STEM与日常科技·英语30篇（3）

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数字孪生心脏用于个性化手术规划

A digital twin heart is a patient-specific 3D model built from MRI, CT, and ultrasound scans combined with biomechanical simulation.
Doctors use it to simulate blood flow, valve motion, and tissue stress before performing real surgery.
Unlike generic anatomical models, this twin reflects the exact shape, stiffness, and defects of an individual’s heart.
Surgeons can test different stent placements or repair strategies virtually to predict outcomes.
Machine learning helps calibrate the model using real-time pressure and flow data from catheterization.
This reduces trial-and-error in the operating room and shortens procedure time significantly.
Regulatory agencies now approve certain twin-based plans as part of pre-op documentation in Europe and Japan.
The model updates continuously as new imaging data arrives, supporting long-term monitoring.
It bridges the gap between population-level medical knowledge and truly personalized care.
Such twins exemplify how physics-informed AI transforms diagnostic precision in cardiology.