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预测自发性输尿管结石排出:自动化 3D 测量与放射科医生相当,线性测量与体积测量相当。

Prediction of spontaneous ureteral stone passage: Automated 3D-measurements perform equal to radiologists, and linear measurements equal to volumetric.

机构信息

Department of Radiology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.

出版信息

Eur Radiol. 2018 Jun;28(6):2474-2483. doi: 10.1007/s00330-017-5242-9. Epub 2018 Jan 24.

DOI:10.1007/s00330-017-5242-9
PMID:29368161
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5938294/
Abstract

OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

KEY POINTS

• An automated 3D technique predicts spontaneous stone passage with high accuracy. • Linear, areal and volumetric measurements performed similarly in predicting stone passage. • Reader variability has a large impact on the predicted prognosis for stone passage.

摘要

目的

比较不同大小估计值预测输尿管结石自发排出的能力,使用三维分割,并探讨手动测量变异性对结石排出预测的影响。

方法

我们回顾性纳入了 391 例非增强 CT(NECT)上的输尿管结石连续患者。将三维分割大小估计值与三位放射科医生测量的平均值进行比较。对每个估计值进行自发通过的预测进行接收者操作特征(ROC)分析。比较上下结石中手动估计值之间预测通过概率的差异。

结果

ROC 曲线下面积(AUC)的测量值范围为 0.88 至 0.90。在自动 3D 算法和手动测量之间,宽度的 95%一致性界限为 0.2 ± 1.4mm。在 44%的上输尿管结石和 6%的下输尿管结石中,手动骨窗测量导致预测通过概率的读者之间差异超过 20 个百分点。

结论

所有自动 3D 算法大小估计值均独立预测自发结石通过,准确性与三位读者手动线性测量的平均值相似。上尿路结石的手动大小估计对自发通过的预测显示出较大的读者间变异性。

关键点

• 一种自动 3D 技术可以高精度预测结石自发排出。• 线性、面积和体积测量在预测结石排出方面表现相似。• 读者变异性对结石排出的预测预后有很大影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/54300266af8d/330_2017_5242_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/b8af43e6b6fb/330_2017_5242_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/4d69bd10d434/330_2017_5242_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/ddeb7d2963af/330_2017_5242_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/da46e64a3a3d/330_2017_5242_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/26e4ef7bd9db/330_2017_5242_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/54300266af8d/330_2017_5242_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/b8af43e6b6fb/330_2017_5242_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/4d69bd10d434/330_2017_5242_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/ddeb7d2963af/330_2017_5242_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/da46e64a3a3d/330_2017_5242_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/26e4ef7bd9db/330_2017_5242_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2df4/5938294/54300266af8d/330_2017_5242_Fig6_HTML.jpg

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