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Background and Objectives: The diagnosis of cholesteatoma is usually clinic, and the only efficient treatment is surgical. High-resolution computed tomography (HRCT) is not considered absolutely necessary for the management of an uncomplicated cholesteatoma, but unsuspected situations from a clinical point of view can be discovered using the scans, warning the surgeon. Our objective is to compare HRCT scan information with intraoperative findings in patients with cholesteatoma and analyze the usefulness of a preoperative HRCT scan from a surgical point of view. Materials and Methods: This is a prospective descriptive study conducted in the Department of Otolaryngology, Victor Babes University of Medicine and Pharmacy Timisoara, Romania, from May 2021 to April 2022. It was carried out on 46 patients with a clinical diagnosis of cholesteatoma who were consequently operated on in our department. All patients received full clinical and audiological examinations. In all cases, an HRCT scan was performed preoperatively as a mandatory investigation. Preoperative HRCT scans were analyzed, and their findings were compared to the intraoperative notes. The two sets of observations were analyzed using standard statistical methods. Results: Extensive cholesteatoma was the most common type of disease, involving 46% of the patients, followed by pars flaccida cholesteatoma (35%) and pars tensa cholesteatoma (19%). Eroded scutum was the most frequent lesion involving 70% of the patients, followed by incus erosion (67%). Comparison of the HRCT and intraoperative findings revealed a very good correlation for tegmen tympani erosion, sigmoid plate erosion, scutum and malleus erosion, and a moderate-to-good correlation for lateral semicircular canal erosion, incus and stapes erosion, and fallopian canal erosion. Conclusions: HRCT is a valuable tool in the preoperative assessment of cholesteatoma, helping in making surgical decisions. It can accurately predict the extent of disease and is helpful for detecting unapparent dangerous situations. However, it is not very accurate in detecting fallopian canal and stapes erosion.

Background and Objectives: Our study aimed to investigate the gross anatomy aspects of the fossa ovalis (FO) and the presence of some anatomical variation resulting from the incomplete fusion of septum primum and septum secundum, such as an atrial septal pouch (SP) and left atrial septal ridge. Materials and Methods: Thirty-one adult human hearts removed from formalin-fixed specimens were examined to provide information about the morphology of the FO. The organs were free of any gross anatomically visible pathological conditions. Results: The most common variants were the FO located in the inferior part of the interatrial septum (64.51%), circular (61.3%), with a net-like structure (51.62%), prominent limbus (93.55%), and patent foramen ovale (PFO) (25.8%). The right SP was observed in 9.67% of specimens, the left SP was observed in 29.03% of cases, and in 51.61% of cases, a double SP was observed. One sample presented a right SP and a double left SP, and one case showed a triple left SP, which was not reported previously to our knowledge. Conclusions: Knowledge of the interatrial septal anatomy becomes important for interventional cardiologists and should be documented before transeptal puncture.

Abstract  We present a simulation-based performance model to analyze a parallel sparse LU factorization algorithm on modern cached-based, high-end parallel architectures. We consider supernodal right-looking parallel factorization on a bi-dimensional grid of processors, that uses static pivoting. Our model characterizes the algorithmic behavior by taking into account the underlying processor speed, memory system performance, as well as the interconnect speed. The model is validated using the implementation in the SuperLU_DIST linear system solver, the sparse matrices from real application, and an IBM POWER3 parallel machine. Our modeling methodology can be adapted to study performance of other types of sparse factorizations, such as Cholesky or QR, and on different parallel machines. [ABSTRACT FROM AUTHOR]