Cardiovascular disease (CVD) has been the leading global cause of death for the last 15 years. In 2016, CVD, and resulting sudden and severe medical emergencies, accounted for 15.2 million deaths globally (1). Early CVD pathophysiology is characterized by both inflammation and microcalcification of vasculature. Currently, detection and observation of the disease at this stage are difficult. Additionally, the cause-effect relationships among symptoms remain unknown (2, 3, 4, 5). Nevertheless, inflammation and calcification have independently been connected to CVD risk (1, 6). Moreover, studies have shown that calcification specifically in the aorta is associated with an increased risk of death from CVD (7). For these reasons, this study aims to establish a method to examine and quantify the relationship between inflammation and plaque microcalcification in the descending thoracic aorta, and develop a strategy to better detect these CVD risk factors. PET/CT imaging with 2-deoxy-2-[18F]fluoro-D-glucose (FDG) and 18-Sodium Fluoride (NaF) radiotracers were used to detect plaque inflammation and vascular microcalcification, respectively. The thoracic aorta was then manually segmented on PMOD, and inflammation/microcalcification in each participant’s aorta were quantified by calculating the mean standard uptake value (SUV) for both radiotracers. The relationship between inflammation and microcalcification, as well as how both contribute to CVD, were analyzed by comparing SUVs for control participants and patients. It was found that participants with CVD have significantly more inflammation and microcalcification in this area than that among controls and that aortic inflammation and microcalcification are positively correlated with each other and with age.
This study aims to display the ability and efficacy of 3D printing image-based, implantable biological scaffolds with varying properties. In this study, scaffolds were printed using various ratios of hydroxyapatite (HA) to polycaprolactone (PCL) to display a spectrum of properties suitable for musculoskeletal scaffolds. As an initial application of this method, scaffolds were generated from a series of one hundred DICOM images for a 60-year-old, female proximal femur. Additional structures, including a printed box and a circular lattice were generated. These models were printed at HA to PCL ratios (m/m) of 1:9, 2:8, 3:7, 4:6, 5:5, 6:4, 7:3, 8:2, and 9:1. Postprinting analysis of the ratios was performed with scanning electron microscopy to observe the prints’ microstructure. Post printing analysis also included a compression test to observe biomechanical properties and a cell culture on the prints to observe cellular viability and adhesion. Ratios showed vast microstructural differences. It was also found that the 6:4 sample had the most similar surface level microstructure to that of human trabecular bone. The compression test revealed a positive correlation (R2 = 0.92) between HA concentration (%) and stiffness (N/mm). Cellular viability and adhesion were confirmed for 10 days after initial seeding cells.