Development of a radiomics model to discriminate ammonium urate stones from uric acid stones in vivo: A remedy for the diagnostic pitfall of dual-energy computed tomography

被引:1
|
作者
Zheng, Junjiong [1 ]
Zhang, Jie [1 ]
Cai, Jinhua [2 ]
Yao, Yuhui [1 ]
Lu, Sihong [1 ]
Wu, Zhuo [3 ]
Cai, Zhaoxi [3 ]
Tuerxun, Aierken [4 ]
Batur, Jesur [4 ]
Huang, Jian [1 ]
Kong, Jianqiu [1 ,5 ]
Lin, Tianxin [1 ,5 ]
机构
[1] Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Guangdong Prov Clin Res Ctr Urol Dis, Dept Urol,Guangdong Prov Key Lab Malignant Tumor E, Guangzhou 510120, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Dept Neurol, Guangzhou 510120, Guangdong, Peoples R China
[3] Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Dept Radiol, Guangzhou 510120, Guangdong, Peoples R China
[4] First Peoples Hosp Kashgar Prefecture, Dept Urol, Kashgar 844000, Xinjiang, Peoples R China
[5] Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Dept Urol, 107 Yan Jiang West Rd, Guangzhou 510120, Guangdong, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Ammonium urate; Dual-energy scanned projection radiography; Radiomics; Uric acid; Urolithiasis; PERCUTANEOUS NEPHROLITHOTOMY; EAU GUIDELINES; MANAGEMENT; UROLITHIASIS; CALCULI; CURVE;
D O I
10.1097/CM9.0000000000002866
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them. Methods: This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated. Results: When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899-0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796-0.995) and 0.870 (95% CI, 0.769-0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model. Conclusions: DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.
引用
收藏
页码:1095 / 1104
页数:10
相关论文
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