Objective
To develop a digital twin-driven robot-assisted extracorporeal shock wave lithotripsy (ESWL) system, address the challenges of difficult localization and energy-induced damage in traditional ESWL for pediatric urolithiasis treatment, and construct an integrated solution for "precision diagnosis - intelligent treatment - full-cycle management".
Methods
Optical motion capture technology, ultrasound AI recognition algorithms, and renal digital twin models were integrated. A coupled digital twin of "anatomy-physiology-metabolism" was constructed through 3D reconstruction of CT/MRI. Precision localization and tracking were achieved by combining a six-degree-of-freedom robotic arm with a spatiotemporal convolutional neural network. Preoperative metabolic simulation predicted recurrence risk, real-time metabolic indicators optimized energy parameters during surgery, and intelligent follow-up management was implemented postoperatively.
Results
The lithotripsy system showed a localization error <2mm, a 40% improvement in lithotripsy efficiency, 92% energy focusing accuracy, a recurrence rate reduced from 30% to below 10%, a 60% simplification of the operation process, a learning cycle shortened to 1 month, compatibility with mainstream devices, and support for remote operation.
Conclusion
Visualized digital twin technology promotes the shift of pediatric urolithiasis prevention and treatment from "experience-dependent" to "digitally-driven", providing radiation-free, high-precision individualized treatment solutions for children and patients with complex urolithiasis. It is of great significance for promoting the downsinking of hierarchical medical resources.
Keywords: Digital Twin,Extracorporeal Shock Wave Lithotripsy, Intelligent Navigation,Individualized Treatment,Full-Cycle Management
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