Doctors from Scotland and the US have completed what is thought to be a world-first stroke procedure using a robot. Prof Iris Grunwald, of the University of Dundee, performed the remote thrombectomy - the removal of blood clots after a stroke - on a human cadaver that had been donated to medical science. The professor was at Ninewells Hospital in Dundee, while the body she was operating on while using the machine was across the city at the university. Hours later, Ricardo Hanel - a neurosurgeon in Florida - used the technology to carry out the first transatlantic surgery from his Jacksonville base on a human body in Dundee over 4,000 miles (6,400km) away. The team has called it a potential game changer if it becomes approved for use on patients.

Autonomous navigation for mechanical thrombectomy (MT) remains a critical challenge due to the complexity of vascular anatomy and the need for precise, real-time decision-making. Reinforcement learning (RL)-based approaches have demonstrated potential in automating endovascular navigation, but current methods often struggle with generalization across multiple patient vasculatures and long-horizon tasks. We propose a world model for autonomous endovascular navigation using TD-MPC2, a model-based RL algorithm. We trained a single RL agent across multiple endovascular navigation tasks in ten real patient vasculatures, comparing performance against the state-of-the-art Soft Actor-Critic (SAC) method. Results indicate that TD-MPC2 significantly outperforms SAC in multi-task learning, achieving a 65% mean success rate compared to SAC's 37%, with notable improvements in path ratio. TD-MPC2 exhibited increased procedure times, suggesting a trade-off between success rate and execution speed. These findings highlight the potential of world models for improving autonomous endovascular navigation and lay the foundation for future research in generalizable AI-driven robotic interventions.

Home to fine cheese, breathtaking scenery and footballing politics (FIFA HQ overlooks Lake Zurich), Switzerland's largest city is also a financial juggernaut. The central square of Paradeplatz is its beating heart, where the Swiss banking system pumps venture capital funding into a thriving tech ecosystem--around CHF 72 million (more than 1 billion) was poured into Zurich startups alone in 2023. Fintech is a natural major player, but if the banking industry is the ecosystem's engine, innovation is its fuel. Many of the city's most exciting startups began life as student projects at its world-leading universities, which provide a steady flow of great thinkers. "Zurich is a city of ideas, people, and capital," says Frank Floessel, head of entrepreneurship at ETH Zurich, a public research university focused on science, technology, and engineering that'spins out' an average of 25 startups every year. "We have plenty of talent and know-how.

Objective: The objective of this work is to introduce and demonstrate the effectiveness of a novel sensing modality for contact detection between an off-the-shelf aspiration catheter and a thrombus. Methods: A custom robotic actuator with a pressure sensor was used to generate an oscillatory vacuum excitation and sense the pressure inside the extracorporeal portion of the catheter. Vacuum pressure profiles and robotic motion data were used to train a support vector machine (SVM) classification model to detect contact between the aspiration catheter tip and a mock thrombus. Validation consisted of benchtop accuracy verification, as well as user study comparison to the current standard of angiographic presentation. Results: Benchtop accuracy of the sensing modality was shown to be 99.67%. The user study demonstrated statistically significant improvement in identifying catheter-thrombus contact compared to the current standard. The odds ratio of successful detection of clot contact was 2.86 (p=0.03) when using the proposed sensory method compared to without it. Conclusion: The results of this work indicate that the proposed sensing modality can offer intraoperative feedback to interventionalists that can improve their ability to detect contact between the distal tip of a catheter and a thrombus. Significance: By offering a relatively low-cost technology that affords off-the-shelf aspiration catheters as clot-detecting sensors, interventionalists can improve the first-pass effect of the mechanical thrombectomy procedure while reducing procedural times and mental burden.

The Lucid Robotic System is aimed at one of the central dilemmas of modern neurology: How to quickly identify patients with the most severe strokes who could benefit from being taken immediately to hospitals that can perform a complex clot-removal procedure, potentially helping to avoid major disability. The Lucid system, manufactured by Neural Analytics Inc. of Los Angeles, combines two technologies. One is a transcranial ultrasound, which shows whether a blood clot is blocking blood flow to the brain. The ultrasound, taken through a kind of natural window into the brain near a person's ear, is combined with the robotic part, which uses artificial intelligence to assess patients by instantaneously comparing them to thousands of earlier images of patients with severe strokes. "The goal is to have this in the ambulance soon," said Thomas G. Devlin, neurology chairman at the Erlanger Health System in Chattanooga.