Surgical treatment for heart myxomas.

According to unselected autopsy data, primary cardiac tumours are a rare entity. About 80% of the tumours are benign and nearly half of these are myxomas. In clinical practice, when diagnosis of this pathological entity is ascertained, decision for surgical treatment is made in order to prevent thromboembolism and obstruction of the valvular apparatus. Surgical resection including total tumour removal is accompanied by low perioperative mortality. The recidive rate is low in sporadic cases. However, in familial syndrome groups, such as the Swiss-Carney syndrome, the recurrence rate is higher.

Impact of 18F-FDG PET scan on the prevalence of benign thoracic lesions at surgical resection

OBJECTIVE: The main utility of 18-fluorodeoxyglucose positron emission tomography (FDG-PET) lies in the staging of lung cancer. However, it can also be used to differentiate indeterminate pulmonary lesions, but its impact on the resection of benign lesions at surgery is unknown. The aim of this study was to compare the prevalence of benign lesions at thoracotomy carried out for suspected lung cancer, before and after the introduction of PET scanning in a large thoracic surgical centre. MATERIALS AND METHODS: We reviewed our prospectively recorded surgical database for all consecutive patients undergoing thoracotomy for suspected or proven lung cancer and compared the prevalence of benign lesions in 2 consecutive 2-year groups, before (group I) and after (group II) the introduction of FDG-PET scan respectively. RESULTS: Surgical resection was performed on 1233 patients during the study period. The prevalence of benign lesions at surgery in groups I and II was similar (44/626 and 41/607, both 7%), and also in group II between those who underwent FDG-PET scan and the remainder (21/301 and 20/306 respectively, both 7%). In group II, of the 21 patients with benign lesions, who underwent FDG-PET, 19 had a false positive scan (mean standardised uptake value 5.3 [range 2.6-12.7]). Of these, 13 and 4 patients respectively had non-diagnostic bronchoscopy and percutaneous transthoracic lung biopsy pre thoracotomy. There was no difference in the proportion of different benign lesions resected between group I and those with FDG-PET in group II. CONCLUSION: The introduction of FDG-PET scanning has not altered the proportion of patients undergoing thoracotomy for ultimately benign lesions, mainly due to the avidity for the isotope of some non-malignant lesions. Such false positive results need to be considered when patients with unconfirmed lung cancer are contemplated for surgical resection.

Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.

Cleidocranial dysostosis: a report on two familial cases

Cleidocranial dysostosis is a rare genetic syndrome with an autosomal dominant inheritance pattern. The most common manifestations include clavicular aplasia or hypoplasia, open fontanelles and abnormal dentition. The present report describes two familial cases whose late diagnosis was made by means of clinical and radiographic findings. The treatment was radical, with complete surgical teeth extraction and making of total dental prosthesis.

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

Aplicação de SPME (Solid Phase Micro-Extraction) na análise de águas potáveis de três localidades do estado de São Paulo

The technique of solid phase microextraction (SPME) was used for the extraction of halogenated contaminants of water samples from three cities of the State of São Paulo and the extracts were submitted to gas chromatographic analysis with electron capture detection (GC-ECD). In the samples of water collected at the city of São Paulo the detected level of trihalomethanes (THM) expressed as the sum of chloroform, dibromochloromethane and dichlorobromomethane, were higher than the permissible limit established by the Brazilian regulation. In the samples collected at the two other cities the level of any of the three THM remained below the sensitivity of the ECD.

The Pelosi-type versus the modified Misgav-Ladach: a randomized trial of two surgical techniques for cesarean section

Cesarean section (CS) is now the most common major surgical procedure performed on women worldwide. A quarter of deliveries in Spain are performed by cesarean section. With the increasing rates of the operation, there is the need to use evidence-based techniques to optimize outcomes and minimize complications. The goal of this study is to employ a well-designed randomized controlled trial to evaluate the intraoperative blood loss of two surgical techniques for cesarean section, the Pelosi-type and the modified Misgav-Ladach. The trial will take place in Hospital Universitari de Girona Dr. Josep Trueta From 2014 to 2015, 512 pregnant women undergoing delivery by their first lower segment cesarean section in this center will be selected through a consecutive nonprobability sampling. We will collect the main obstetrical characteristics, intraoperative outcomes, short-term outcomes for the baby and postoperative outcomes. We will evaluate the intraoperative blood loss by comparing the changes in hemoglobin levels, pre and postoperatively. Patients will be followed during the postoperative period and in a two-week postoperative appointment. We will analyze the continuous variables, such as the differences in hemoglobin levels, using an unpaired two-sided Student’s t-test, while for the categorical variables Fischer’s exact test will be used

Features extraction based on the Discrete Hartley Transform for closed contour

In this paper the authors propose a new closed contour descriptor that could be seen as a Feature Extractor of closed contours based on the Discrete Hartley Transform (DHT), its main characteristic is that uses only half of the coefficients required by Elliptical Fourier Descriptors (EFD) to obtain a contour approximation with similar error measure. The proposed closed contour descriptor provides an excellent capability of information compression useful for a great number of AI applications. Moreover it can provide scale, position and rotation invariance, and last but not least it has the advantage that both the parameterization and the reconstructed shape from the compressed set can be computed very efficiently by the fast Discrete Hartley Transform (DHT) algorithm. This Feature Extractor could be useful when the application claims for reversible features and when the user needs and easy measure of the quality for a given level of compression, scalable from low to very high quality.