Feasibility of a Patient-Specific Digital Twin for Ventriculoperitoneal Shunt Trajectory Planning
Organizations: MedVisAI Lab, Singapore. · Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore. · Centre of AI in Medicine, Singapore. · A*STAR Institute of Advanced Intelligence and Computing (A*STAR IAIC), Agency for Science, Technology and Research (A*STAR), Singapore. ·
Abstract
Catheter obstruction is the commonest cause of shunt failure; freehand insertion at Keen's point leaves the tip free in cerebrospinal fluid in only one case in ten. We built a digital twin that reconstructs skull, scalp, ear and ventricles from preoperative CT by deterministic geometry, searches every entry around Keen's point for the perpendicular trajectory with the longest intraventricular length under safety constraints, and returns the plan as two ruler measurements from the ear and two depths. Executed freehand in 11 consecutive adults (IDEAL Stage 2a), it achieved Hayhurst Grade 1 placement in 10 of 11 against 22 of 213 historically (p = 9 x 10^-9), median entry and angular deviations 2.5 mm and 5.9 degrees, 1.4 cm more intraventricular catheter than Keen's point, and no intraoperative complication. The technique was unchanged; the gain came from choosing entry and depth per patient. Whether it lowers revision is the next stage's hypothesis.
Digital Twins
Digital twins are virtual models synchronized with real systems to support monitoring, prediction, simulation, and decision-making.
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