Cartan provides an AI-driven platform that creates a patient‑specific digital twin of the knee from imaging and motion data, then runs long‑term biomechanical simulations to generate a customized surgical plan for bicruciate‑retaining knee replacements. The system offers real‑time intra‑operative guidance and instant re‑simulation of plan adjustments, helping surgeons preserve both cruciate ligaments and improve joint stability.
Funding
Funding not disclosed
Founders
Product
Problem
Conventional total knee arthroplasty (TKA) typically sacrifices the anterior cruciate ligament (ACL) and often the posterior cruciate ligament (PCL), leading to reduced knee stability and a roughly 20% patient dissatisfaction rate. Bicruciate‑retaining (BCR) knee replacements preserve both ligaments and provide a more natural-feeling joint, but the procedure is technically demanding, requiring precise bone cuts, hybrid measured‑resection and gap‑balancing techniques, and early tibial rotation decisions. Most orthopedic surgeons lack the case volume and intra‑operative guidance needed to perform BCR reliably, resulting in its use in fewer than 1% of knee replacements.
Solution
Cartan offers an AI‑native platform that creates a patient‑specific digital twin of the knee from CT, MRI, and kinematic data, then runs long‑term biomechanical simulations to predict implant performance over decades. The system generates a customized surgical plan that optimizes component positioning while preserving the ACL and PCL, and provides real‑time intra‑operative feedback to guide bone cuts and balance the joint. Surgeons can iteratively adjust the plan pre‑operatively, with each change instantly re‑simulated to update confidence intervals on wear, stress, and survivorship. By embedding AI‑driven planning and instrumented guidance into the workflow, Cartan simplifies the complex BCR procedure, making it accessible to a broader range of surgeons and aiming to improve postoperative stability and patient satisfaction.
Target Audience
Primary customers are orthopedic surgeons and hospital orthopedic departments seeking to adopt bicruciate‑retaining knee replacement techniques, as well as surgical planning centers that require advanced biomechanical simulation tools for joint arthroplasty.
Features
- AI agents ingest CT, MRI, and kinematic data to construct a physics‑based digital twin comprising over 50,000 mesh triangles and 9,000+ kinematic points
- Long‑term (up to 50‑year) biomechanical simulations evaluate wear, cyclic stress, fracture risk, bone ingrowth, and aseptic loosening for each implant configuration
- Pre‑operative planning interface allows surgeons to modify component rotation, tibial slope, and coronal alignment with instant re‑simulation and updated confidence intervals
- Real‑time intra‑operative guidance tracks surgical state, provides precise cutting instructions, and verifies each step against predefined biomechanical thresholds
- Integration with NVIDIA Cosmos MONAI, PhysicsNeMo, PINNs, FEBio, JAX/Diffrax, and Monte Carlo methods for high‑fidelity modeling and rapid computation
- Export of simulation results and surgical parameters via standard DICOM and FHIR interfaces for inclusion in electronic health records