Prediction of spontaneous ureteral stone passage: Automated 3D-measurements perform equal to radiologists, and linear measurements equal to volumetric
Prediction of spontaneous ureteral stone passage: Automated 3D-measurements perform equal to radiologists, and linear measurements equal to volumetric
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DOI:
10.1007/s00330-017-5242-9
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发表时间:
2018-06-01
影响因子:
5.9
通讯作者:
Liden, Mats
中科院分区:
文献类型:
--
作者:
Jendeberg, Johan;Geijer, Hakan;Liden, Mats
To compare the ability of different size estimates to predict spontaneous passage of ureteral stones using a 3D-segmentation and to investigate the impact of manual measurement variability on the prediction of stone passage.We retrospectively included 391 consecutive patients with ureteral stones on non-contrast-enhanced CT (NECT). Three-dimensional segmentation size estimates were compared to the mean of three radiologists' measurements. Receiver-operating characteristic (ROC) analysis was performed for the prediction of spontaneous passage for each estimate. The difference in predicted passage probability between the manual estimates in upper and lower stones was compared.The area under the ROC curve (AUC) for the measurements ranged from 0.88 to 0.90. Between the automated 3D algorithm and the manual measurements the 95% limits of agreement were 0.2 +/- 1.4 mm for the width. The manual bone window measurements resulted in a > 20 percentage point (ppt) difference between the readers in the predicted passage probability in 44% of the upper and 6% of the lower ureteral stones.All automated 3D algorithm size estimates independently predicted the spontaneous stone passage with similar high accuracy as the mean of three readers' manual linear measurements. Manual size estimation of upper stones showed large inter-reader variations for spontaneous passage prediction.aEuro cent An automated 3D technique predicts spontaneous stone passage with high accuracy.aEuro cent Linear, areal and volumetric measurements performed similarly in predicting stone passage.aEuro cent Reader variability has a large impact on the predicted prognosis for stone passage.