This MedTech company provides the TEVAR-Twin solution, an AI/ML-enabled software utilizing high-fidelity numerical models to create digital twins from patient CT scans. This technology assists surgeons in selecting the optimal stent-graft for Thoracic Endovascular Aortic Repair (TEVAR) procedures. The platform aims to enhance procedural confidence and precision by predicting device performance specific to the patient's anatomy.
Funding
Funding not disclosed
Founders
Product
Problem
Selecting the optimal stent-graft size for minimally invasive aortic repair (TEVAR) relies on pre-operative CT scans, but current methods lack precision, leading to potential complications like endoleaks, graft migration, and re-interventions. Inaccurate sizing increases procedural risks and negatively impacts patient outcomes.
Solution
AllStent offers a precision medicine platform that leverages AI and machine learning to construct patient-specific digital twin models from pre-surgical CT images. These high-fidelity numerical models simulate stent-graft deployment, enabling surgeons to select the "best-fit" device for each individual. By providing clinically validated simulations, AllStent aims to improve the accuracy of stent-graft sizing, reduce procedural risks, and optimize patient outcomes in TEVAR procedures. The platform facilitates enhanced surgical planning by predicting device performance within the patient's unique aortic anatomy.
Target Audience
The primary target audience includes vascular surgeons and interventional radiologists performing TEVAR procedures in hospitals and clinical centers.
Features
- AI/ML-powered digital twin creation from patient-specific CT scans
- Clinically validated high-fidelity numerical modeling of stent-graft deployment
- Simulation of device performance within individual aortic anatomies
- Visualization tools for pre-operative planning and stent-graft selection