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开发一种新的网格模型来定义一个新的指标“结石量”,以评估结石并预测碎石时间。

Development of a novel mesh model to define a new index "amount of stone" to evaluate calculus and predicting the lithotripsy time.

机构信息

Department of Urology, Huai'an First Affiliated Hospital of Nanjing Medical University, No. 6 West Beijing Road, Huai'an, 223300, Jiangsu, China.

Center of Lithotripsy, Huai'an First Hospital Affiliated of Nanjing Medical University, No. 6 West Beijing Road, Huai'an, 223300, Jiangsu, China.

出版信息

Int Urol Nephrol. 2023 Oct;55(10):2431-2438. doi: 10.1007/s11255-023-03697-9. Epub 2023 Jul 13.

Abstract

OBJECTIVE

Develop a mesh model to define a new "index amount of stone" to evaluate calculus and predict lithotripsy time.

METHODS

The stones were divided into target units with diameter of 5 mm by the mesh from x, y and z directions, and the cross-sectional areas between units were calculated as amount of stone as a new index to evaluate calculus. Design a prospective study with 112 cases of percutaneous nephrolithotomy to verify the reliability of this index, and to compare the accuracy of the quantity, volume and maximum diameter of stones in predicting the time of lithotripsy.

RESULTS

Amount of stone (Q) is reliable. The lithotripsy time was significantly correlated with the amount of stone, volume and maximum diameter of the stone (p < 0.01). The three regression equations were valid. The linear fit in the amount group was larger than that in the volume group, and further larger than that in the maximum diameter group, with R values of 0.716, 0.661 and 0.471, respectively.

CONCLUSIONS

It is more accurate and convenient to use amount of stone to evaluate calculus, which can be used to predict the lithotripsy time.

摘要

目的

建立一种网格模型,以定义新的“结石指数”来评估结石并预测碎石时间。

方法

通过网格从 x、y 和 z 方向将结石划分为直径为 5mm 的目标单位,计算单位之间的截面积作为结石的量作为评估结石的新指标。设计一项前瞻性研究,纳入 112 例经皮肾镜取石术患者,验证该指标的可靠性,并比较结石数量、体积和最大直径预测碎石时间的准确性。

结果

结石量(Q)是可靠的。碎石时间与结石量、体积和最大直径均呈显著相关(p<0.01)。三个回归方程均有效。在量组中的线性拟合大于体积组,进一步大于最大直径组,R 值分别为 0.716、0.661 和 0.471。

结论

使用结石量评估结石更准确、更方便,可以用来预测碎石时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/724e/10499979/f683d40f962c/11255_2023_3697_Fig1_HTML.jpg

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