Validation of Vessel Width in Super-Resolution Ultrasound Imaging Using Micro-CT

Super-resolution ultrasound (SRUS) techniques, ultrasound localization microscopy (ULM) and super-resolution using erythrocytes (SURE), resolve vasculature beyond the diffraction limit, yet detection thresholds and filtering can bias width estimates. This study tests whether modest spatial smoothing, matched to the system’s effective resolution (Gaussian σ = 15 µm), reduces bias relative to micro-CT. A Sprague–Dawley rat kidney was imaged with SURE and ULM and co-registered to ex vivo micro-CT (5.45 µm voxels). Vessel widths were measured as the full width half maximum of SRUS line profiles and local thickness on micro-CT along identical lines, stratified by vessel type (interlobar, arcuate, and cortial radial vessels). Without smoothing, SRUS underestimated micro-CT across classes: interlobar mean normalized error was −89.9 ± 8.9 % (SURE) and −80.6 ± 12.4 % (ULM); arcuate −59.9 ± 13.1 % (SURE) and −87.2 ± 10.9 % (ULM); radial −39.3 ± 34.3 % (SURE) and −91.1 ± 5.3 % (ULM). With smoothing, errors moved toward zero: interlobar 9.7 ± 35.7 % (SURE) and −1.0 ± 25.7 % (ULM); arcuate −4.3 ± 40.5 % (SURE) and 28.8 ± 41.3 % (ULM); radial 23.4 ± 31.7 %(SURE) and 14.6 ± 23.8 % (ULM). Paired, line-wise normalized improvements were predominantly positive, e.g., interlobar gains of 60 ± 22 % (SURE) and 59 ± 22 %, with the largest class-wise gain up to 73 ± 21 % for radial vessels in ULM. These results show that resolution-matched smoothing mitigates systematic underestimation in SRUS width estimates, yielding near-unbiased ULM interlobar measurements and attenuated bias across vessel classes, and support modality-aware preprocessing for structural quantification in SRUS.