Assessing the influence of parameters on tissue welding in small bowel end-to-end anastomosis in vitro and in vivo.

BACKGROUND: The use of high-frequency electric welding technology for intestinal end-to-end anastomosis holds significant promise. Past studies have focused on in vitro, and the safety and efficacy of this technology is uncertain, severely limiting the clinical application of this technology. This study investigates the impact of compression pressure, energy dosage, and duration on anastomotic quality using a homemade anastomosis device in both in vitro and in vivo settings. METHODS: Two hundred eighty intestines and 5 experimental pigs were used for in vitro and in vivo experiments, respectively. The in vitro experiments were conducted to study the effects of initial pressure (50-400 kpa), voltage (40-60 V), and time (10-20 s) on burst pressure, breaking strength, thermal damage, and histopathological microstructure of the anastomosis. Optimal parameters were then inlaid into a homemade anastomosis and used for in vivo experiments to study the postoperative porcine survival rate and the pathological structure of the tissues at the anastomosis and the characteristics of the collagen fibers. RESULTS: The anastomotic strength was highest when the compression pressure was 250 kPa, the voltage was 60 V, and the time was 15 s. The degree of thermal damage to the surrounding tissues was the lowest. The experimental pigs had no adverse reactions after the operation, and the survival rate was 100%. 30 days after the operation, the surgical site healed well, and the tissues at the anastomosis changed from immediate adhesions to permanent connections. CONCLUSION: High-frequency electric welding technology has a certain degree of safety and effectiveness. It has the potential to replace the stapler anastomosis in future and become the next generation of new anastomosis device.

Generating 3D Multispectral Point Clouds of Plants with Fusion of Snapshot Spectral and RGB-D Images.

Accurate and high-throughput plant phenotyping is important for accelerating crop breeding. Spectral imaging that can acquire both spectral and spatial information of plants related to structural, biochemical, and physiological traits becomes one of the popular phenotyping techniques. However, close-range spectral imaging of plants could be highly affected by the complex plant structure and illumination conditions, which becomes one of the main challenges for close-range plant phenotyping. In this study, we proposed a new method for generating high-quality plant 3-dimensional multispectral point clouds. Speeded-Up Robust Features and Demons was used for fusing depth and snapshot spectral images acquired at close range. A reflectance correction method for plant spectral images based on hemisphere references combined with artificial neural network was developed for eliminating the illumination effects. The proposed Speeded-Up Robust Features and Demons achieved an average structural similarity index measure of 0.931, outperforming the classic approaches with an average structural similarity index measure of 0.889 in RGB and snapshot spectral image registration. The distribution of digital number values of the references at different positions and orientations was simulated using artificial neural network with the determination coefficient (R 2) of 0.962 and root mean squared error of 0.036. Compared with the ground truth measured by ASD spectrometer, the average root mean squared error of the reflectance spectra before and after reflectance correction at different leaf positions decreased by 78.0%. For the same leaf position, the average Euclidean distances between the multiview reflectance spectra decreased by 60.7%. Our results indicate that the proposed method achieves a good performance in generating plant 3-dimensional multispectral point clouds, which is promising for close-range plant phenotyping.