Mechanical Behavior of the Lamellar Structure in Semi-Crystalline Polymers

We have employed molecular dynamics simulations to study the behavior of virtual polymeric materials under an applied uniaxial tensile load. Through computer simulations, one can obtain experimentally inaccessible information about phenomena taking place at the molecular and microscopic levels. Not only can the global material response be monitored and characterized along time, but the response of macromolecular chains can be followed independently if desired. The computer-generated materials were created by emulating the step-wise polymerization, resulting in self-avoiding chains in 3D with controlled degree of orientation along a certain axis. These materials represent a simplified model of the lamellar structure of semi-crystalline polymers,being comprised of an amorphous region surrounded by two crystalline lamellar regions. For the simulations, a series of materials were created, varying i) the lamella thickness, ii) the amorphous region thickness, iii) the preferential chain orientation, and iv) the degree of packing of the amorphous region. Simulation results indicate that the lamella thickness has the strongest influence on the mechanical properties of the lamella-amorphous structure, which is in agreement with experimental data. The other morphological parameters also affect the mechanical response, but to a smaller degree. This research follows previous simulation work on the crack formation and propagation phenomena, deformation mechanisms at the nanoscale, and the influence of the loading conditions on the material response. Computer simulations can improve the fundamental understanding about the phenomena responsible for the behavior of polymeric materials, and will eventually lead to the design of knowledge-based materials with improved properties.

Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.