STEM与日常科技·英语30篇（3）
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Digital Twin Hearts for Personalized Surgical Planning
数字孪生心脏用于个性化手术规划
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A digital twin heart is a patient-specific 3D model built from MRI, CT, and ultrasound scans combined with biomechanical simulation.
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Doctors use it to simulate blood flow, valve motion, and tissue stress before performing real surgery.
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Unlike generic anatomical models, this twin reflects the exact shape, stiffness, and defects of an individual’s heart.
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Surgeons can test different stent placements or repair strategies virtually to predict outcomes.
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Machine learning helps calibrate the model using real-time pressure and flow data from catheterization.
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This reduces trial-and-error in the operating room and shortens procedure time significantly.
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Regulatory agencies now approve certain twin-based plans as part of pre-op documentation in Europe and Japan.
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The model updates continuously as new imaging data arrives, supporting long-term monitoring.
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It bridges the gap between population-level medical knowledge and truly personalized care.
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Such twins exemplify how physics-informed AI transforms diagnostic precision in cardiology.