESULTS:A total of 148 cases were included, with a median age of 3.4 years (interquartile range, 2.1–6.1 years), and a male/female ratio of 1.24. The predesigned flow chart facilitated identification of pilocytic astrocytoma, ependymoma, and medulloblastoma sonic hedgehog tumors with high sensitivity and specificity. On the basis of the results, the flow chart was adjusted so that it would also be able to better discriminate atypical teratoid/rhabdoid tumors and medulloblastoma groups 3 or 4 (sensitivity = 75%–79%; specificity = 92%–99%). Moreover, our adjusted flow chart was useful in ruling out ependymoma, pilocytic astrocytomas, and medulloblastoma sonic hedgehog tumors.CONCLUSIONS:The modified flow chart offers a structured tool to aid in the adjunct diagnosis of pediatric posterior fossa tumors. Our results also establish a useful starting point for prospective clinical studies and for the development of automated algorithms, which may provide precise and adequate diagnostic tools for these tumors in clinical practice.In the past 10 years, there has been an exponential increase in knowledge of the molecular characteristics of pediatric brain tumors, which was only partially incorporated in the 2016 World Health Organization Classification of Tumors of the Central Nervous System.1 The main update in the 2016 Classification was the introduction of the molecular profile of a tumor as an important factor for predicting different biologic behaviors of entities which, on histology, look very similar or even indistinguishable.2 A typical example is the 4 main groups of medulloblastoma: wingless (WNT), sonic hedgehog (SHH) with or without the p53 mutation, group 3, and group 4. Although they may appear similar on microscopy, these categories have distinct molecular profiles, epidemiology, prognosis, and embryologic origin.3Subsequent to the publication of the 2016 World Health Organization Classification, further studies have identified even more molecular subgroups of medulloblastoma with possible prognostic implications4 and also at least 3 new molecular subgroups of atypical teratoid/rhabdoid tumor (AT/RT)5 and several subgroups of ependymoma.6 MR imaging shows promise as a technique for differentiating histologic tumors and their molecular subgroups. This capability relies on not only various imaging characteristics but also the location and spatial extension of the tumor, evident on MR imaging, which can be traced to the embryologic origin of the neoplastic cells.5,7-10One approach to the challenge of identifying imaging characteristics of different tumors in children is to use artificial intelligence. Yet despite this exciting innovation, correctly identifying the location of the mass and its possible use as an element for differential diagnosis still requires the expertise of an experienced radiologist. Previously, D''Arco et al11 proposed a flow chart (Fig 1) for the differential diagnosis of posterior fossa tumors in children based on epidemiologic, imaging signal, and location characteristics of the neoplasm. The aims of the current study were the following: 1) to validate, in a retrospective, large cohort of posterior fossa tumors from 2 separate pediatric tertiary centers, the diagnostic accuracy of that flow chart, which visually represents the neuroadiologist''s mental process in making a diagnosis of posterior fossa tumors in children, 2) to describe particular types of posterior fossa lesions that are not correctly diagnosed by the initial flow chart, and 3) to provide an improved, clinically accessible flow chart based on the results.Open in a separate windowFIG 1.Predesigned radiologic flow chart created according to the literature before diagnostic accuracy analysis. The asterisk indicates brain stem tumors excluded from the analysis. Double asterisks indicate relative to gray matter. Modified with permission from D''Arco et al.11相似文献
