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1.
Urolithiasis ; 47(2): 181-188, 2019 Apr.
Article in English | MEDLINE | ID: mdl-29356874

ABSTRACT

Ultrasound imaging for kidney stones suffers from poorer sensitivity, diminished specificity, and overestimation of stone size compared to computed tomography (CT). The purpose of this study was to demonstrate in vitro feasibility of novel ultrasound imaging methods comparing traditional B-mode to advanced beamforming techniques 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). The ultrasound techniques were evaluated using a research-based ultrasound system applied to an in vitro kidney stone model at 4 and 8 cm depths. Stone diameter sizing and stone contrast were compared among the different techniques. Analysis of variance was used to analyze the differences among group means, with p < 0.05 considered significant, and a Student's t test was used to compare each method with B-mode, with p < 0.0025 considered significant. All stones were detectable with each method. MLSC performed best with stone sizing and stone contrast compared to B-mode. On average, B-mode sizing error ± SD was > 1 mm (1.2 ± 1.1 mm), while those for PWSF, ADMIRE, and MLSC were < 1 mm (- 0.3 ± 2.9 mm, 0.6 ± 0.8, 0.8 ± 0.8, respectively). Subjectively, MLSC appeared to suppress the entire background thus highlighting only the stone. The ADMIRE and SLSC techniques appeared to highlight the stone shadow relative to the background. The detection and sizing of stones in vitro are feasible with advanced beamforming methods with ultrasound. Future work will include imaging stones at greater depths and evaluating the performance of these methods in human stone formers.


Subject(s)
Image Processing, Computer-Assisted/methods , Kidney Calculi/diagnostic imaging , Kidney/diagnostic imaging , Algorithms , Feasibility Studies , Humans , Sensitivity and Specificity , Ultrasonography/methods
2.
PLoS One ; 13(8): e0203138, 2018.
Article in English | MEDLINE | ID: mdl-30153279

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.


Subject(s)
Kidney Calculi/diagnostic imaging , Ultrasonography/methods , Aged , Algorithms , Feasibility Studies , Female , Humans , Male , Middle Aged , Nonlinear Dynamics , Pattern Recognition, Automated/methods , Pilot Projects , Prospective Studies , Tomography, X-Ray Computed
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