Bioresorbable vascular scaffolds (BVS), the next step in the continuum of minimally invasive vascular interventions present new opportunities for patients and clinicians but challenges as well. As they are comprised of polymeric materials standard imaging is challenging. This is especially problematic as modalities like optical coherence tomography (OCT) become more prevalent in cardiology. OCT, a light-based intracoronary imaging technique, provides cross-sectional images of plaque and luminal morphology. Until recently segmentation of OCT images for BVS struts was performed manually by experts. However, this process is time consuming and not tractable for large amounts of patient data. Several automated methods exist to segment metallic stents, which do not apply to the newer BVS. Given this current limitation coupled with the emerging popularity of the BVS technology, it is crucial to develop an automated methodology to segment BVS struts in OCT images. The objective of this paper is to develop a novel BVS strut detection method in intracoronary OCT images. First, we pre-process the image to remove imaging artifacts. Then, we use a K-means clustering algorithm to automatically segment the image. Finally, we isolate the stent struts from the rest of the image. The accuracy of the proposed method was evaluated using expert estimations on 658 annotated images acquired from 7 patients at the time of coronary arterial interventions. Our proposed methodology has a positive predictive value of 0.93, a Pearson Correlation coefficient of 0.94, and a F1 score of 0.92. The proposed methodology allows for rapid, accurate, and fully automated segmentation of BVS struts in OCT images.
Endothelial dysfunction has found to be related to cardiovascular disease. In the study, we assessed the endothelial flow-mediated vasodilatation (FMD) in three different-sized vessels. The study included 27 healthy volunteers who were asked to experience a 3-minute occlusion of brachial arteries. We found that FMD of radial arteries using the low-pressure oscillometry was significantly larger than that of small arteries together with microvessels in fingers using the photoplethysmography (PPG) (122 +/- 64 versus 87 +/- 56, p < 0.05). In addition, FMD measurements with PPG and laser Doppler flowmetry tended to negatively correlate with pulse pressure and pulse wave velocity. With a less coefficient of variations, the proposed low-pressure oscillometry may be a means for assessing the vascular endothelial function of peripheral circulation.
The use of small specific molecules including nutrients and pharmacological agents has been tried in the modulation of stem cells differentiation to obtain insulin secreting cells. The aim of this study was to investigate the ability of nano-sized collagen I molecules to enhance the differentiation of MSCs toward insulin-secreting cells in combination with nicotinamide and exendin-4. The preliminary results demonstrated that enhanced differentiation of MSCs towards insulin-secreting cells were achieved after an extra treatment with nano-sized collagen I molecules from the RT-PCR analysis and immunofluorescence staining of PDX-1, Nkx-6.1 and insulin markers.
Degeneration or injuries on articular cartilage is hard to self-repair. Physical stimulation, such as electrical, ultrasound or shear stress could be used for promoting chondrocytes proliferation and articular cartilage self-repair. Previous research on ultrasound stimulation used high frequency ultrasound. In this study, low frequency ultrasound stimulation is proposed as the treatment of osteoarthritis. An osteoarthritis model using New Zealand White rabbits was used to investigate whether low frequency ultrasound stimulation of 32.8 kHz is effective for the regeneration of articular cartilage. The evidence shows that low frequency ultrasound of 100mW can promote the regeneration of articular cartilage.
A challenging problem in dental implant surgery is to evaluate the stability of the implant. In this simulation study, an experimental phantom is used to represent a jawbone with a dental implant. It is made of a little pool filled with soft-tissue equivalent material and a disc of fresh Oakwood with a metal screw. Varying levels of contact between screw and wood are simulated by screwing in or out the screw. Initially, the screw is screwed in and fixed firmly in wood. Thereafter, the screw is screwed out, a half turn each time, to increase the gap gradually between wood and screw. Pulse-echo ultrasound is used and the power spectra of the received echo-signals are computed. These spectra are normalized then analyzed by using the partial least squares method to estimate the corresponding implant stiffness grade in terms of number of turns when beginning from the initial tight-screw state then screwing out the screw. A coefficient of determination R2 of 96.4% and a mean absolute error of ±0.23 turns are achieved when comparing real and estimated values of stiffness grades, indicating the efficiency of this approach.
