Achieving superior outcomes through the use of robots in medical applications requires an integrated approach to the design of the robot, tooling and the procedure itself. In this paper, this approach is applied to develop a robotic technique for closing abnormal communication between the atria of the heart. The goal is to achieve the efficacy of surgical closure as performed on a stopped, open heart with the reduced risk and trauma of a beating-heart catheter-based procedure. In the proposed approach, a concentric tube robot is used to percutaneously access the right atrium and deploy a tissue approximation device. The device is constructed using a metal microelectromechanical system (MEMS) fabrication process and is designed to both fit the manipulation capabilities of the robot as well as to reproduce the beneficial features of surgical closure by suture. The effectiveness of the approach is demonstrated through ex vivo and in vivo experiments.
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http://dx.doi.org/10.1177/0278364912443718 | DOI Listing |
Arthroplast Today
December 2024
Department of Orthopaedic Surgery, University of Louisville, Louisville, KY, USA.
Background: Robotic-assisted total knee arthroplasty (RA-TKA) was introduced to provide surgeons with virtual preoperative planning and intraoperative information to achieve the desired surgical goals in an effort to improve patient outcomes. The purpose of this study was to compare clinical outcomes and patient-reported outcome measures following primary TKA using RA-TKA vs manual instrumentation.
Methods: This was a retrospective cohort review study comparing 393 primary RA-TKAs vs 312 manual TKAs at a minimum 2-year follow-up.
J Biomed Opt
January 2025
University of Ljubljana, Faculty of Mathematics and Physics, Ljubljana, Slovenia.
Significance: Machine learning models for the direct extraction of tissue parameters from hyperspectral images have been extensively researched recently, as they represent a faster alternative to the well-known iterative methods such as inverse Monte Carlo and inverse adding-doubling (IAD).
Aim: We aim to develop a Bayesian neural network model for robust prediction of physiological parameters from hyperspectral images.
Approach: We propose a two-component system for extracting physiological parameters from hyperspectral images.
Undersea Hyperb Med
January 2025
Hyperbaric and Tissue Viability Unit, Gozo General Hospital, Malta.
Arieli has previously demonstrated that the exposure metric K could be used to predict pulmonary oxygen toxicity (POT) based on changes in Vital Capacity (VC). Our previous findings indicate that the Equivalent Surface Oxygen Time (ESOT) allows the estimation of POT without loss of accuracy compared to K. In this work, we have further investigated POT recovery.
View Article and Find Full Text PDFInt J Numer Method Biomed Eng
January 2025
Center of Mathematics, University of the Republic Uruguay, Montevideo, Uruguay.
The finite-element method (FEM) is a well-established procedure for computing approximate solutions to deterministic engineering problems described by partial differential equations. FEM produces discrete approximations of the solution with a discretisation error that can be quantified with a posteriori error estimates. The practical relevance of error estimates for biomechanics problems, especially for soft tissue where the response is governed by large strains, is rarely addressed.
View Article and Find Full Text PDFOral Maxillofac Surg
January 2025
Oral Biology Department, Faculty of Dentistry, Mansoura University, Mansoura, Egypt.
Objective: A nanometer-sized vesicles originating from bone marrow mesenchymal stem cells (BMMSCs), called exosomes, have been extensively recognized. This study defines the impact of BMMSCs and their derived exosomes on proliferation, apoptosis and oxidative stress (OS) levels of CP-induced parotid salivary gland damage.
Methods: BMMSCs were isolated from the tibia of four white albino rats and further characterized by flowcytometric analysis.
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