A piezoresistive-based 3-axial MEMS tactile sensor and integrated surgical forceps for gastrointestinal endoscopic minimally invasive surgery.

In robotic-assisted surgery (RAS), traditional surgical instruments without sensing capability cannot perceive accurate operational forces during the task, and such drawbacks can be largely intensified when sophisticated tasks involving flexible and slender arms with small end-effectors, such as in gastrointestinal endoscopic surgery (GES). In this study, we propose a microelectromechanical system (MEMS) piezoresistive 3-axial tactile sensor for GES forceps, which can intuitively provide surgeons with online force feedback during robotic surgery. The MEMS fabrication process facilitates sensor chips with miniaturized dimensions. The fully encapsulated tactile sensors can be effortlessly integrated into miniature GES forceps, which feature a slender diameter of just 3.5 mm and undergo meticulous calibration procedures via the least squares method. Through experiments, the sensor's ability to accurately measure directional forces up to 1.2 N in the Z axis was validated, demonstrating an average relative error of only 1.18% compared with the full-scale output. The results indicate that this tactile sensor can provide effective 3-axial force sensing during surgical operations, such as grasping and pulling, and in ex vivo testing with a porcine stomach. The compact size, high precision, and integrability of the sensor establish solid foundations for clinical application in the operating theater.

Novel miniature transendoscopic telerobotic system for endoscopic submucosal dissection (with videos).

BACKGROUND AND AIMS: The lack of tissue traction and instrument dexterity to allow for adequate visualization and effective dissection were the main issues in performing endoscopic submucosal dissection (ESD). Robot-assisted systems may provide advantages. In this study we developed a novel transendoscopic telerobotic system and evaluated its performance in ESD. METHODS: A miniature dual-arm robotic endoscopic assistant for minimally invasive surgery (DREAMS) was developed. The DREAMS system contained the current smallest robotic ESD instruments and was compatible with the commercially available dual-channel endoscope. After the system was established, a prospective randomized controlled study was conducted to validate the performance of the DREAMS-assisted ESD in terms of efficacy, safety, and workload by comparing it with the conventional technique. RESULTS: Two robotic instruments can achieve safe collaboration and provide sufficient visualization and efficient dissection during ESD. Forty ESDs in the stomach and esophagus of 8 pigs were completed by DREAMS-assisted ESD or conventional ESD. Submucosal dissection time was comparable between the 2 techniques, but DREAMS-assisted ESD demonstrated a significantly lower muscular injury rate (15% vs 50%, P = .018) and workload scores (22.30 vs 32.45, P < .001). In the subgroup analysis of esophageal ESD, DREAMS-assisted ESD showed significantly improved submucosal dissection time (6.45 vs 16.37 minutes, P = .002), muscular injury rate (25% vs 87.5%, P = .041), and workload (21.13 vs 40.63, P = .001). CONCLUSIONS: We developed a novel transendoscopic telerobotic system, named DREAMS. The safety profile and technical feasibility of ESD were significantly improved with the assistance of the DREAMS system, especially in the narrower esophageal lumen.

Mapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning.

Chemotherapy can induce toxicity in the central and peripheral nervous systems and result in chronic adverse reactions that impede continuous treatment and reduce patient quality of life. There is a current lack of research to predict, identify, and offset drug-induced neurotoxicity. Rapid and accurate assessment of potential neuropathy is crucial for cost-effective diagnosis and treatment. Here we report dynamic near-infrared upconversion imaging that allows intraneuronal transport to be traced in real time with millisecond resolution, but without photobleaching or blinking. Drug-induced neurotoxicity can be screened prior to phenotyping, on the basis of subtle abnormalities of kinetic characteristics in intraneuronal transport. Moreover, we demonstrate that combining the upconverting nanoplatform with machine learning offers a powerful tool for mapping chemotherapy-induced peripheral neuropathy and assessing drug-induced neurotoxicity.