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FEops HEARTguide™ wins CSI Highlight of the year award

 

Patient-specific simulations for structural heart interventions.

Enabling manufacturers, assisting physicians to further optimize structural heart interventions

Accelerating time to market, improving clinical outcomes in structural heart interventions

Heart valve diseases are on the rise, as is the use of minimally invasive procedures to treat them. Long development cycles in medtech makes the innovation of new, minimally invasive structural heart devices resource-intensive and challenging. 

FEops’ simulation technology uses advanced computational modeling and simulation to provide manufacturers and physicians with pre-operative insights into the interaction between patient anatomy and heart implants.

FEops offers the first and only patient-specific simulation technology for structural heart interventions, surpassing basic anatomical measurement by accurately predicting how devices will interact with each unique patient. Our end-to-end solution adds value at every step in the structural heart product life cycle, helping manufacturers accelerate time to market and offering insights that help physicians achieve better patient outcomes.

Note: FEops HEARTguide™ is a CE-marked product with indication in TAVI and LAAo. FEops HEARTguide is not available for clinical use in the USA

FEops simulation technology adds value to the structural heart product lifecycle, accelerating R&D and clinical trials and improving patient outcomes

TAVIguide

Meet FEops HEARTguide™, a cloud-based solution for hospitals and physicians that predicts the interaction between a device and a patient’s unique anatomy using FEops simulation technology.

Contact our team for details

FEops HEARTguide™ is a CE-marked product with indication for use in TAVI and LAAo.  FEops HEARTguide is not available for clinical use in the USA.

FEops are leading the way in image segmentation and computer modelling. With an emphasis on structural intervention, new solutions are being developed to enable clinicians to better plan for their procedures and to predict outcomes more robustly than historical geometric data alone.

Dr Ronak Rajani

Guy’s and St Thomas’, London, UK