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This case report describes the use of the Micro Vascular Plug (MVP) system in a mural-type vein of Galen aneurysmal malformation, resulting in successful occlusion of the cerebrovascular fistula. This result was confirmed with immediate cessation in blood flow and 6-month follow-up angiography. The unique characteristics of the MVP provide potential advantages over current embolic techniques for occlusion of high-flow, fistulous, intracranial vessels such as those seen in the vein of Galen aneurysmal malformation, and may represent a valuable addition to the currently available options.

Background: Central nervous system vasculitis (CNSV) is a rare disorder, the pathophysiology of which is not fully understood. It involves a combination of inflammation and thrombosis. CNSV is most commonly associated with headache, gradual changes in mental status, and focal neurological symptoms. Diagnosis requires the effective use of history, laboratory testing, imaging, and biopsy. Catheter angiography can be a powerful tool in the diagnosis when common and low-frequency angiographic manifestations of CNSV are considered. We review these manifestations and their place in the diagnostic algorithm of CNSV. Summary: We reviewed the PubMed database for case series of CNSV that included 5 or more patients. Demographic and angiographic findings were collected. Angiographic findings were dichotomized between common and low-frequency findings. A system for incorporating these findings into clinical decision-making is proposed. Key Message: CNSV is a diagnostic challenge due to the absence of a true gold standard test. In the absence of such a test, catheter angiography remains a central piece of the diagnostic puzzle when appropriately employed and interpreted.

Tables are provided covering sample sizes up to 10. Interpretations are made for the variation of the coefficients and variances of the estimates as the number of censored observations vary. An index of experimental efficiency termed “efficiency per unit of waiting time” can be constructed with the tabulations provided. It is shown that (1) For the one-parameter single exponential distribution, the estimate of σ obtained from singly censored samples from the left has a smaller variance than that based upon singly censored samples from the right, provided that the number of missing observations is equal on both sides. (2) For the two-parameter single exponential distribution: a. The minimum value can be estimated more efficiently in samples censored from the right than in samples censored from the left, provided that the number of missing observations is equal; b. the estimate of the standard deviation in singly and doubly censored samples does not depend upon the side from which censoring takes p...

The variance-covariance matrices arising in the analysis of variance, response-surface fitting and order statistics have special patterns expediting and facilitating their algebraic manipulation. By appropriate triangulation and partitioning devices, the determinants of these matrices can be evaluated from general formulae. The characteristic equations, and sometimes their roots, can also be obtained in a direct single step.

Matrix inversion is used in the least squares analysis of data to estimate parameters and their variances and covariances. When the data come from the analysis of variance, analysis of covariance, order statistics, or the fitting of response-surfaces, the matrix to be inverted usually falls into a structured pattern that simplifies its inversion.One class of patterned matrices is characterized by non-singular symmetrical arrangemepts in which linear combinations of the first (r – 1) rows provide the right-hand portion, starting with the elements on the principal diagonal, of the rth and remaining rows. That is: for r i j, with vij = vij for all i ≠ j. The inverses of matrices of this clase contain a non-null principal diagonal, and immediately adjacent to the principal diagonal, (r − 1) non-null superdiagonals and (r – 1) non-null subdiagonals. All other elements are zero. These inverses are called diagonal matrices of type r. That is, a matrix is diagonal of type r if aij = 0 for |i – j| r and aij = aji ...

ORDER STATISTICS is that body of knowledge which utilizes the rank or order of an observation as well as its magnitude. It combines the technics of conventional statistics (which consider the magnitude of the observation) with those of rank order statistics (which consider only the relative rank whether or not the original observations were measured on an ordinal scale). The applications of order statistics have been generally of the following two classes