Left atrial myxoma attached to the anterior mitral leaflet with symptoms suggestive of infective endocarditis

The case of a 55-year-old woman is presented, whose clinical signs were initially suggestive of infective endocarditis. Transthoracic echocardiography (TTE) provided the diagnosis of a large left atrial myxoma attached to the anterior mitral leaflet. Perioperative transesophageal echocardiography (TEE) confirmed preoperative findings and assisted the surgical team in the assessment of tumour size, area of attachment, and mobility. Following tumour resection, TEE demonstrated residual moderate mitral valve regurgitation, which resulted in a change of surgical strategy. This report reinforces the importance of intraoperative TEE to facilitate and optimize surgical and anaesthesiological management of patients presenting with non-specific cardiorespiratory symptoms.

Ventricular prosthesis embolization during transapical aortic valve implantation: the role of transesophageal echocardiography in diagnosis and management

The authors present the case of an 81-year-old patient with severe aortic stenosis who experienced left ventricular embolization of an aortic bioprosthesis during transapical aortic valve implantation. The authors discuss reasons for prosthesis embolization and reinforce the attention to technical details and the widespread use of multimodality imaging techniques. In this context, transesophageal echocardiography appears indispensable in the detection and management of procedure-related complications.

An uncommon cause of coronary artery ostial obstruction: papillary fibroelastoma

Cardiac papillary fibroelastoma is a benign tumor that mainly affects cardiac valves. The tumor has the potential to cause angina and myocardial infarction due to embolization of tumor fragments. We describe a rare case of right coronary artery ostial obstruction by a 12 x 19 mm sized papillary fibroelastoma located in the sinus of Valsalva. The report underlies the importance of echocardiography in diagnosis and intraoperative treatment of this type of cardiac mass.

Clinical outcome and predictors for adverse events after transcatheter aortic valve implantation with the use of different devices and access routes

Background Transcatheter aortic valve implantation (TAVI) is a treatment option for high-risk patients with severe aortic stenosis. Previous reports focused on a single device or access site, whereas little is known of the combined use of different devices and access sites as selected by the heart team. The purpose of this study is to investigate clinical outcomes of TAVI using different devices and access sites. Methods A consecutive cohort of 200 patients underwent TAVI with the Medtronic CoreValve Revalving system (Medtronic Core Valve LLC, Irvine, CA; n = 130) or the Edwards SAPIEN valve (Edwards Lifesciences LLC, Irvine, CA; n = 70) implanted by either the transfemoral or transapical access route. Results Device success and procedure success were 99% and 95%, respectively, without differences between devices and access site. All-cause mortality was 7.5% at 30 days, with no differences between valve types or access sites. Using multivariable analysis, low body mass index (<20 kg/m2) (odds ratio [OR] 6.6, 95% CI 1.5-29.5) and previous stroke (OR 4.4, 95% CI 1.2-16.8) were independent risk factors for short-term mortality. The VARC-defined combined safety end point occurred in 18% of patients and was driven by major access site complications (8.0%), life-threatening bleeding (8.5%) or severe renal failure (4.5%). Transapical access emerged as independent predictor of adverse outcome for the Valve Academic Research Consortium–combined safety end point (OR 3.3, 95% CI 1.5-7.1). Conclusion A heart team–based selection of devices and access site among patients undergoing TAVI resulted in high device and procedural success. Low body mass index and history of previous stroke were independent predictors of mortality. Transapical access emerged as a risk factor for the Valve Academic Research Consortium–combined safety end point.

Giant aneurysm after aortic coarctation: repair without circulatory arrest

We describe the case of a 23-year-old patient presenting for redo aortic arch surgery because of recoarctation and poststenotic aneurysm formation after patch aortoplasty in infancy. Using the hemi-clamshell approach, the entire aortic arch was replaced and the supraaortic branches were reimplanted. The applied surgical technique using hypothermic extracorporeal circulation without cardiac arrest allowed an uninterrupted cerebral and spinal cord perfusion due to stepwise clamping of the aortic arch during reconstruction and resulted in an excellent neurologic outcome at six-month follow-up.?

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Minimization of Intra-Operative Shaping of Orthopaedic Fixation Plates: A Population-Based Design

In this paper we present a new population-based method for the design of bone fixation plates. Standard pre-contoured plates are designed based on the mean shape of a certain population. We propose a computational process to design implants while reducing the amount of required intra-operative shaping, thus reducing the mechanical stresses applied to the plate. A bending and torsion model was used to measure and minimize the necessary intra-operative deformation. The method was applied and validated on a population of 200 femurs that was further augmented with a statistical shape model. The obtained results showed substantial reduction in the bending and torsion needed to shape the new design into any bone in the population when compared to the standard mean-based plates.

Geometry-Aware Multiscale Image Registration via OBBTree-Based Polyaffine Log-Demons

Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

Personalized X-Ray Reconstruction of the Proximal Femur via Intensity-Based Non-rigid 2D-3D Registration

This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.