inHEART offers an AI‑driven, cloud‑based platform that generates a patient‑specific 3D digital twin of the heart from standard CT or MRI scans, automatically segmenting chambers, vessels, scar tissue and other anatomical features. The interactive model can be explored for pre‑procedural planning and integrates directly with major electroanatomic mapping systems to guide catheter ablations, reducing planning time and improving success rates for ventricular and atrial arrhythmia procedures.
Funding
$811.3K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
SCFounders
Product
Problem
Electrophysiologists must plan complex catheter ablations using limited two‑dimensional imaging, which can obscure patient‑specific cardiac anatomy, scar distribution, and surrounding structures. This uncertainty prolongs procedure times, increases recurrence risk, and hampers personalized treatment strategies.
Solution
inHEART provides an AI‑driven, cloud‑based platform that creates a patient‑specific three‑dimensional digital twin of the heart from standard CT or MRI scans. The system automatically segments cardiac chambers, major vessels, collateral structures, and tissue characteristics such as scar transmurality, fatty infiltration, and calcifications. Clinicians can explore the model interactively before the procedure to define optimal ablation targets and strategies. The digital twin integrates seamlessly with major electroanatomic mapping (EAM) systems (e.g., CARTO, Rhythmia, EnSite, Affera) for real‑time guidance during the intervention. By delivering detailed anatomical insight and pre‑procedural planning tools, the platform reduces intraprocedural planning time and improves clinical success rates for ventricular and atrial arrhythmia ablations.
Target Audience
Primary users are electrophysiologists and cardiac arrhythmia teams in hospitals and specialized EP labs who perform ventricular tachycardia, atrial fibrillation, and cardioneuroablation procedures.
Features
- Automated AI segmentation of cardiac chambers, valves, coronary arteries, veins, nerves, and adjacent thoracic structures from anonymized CT/MRI data
- Visualization of tissue characteristics including scar extent, transmurality, wall thinning, fatty infiltrate, and calcifications
- Cloud‑based 3D rendering delivered within 24 hours, accessible via a secure web interface
- Interactive exploration tools for measuring wall thickness, scar depth, and spatial relationships to guide ablation lines
- Direct integration with all major EAM platforms, enabling overlay of the digital twin onto live mapping data
- Collaborative sharing of models with remote colleagues for multidisciplinary treatment planning
- Compliance with FDA clearance and CE certification for medical device software