YiRang Shin, Qi You, Yike Wang, Matthew R. Lowerison, Bing-Ze Lin, Peng Song
tlooto Summary
B-fULM is established as a practical and sensitive approach for super-resolved 3D functional neuroimaging by predicting that integrating amplitude with count-based fULM improves functional sensitivity, particularly under high MB concentrations where localization saturates.
Abstract
Functional ultrasound localization microscopy (fULM) enables brain-wide mapping of neural activity at micron-scale resolution but suffers from limited sensitivity due to sparse and noisy microbubble (MB) detections. Extending fULM into three dimensions (3D) further exacerbates these challenges because of low-frequency matrix arrays, reduced localization efficiency, and severe data sparsity. To address these limitations, we developed a statistical framework that models MB arrivals in 3D as a Poisson process accounting for localization efficiency, detection probability, and backscattered amplitude. This analysis predicts that integrating amplitude with count-based fULM improves functional sensitivity, particularly under high MB concentrations where localization saturates. Three-dimensional MB advection simulations confirmed these predictions, showing that backscattering fULM (B-fULM) maintains sensitivity at higher MB concentrations where conventional fULM fails. In rat brain experiments, B-fULM yielded stronger and more robust stimulus-evoked responses, with SNR gains of 18% in the somatosensory cortex and 61% in the thalamus, while preserving super-resolved spatial detail (33.4 μm for B-fULM vs 35.7 μm for fULM). These results establish B-fULM as a practical and sensitive approach for super-resolved 3D functional neuroimaging.
Citation format
SHIN, YiRang, et al. Microbubble backscattering intensity improves the sensitivity of three-dimensional (3-d) functional ultrasound localization microscopy (fulm). IEEE TRANSACTIONS ON MEDICAL IMAGING, 2026, 45(6): 2701–2712.