Evaluation of cerebral hemodynamic assessment from time-of-flight magnetic resonance angiography using a topological network-based model with Transcranial Doppler measurements

Quantitative measurement of cerebral hemodynamics is essential for the diagnosis, management, and prognostication of cerebrovascular diseases. Transcranial Doppler (TCD), though widely used for non-invasive blood flow velocity measurement, is inherently limited by inadequate acoustic windows and significant operator dependency and provides only localized velocity information without anatomical context. To address these limitations, Dr. NEAR flow (DNF) was developed to estimate key hemodynamic parameters, including blood flow rate, relative pressure, and velocity from routinely acquired time-of-flight magnetic resonance angiography (TOF-MRA). In this single-center retrospective study, the performance of DNF was evaluated in 113 patients by directly comparing DNF-calculated velocities with time-averaged mean velocities measured by TCD across seven major cerebral arteries. Patient-specific inflow boundary conditions were defined using TCD measurements to ensure physiologically consistent comparisons. Analysis of 700 arterial-level velocity pairs demonstrated a statistically significant positive correlation between the two modalities (Pearson's correlation coefficient, r = 0.74, p < 0.0001). These results indicate that DNF offers a robust, non-invasive alternative for comprehensive cerebrovascular assessment, overcoming the procedural burdens and technical limitations associated with conventional TCD.