Non-contrast CT radiomics for identifying nonfunctioning kidneys: a multicenter development and external validation study.

IF 2.2 4区 医学 Q3 UROLOGY & NEPHROLOGY
Yufei Jiang, Yihan Zheng, Zechen Feng, Liuru Bao, Qiang Wei
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引用次数: 0

Abstract

Purpose: In urological practice, the decision to resect or preserve a kidney with obstruction, tumor or atrophy is based on split renal function, although SPECT renal dynamic scintigraphy as the reference standard is resource-intensive. We developed and externally validated a non-contrast CT radiomics model to identify nonfunctioning kidneys and support urological decision-making in this setting.

Methods: In this three-center retrospective study (TRIPOD+AI), adults underwent non-contrast CT and SPECT renal dynamic scintigraphy within 72 h. IBSI-compliant radiomics features were extracted with PyRadiomics, and between-kidney asymmetry features were constructed. After three-stage selection (Spearman, recursive feature elimination, and LASSO), 12 machine learning models were developed and externally validated in 2 independent cohorts. A Rad-score and clinical nomogram were also derived.

Results: Among 1029 patients, the internal cohort included 418 patients. Twenty-three of features were retained. The random forest model yielded an internal test AUC of 0.9426, sensitivity of 85.5%, specificity of 88.3%, and negative predictive value of 95.6%. Its external AUCs were 0.875 and 0.913. The nomogram attained external AUCs of 0.920 and 0.881. At the thresholds fixed in the training data, the random forest achieved external sensitivity of 66.0 and 76.4% with negative predictive values of 94.8 and 93.3%, and the nomogram 92.5 and 93.7% with 98.3 and 97.2%. Both radiomics models outperformed logistic-regression baselines built from clinical variables and simple CT size and asymmetry measurements, although the margin over the combined baseline was not statistically significant in one external cohort. The Rad-score was correlated with single-kidney GFR (ρ = -0.738, P < 0.001) and facilitated risk stratification.

Conclusion: Non-contrast CT radiomics identified nonfunctioning kidneys without contrast agents or radiotracers. Because non-contrast CT is already part of routine urological workup, this externally validated rule-out tool may reduce unnecessary SPECT examinations and support decisions between nephrectomy and nephron-sparing management.

鉴别无功能肾脏的非对比CT放射组学:一项多中心发展和外部验证研究。
目的:在泌尿外科实践中,切除或保留梗阻、肿瘤或萎缩肾脏的决定是基于肾功能分裂,尽管SPECT肾动态显像作为参考标准需要耗费大量资源。我们开发并外部验证了一种非对比CT放射组学模型来识别无功能肾脏,并在这种情况下支持泌尿科决策。方法:在这项三中心回顾性研究(TRIPOD+AI)中,成年人在72小时内进行了非对比CT和SPECT肾脏动态扫描。使用PyRadiomics提取符合ibsi的放射组学特征,并构建肾间不对称特征。经过三个阶段的选择(Spearman、递归特征消除和LASSO),我们开发了12个机器学习模型,并在2个独立的队列中进行了外部验证。并得出了rad评分和临床nomogram。结果:1029例患者中,内部队列纳入418例患者。23个功能被保留。随机森林模型的内部检验AUC为0.9426,灵敏度为85.5%,特异性为88.3%,阴性预测值为95.6%。其外部auc分别为0.875和0.913。图外auc分别为0.920和0.881。在训练数据中固定的阈值下,随机森林的外灵敏度分别为66.0和76.4%,负预测值分别为94.8和93.3%;nomogram外灵敏度分别为92.5和93.7%,预测值分别为98.3%和97.2%。两种放射组学模型都优于由临床变量和简单CT大小和不对称测量建立的logistic回归基线,尽管在一个外部队列中,超过联合基线的裕度没有统计学意义。rad评分与单肾GFR相关(ρ = -0.738, P < 0.001),有利于风险分层。结论:非对比CT放射组学可以在不使用对比剂或放射性示踪剂的情况下识别非功能肾脏。由于非对比CT已经是常规泌尿系统检查的一部分,这种外部验证的排除工具可以减少不必要的SPECT检查,并支持肾切除术和保留肾管理之间的决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Urology and Nephrology
International Urology and Nephrology 医学-泌尿学与肾脏学
CiteScore
3.40
自引率
5.00%
发文量
329
审稿时长
1.7 months
期刊介绍: International Urology and Nephrology publishes original papers on a broad range of topics in urology, nephrology and andrology. The journal integrates papers originating from clinical practice.
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