Pectus Excavatum postsurgical outcome based on preoperative soft body dynamics simulation

Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which an abnormal formation of the rib cage gives the chest a caved-in or sunken appearance. Today, the surgical correction of this deformity is carried out in children and adults through Nuss technic, which consists in the placement of a prosthetic bar under the sternum and over the ribs. Although this technique has been shown to be safe and reliable, not all patients have achieved adequate cosmetic outcome. This often leads to psychological problems and social stress, before and after the surgical correction. This paper targets this particular problem by presenting a method to predict the patient surgical outcome based on pre-surgical imagiologic information and chest skin dynamic modulation. The proposed approach uses the patient pre-surgical thoracic CT scan and anatomical-surgical references to perform a 3D segmentation of the left ribs, right ribs, sternum and skin. The technique encompasses three steps: a) approximation of the cartilages, between the ribs and the sternum, trough b-spline interpolation; b) a volumetric mass spring model that connects two layers - inner skin layer based on the outer pleura contour and the outer surface skin; and c) displacement of the sternum according to the prosthetic bar position. A dynamic model of the skin around the chest wall region was generated, capable of simulating the effect of the movement of the prosthetic bar along the sternum. The results were compared and validated with patient postsurgical skin surface acquired with Polhemus FastSCAN system

Fast left ventricle tracking in CMR images using localized anatomical affine optical flow

In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 ± 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction.