Assessing the anatomical characteristics of renal masses has a limited effect on the prediction of pathological outcomes in solid, enhancing, small renal masses: results using the PADUA classification system.

Tae Young Shin; Jongchan Kim; Kyo Chul Koo; Sey Kiat Lim; Dong Wook Kim; Min Woong Kang; Koon Ho Rha; Young Deuk Choi; Won Sik Ham

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Assessing the anatomical characteristics of renal masses has a limited effect on the prediction of pathological outcomes in solid, enhancing, small renal masses: results using the PADUA classification system.

机译：评估肾肿块的解剖学特征对固体，增强，小肾肿块的病理结果预测有有限的影响：使用帕多瓦分类系统的结果。

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摘要

Age, sex and tumour size are the primary predictors of tumour pathology of SRMs, and incorporating other anatomical characteristics has only a limited positive effect on the accuracy of prediction of pathological outcomes.

机译：年龄，性和肿瘤大小是SRMS肿瘤病理的主要预测因子，并掺入其他解剖学特征对病理结果预测的准确性仅具有有限的积极作用。

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《BJU international》 |2014年第5期|共8页
作者
Tae Young Shin; Jongchan Kim; Kyo Chul Koo; Sey Kiat Lim; Dong Wook Kim; Min Woong Kang; Koon Ho Rha; Young Deuk Choi; Won Sik Ham;
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Department of Urology Hallym University College of Medicine Chuncheon Korea;

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正文语种 eng
中图分类泌尿科学（泌尿生殖系疾病）;
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1. Assessing the anatomical characteristics of renal masses has a limited effect on the prediction of pathological outcomes in solid, enhancing, small renal masses: results using the PADUA classification system. [J] . Tae Young Shin, Jongchan Kim, Kyo Chul Koo, BJU international . 2014,第5期

机译：评估肾脏肿块的解剖特征对实体，增强的小肾脏肿块的病理结果的预测效果有限：使用PADUA分类系统的结果。
2. Multislice computed tomography versus contrast-enhanced ultrasound in evaluation of complex cystic renal masses using the Bosniak classification system. [J] . Clevert DA, Minaifar N, Weckbach S, Clinical hemorheology and microcirculation . 2008,第1a4期

机译：使用Bosniak分类系统，多层螺旋CT与对比增强超声在评估复杂的囊性肾脏肿块中的价值。
3. Deep learning based classification of solid lipid-poor contrast enhancing renal masses using contrast enhanced CT [J] . Oberai Assad, Varghese Bino, Cen Steven, British Journal of Radiology . 2020,第1111期

机译：基于深度学习的固体脂质差对比度增强肾肿块的分类增强CT
4. Wavelets analysis for differentiating solid, non-macroscopic fat containing, enhancing renal masses: a pilot study [C] . Bino Varghese, Darryl Hwang, Passant Mohamed, 13th international conference on medical information processing and analysis . 2017

机译：小波分析以区分固体，非宏观脂肪，增加肾脏质量：一项初步研究
5. Role of Active Surveillance and Volume Monitoring in Patients with Small Renal Masses. [D] . Nikkhou, Kiavash. 2012

机译：主动监测和体积监测在小肾脏肿块患者中的作用。
6. Deep learning based classification of solid lipid-poor contrast enhancing renal masses using contrast enhanced CT [O] . Assad Oberai, Bino Varghese, Steven Cen, 2020

机译：基于深度学习的固体脂质差对比度的分类使用对比度增强CT增强肾肿块
7. Comparison of partial nephrectomy and percutaneous radiofrequency ablation for small renal masses in the manner of preoperative aspects and dimensions used for an anatomical (padua) classification [O] . Wei-Ting Kuo, Lun-Hsiang Yuan, Yin-Shen Chen, 2015

机译：以解剖学（padua）分类的术前方面和尺寸的方式比较部分肾切除术和经皮射频消融治疗小肾肿块

Assessing the anatomical characteristics of renal masses has a limited effect on the prediction of pathological outcomes in solid, enhancing, small renal masses: results using the PADUA classification system.

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