Publikation

Advanced non-contrasted computed tomography post-processing by CT-Calculometry (CT-CM) outperforms established predictors for the outcome of shock wave lithotripsy

Wissenschaftlicher Artikel/Review - 29.05.2018

Bereiche
PubMed
DOI

Zitation
Langenauer J, Betschart P, Hechelhammer L, Güsewell S, Schmid H, Engeler D, Abt D, Zumstein V. Advanced non-contrasted computed tomography post-processing by CT-Calculometry (CT-CM) outperforms established predictors for the outcome of shock wave lithotripsy. World J Urol 2018; 36:2073-2080.
Art
Wissenschaftlicher Artikel/Review (Englisch)
Zeitschrift
World J Urol 2018; 36
Veröffentlichungsdatum
29.05.2018
eISSN (Online)
1433-8726
Seiten
2073-2080
Kurzbeschreibung/Zielsetzung

OBJECTIVES
To evaluate the predictive value of advanced non-contrasted computed tomography (NCCT) post-processing using novel CT-calculometry (CT-CM) parameters compared to established predictors of success of shock wave lithotripsy (SWL) for urinary calculi.

MATERIALS AND METHODS
NCCT post-processing was retrospectively performed in 312 patients suffering from upper tract urinary calculi who were treated by SWL. Established predictors such as skin to stone distance, body mass index, stone diameter or mean stone attenuation values were assessed. Precise stone size and shape metrics, 3-D greyscale measurements and homogeneity parameters such as skewness and kurtosis, were analysed using CT-CM. Predictive values for SWL outcome were analysed using logistic regression and receiver operating characteristics (ROC) statistics.

RESULTS
Overall success rate (stone disintegration and no re-intervention needed) of SWL was 59% (184 patients). CT-CM metrics mainly outperformed established predictors. According to ROC analyses, stone volume and surface area performed better than established stone diameter, mean 3D attenuation value was a stronger predictor than established mean attenuation value, and parameters skewness and kurtosis performed better than recently emerged variation coefficient of stone density. Moreover, prediction of SWL outcome with 80% probability to be correct would be possible in a clearly higher number of patients (up to fivefold) using CT-CM-derived parameters.

CONCLUSIONS
Advanced NCCT post-processing by CT-CM provides novel parameters that seem to outperform established predictors of SWL response. Implementation of these parameters into clinical routine might reduce SWL failure rates.