AbstractThe study focused on the application value of the space compounding algorithm‐based colour Doppler ultrasound twinkling artefacts in predicting chemical components of urinary tract stones. Specifically, the minimum variance method was used to optimize the space‐compounding algorithm to improve the quality of colour Doppler ultrasound artefacts. Then, the urinary system stone model was built to quantitatively analyse the influence of stone components on colour Doppler twinkling artefacts. The results showed that no notable differences were noted in the twinkling artefact intensity (TAI), the width of twinkling artefact (TAW), and the length of twinkling artefact (TAL) between the oxalic acid monohydrate, hydroxyapatite, uric acid, and cystine stone models (p < 0.01). The area under the curve (AUC) of the TAI for the diagnosis of calcium‐free calculus models was 0.978, that of TAW was 0.9462, and that of TAL was 0.9315. The diagnostic sensitivity and specificity of TAI were 89% and 96%, respectively, the diagnostic sensitivity and specificity of TAW were 86% and 80%, respectively, and the diagnostic sensitivity and specificity of TAL were 78% and 97%, respectively. The ability of TAL (AUC of 0.953) to distinguish between hydroxyapatite stone model and cystine stone was better than TAI (AUC of 0.702) and TAW (AUC of 0.657) (p < 0.01); and TAL and TAW were positively correlated with TAI (R2 was 0.79 and 0.68, respectively, p < 0.01). In conclusion, the space compounding algorithm based on minimum variance method can improve the quality of colour Doppler ultrasound twinkling artefacts, and colour Doppler ultrasound twinkling artefacts can predict the chemical components of urinary stones, which can be used as a criterion for clinical diagnosis.
Read full abstract