Clinical Research Directory

Real Time Craniotomy Planning Using Mixed Reality

This study is a prospective observational study designed to evaluate the effectiveness of Brainlab's Mixed Reality Viewer in enhancing the accuracy and efficiency of preoperative craniotomy planning. The study will be conducted at a single site with two enrollment groups. Group 1 has a target enrollment of 38 subjects. Group 2 has a target enrollment of 16 subjects. By observing the device's use during standard surgical procedures, we can accurately measure its impact on incision planning accuracy, time efficiency, and overall ease of use compared to traditional neuronavigation systems. This design allows for the collection of both quantitative and qualitative data, providing a robust assessment of the Mixed Reality Viewer's potential to enhance surgical outcome

3D Liver Volumetry

The study aims to improve preoperative evaluation of liver resection volume in patients undergoing major hepatectomies. Accurate prediction of the planned resection and the future liver remnant (FLR) is critical to minimize the risk of postoperative liver failure, which is associated with increased morbidity and mortality. Conventional imaging-based volumetry may have limited accuracy. This study investigates the use of individualized 3D liver models combined to enhance visualization and volumetric analysis of liver anatomy and resection boundaries. Patients are recruited in the liver outpatient clinic and, upon consent, preoperative 3D models are created using Medics 3D. During surgery, the planned resection is guided by the individualized 3D models. Postoperatively, the resected specimen undergoes CT-based volumetry to compare the predicted resection volume from the 3D model with the actual volume. Routine postoperative follow-up is conducted. The study aims to optimize surgical planning, enhance the accuracy of future liver remnant prediction.

Assessment of the Feasibility of Using a Preoperative Surgical Fracture Analysis Tool

This study aims to evaluate a preoperative fracture analysis tool that uses 3D visualization and biomechanical modeling to assist surgeons in planning screw and plate fixation for complex tibial plateau fractures. By simulating different fixation strategies based on patient-specific CT data, the tool provides insights into construct stability, potentially improving surgical precision and reducing intraoperative uncertainty. The study also investigates the tool's feasibility within current clinical workflows without altering the standard of care.

NON-INVASIVE BLOOD FLOW ASSESSMENT: Computational Tool for Measuring Arterial Flow From CT

Major invasive surgery, such as oncological abdominal surgery, is associated with a high risk of complications and mortality. One of the main problems in this type of surgery is the difficulty in preserving the arteries and veins necessary to support vital organs. The main objective of this project is to develop software to predict vascular flow changes based on preoperative computed tomography (CT) scans. Currently, the only way to assess preoperative vascular flow is through percutaneous angiography. This is an invasive procedure that requires anaesthesia, hospitalisation, high doses of radiation, vessel manipulation and the possibility of serious injury. It is often used for the diagnosis of vascular stenosis, analysis of vascular flow and preoperative planning to determine which vessels are directly related to organ perfusion. This preoperative planning will be key in the following clinical scenarios: 1. Anomalous hepatic artery anatomy in pancreaticoduodenectomy. 2. Celiac trunk stenosis. 3. Hepatic artery revascularisation from the superior mesenteric artery. 4. Hepatic artery flow assessment in liver transplantation. 5. Splenic artery flow steal phenomenon in liver transplantation. Novella aims to develop a tool that has the capability to predict postoperative vascular flow.