[Submitted on 20 Oct 2026]
Abstract:Digital twins of cerebral perfusion relate tracer dynamics to cerebral blood flow (CBF), blood volume (CBV) and mean transit time (MTT), but must be data-driven, physically consistent and uncertainty-aware. We introduce DuoPIC, a digital twin that needs no reference maps, in which a Windkessel flow model drives a tracer transport partial differential equation (PDE). A population-level neural closure divides each region into fast and slow pathways with tracer mass and MTT conserved by construction, and a tempered posterior quantifies the uncertainty of every estimate. Its voxel maps set the state of the art for lesion detection on ISLES’17 MR (AUC 0.745) and ISLES’24 CT (0.743). On held-out patients, the neural PDE reduced the compartment’s reconstruction error by 19% and lifted 95% MTT interval coverage from 88% to 94%. Code: this https URL
Submission history
From: Quang-Anh N. D. [view email]
[v1] Tue, 20 Oct 2026 19:05:46 UTC (2,719 KB)
