Coronary Arteriovenous Fistulae: A Review

Coronary arteriovenous fistulae are a coronary anomaly, presenting in 0.002% of the general population. Their etiology can be congenital or acquired. We present a review of recent literature related to their epidemiology, etiology, pathophysiology, clinical presentation, diagnostic approach, and therapeutic management.     

Deformable segmentation via sparse representation and dictionary learning

“Shape” and “appearance”, the two pillars of a deformable model, complement each other in object segmentation. In many medical imaging applications, while the low-level appearance information is weak or mis-leading, shape priors play a more important role to guide a correct segmentation, thanks to the strong shape characteristics of biological structures. Recently a novel shape prior modeling method has been proposed based on sparse learning theory. Instead of learning a generative shape model, shape priors are incorporated on-the-fly through the sparse shape composition (SSC). SSC is robust to non-Gaussian errors and still preserves individual shape characteristics even when such characteristics is not statistically significant.Although it seems straightforward to incorporate SSC into a deformable segmentation framework as shape priors, the large-scale sparse optimization of SSC has low runtime efficiency, which cannot satisfy clinical requirements. In this paper, we design two strategies to decrease the computational complexity of SSC, making a robust, accurate and efficient deformable segmentation system. (1) When the shape repository contains a large number of instances, which is often the case in 2D problems, K-SVD is used to learn a more compact but still informative shape dictionary. (2) If the derived shape instance has a large number of vertices, which often appears in 3D problems, an affinity propagation method is used to partition the surface into small sub-regions, on which the sparse shape composition is performed locally. Both strategies dramatically decrease the scale of the sparse optimization problem and hence speed up the algorithm. Our method is applied on a diverse set of biomedical image analysis problems. Compared to the original SSC, these two newly-proposed modules not only significant reduce the computational complexity, but also improve the overall accuracy.     

Polyarteritis nodosa and hypertrophic obstructive cardiomyopathy. A true association?

A 60-year-old man with polyarteritis nodosa under treatment presented with syncope. Echocardiography demonstrated hypertrophic obstructive cardiomyopathy; coronary arteriography revealed normal findings, and Holter monitor showed episodes of non-sustained ventricular tachycardia. This is the first report of hypertrophic obstructive cardiomyopathy developing in a patient with polyarteritis nodosa. Further studies should examine whether a true association exists.Abbreviations ESR Erythrocyte sedimentation rate - PAN Polyarteritis nodosa