Unknown

Dataset Information

0

Feasibility of non-linear beamforming ultrasound methods to characterize and size kidney stones.


ABSTRACT:

Purpose

Ultrasound methods for kidney stone imaging suffer from poor sensitivity and size overestimation. The study objective was to demonstrate feasibility of non-linear ultrasound beamforming methods for stone imaging, including plane wave synthetic focusing (PWSF), short-lag spatial coherence (SLSC) imaging, mid-lag spatial coherence (MLSC) imaging with incoherent compounding, and aperture domain model image reconstruction (ADMIRE).

Materials and methods

The ultrasound techniques were evaluated in an in vitro kidney stone model and in a pilot study of 5 human stone formers (n = 6 stones). Stone contrast, contrast-to-noise ratio (CNR), sizing, posterior shadow contrast, and shadow width sizing were compared among the different techniques and to B-mode. CT imaging within 60 days was considered the gold standard stone size. Paired t-tests using Bonferroni correction were performed to evaluate comparing each technique with B-mode.

Results

Mean CT measured stone size was 6.0mm (range 2.9-12.2mm) with mean skin-to-stone distance 10.2cm (range 5.4-16.3cm). Compared to B-mode, stone contrast was best with ADMIRE (mean +12.2dB), while SLSC and MLSC showed statistically improved CNR. Sizing was best with ADMIRE (mean +1.3mm error), however this was not significantly improved over B-mode (+2.4mm). PWSF performed similarly to B-mode for stone contrast, CNR, SNR, and stone sizing. In the in vitro model, the shadow contrast was highest with ADMIRE (mean 10.5 dB vs 3.1 dB with B-mode). Shadow sizing was best with SLSC (mean error +0.9mm ± 2.9), however the difference compared to B-mode was not significant.

Conclusions

The detection and sizing of stones are feasible with advanced beamforming methods with ultrasound. ADMIRE, SLSC, and MLSC hold promise for improving stone detection, shadow contrast, and sizing.

SUBMITTER: Hsi RS 

PROVIDER: S-EPMC6112662 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC10458485 | biostudies-literature
| S-EPMC8189081 | biostudies-literature
| S-EPMC5918768 | biostudies-literature
2023-10-24 | PXD033298 | Pride
| S-EPMC10017605 | biostudies-literature
| S-EPMC7734295 | biostudies-literature
| S-EPMC4138059 | biostudies-literature
| S-EPMC7937251 | biostudies-literature
| S-EPMC3339356 | biostudies-literature
| S-EPMC6556766 | biostudies-other