Yuhang Xie1, Mengmiao Xu1, Yajie Chen1, Xiaolan Zhu2, Shenghong Ju3, Yuefeng Li4,5. 1. Department of Radiology, Affiliated Hospital of Jiangsu University, No. 438, Jiefang Road, Zhenjiang, 212001, Jiangsu, China. 2. Department of Central Laboratory, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang, 212001, Jiangsu, China. 13775552517@163.com. 3. Department of Radiology, Southeast University Affiliated Zhongda Hospital, No. 87, Dingjiaqiao Road, Nanjing, 210009, Jiangsu, China. jshtougao666@126.com. 4. Department of Radiology, Affiliated Hospital of Jiangsu University, No. 438, Jiefang Road, Zhenjiang, 212001, Jiangsu, China. jiangdalyf@163.com. 5. Department of Central Laboratory, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang, 212001, Jiangsu, China. jiangdalyf@163.com.
Abstract
OBJECTIVE: Although the guideline indicates that total kidney volume (TKV) is an important detection indicator in patients with autosomal dominant polycystic kidney disease (ADPKD), this study attempted to demonstrate that renal parenchymal information, combined with parenchymal volume and radiomics features, may have more valuable clinical guiding significance. METHODS: A totals of 340 ADPKD patients with normal renal function were prospectively collected and followed-up for five years, with renal function tests and non-contrast computed tomography (CT) performed every six months. The relationship between renal function impairment and renal parenchymal volume (RPV) as along with radiomics features was explored using a multiple linear regression model and multiple logistic regression. Then, a combined model of RPV with radiomics features was constructed to comprehensively evaluate its predictive value. RESULTS: Compared with TKV, decreased RPV presented a closer relationship with renal function impairment, namely, with the impairment rate (RPV: 82.3% vs. TVK: 67.1%) and eGFR (RPV: r = 0.614, p < 0.001 vs. TKV: r = -0.452, p < 0.001), and showed higher predictive power (RPV: AUC = 0.752 [95%CI 0.692-0.805], p < 0.001 vs. TKV: AUC = 0.711 [95%CI 0.649-0.768], p < 0.001). Correspondingly, the radiomics analysis that was derived from the renal parenchyma also showed a satisfactory result (AUC = 0.849 [95%Cl 0.797-0.892], p < 0.001). Importantly, the predictive power for renal function impairment was further improved in the combined model of RPV and radiomics features (AUC = 0.902 [95%Cl 0.857-0.937], p < 0.001). CONCLUSION: Renal parenchyma information may be a sensitive biomarker of renal function impairment in ADPKD, which can provide a new approach for clinically monitoring renal function, and may greatly improve the pre-hospital prevention and treatment effects.
OBJECTIVE: Although the guideline indicates that total kidney volume (TKV) is an important detection indicator in patients with autosomal dominant polycystic kidney disease (ADPKD), this study attempted to demonstrate that renal parenchymal information, combined with parenchymal volume and radiomics features, may have more valuable clinical guiding significance. METHODS: A totals of 340 ADPKD patients with normal renal function were prospectively collected and followed-up for five years, with renal function tests and non-contrast computed tomography (CT) performed every six months. The relationship between renal function impairment and renal parenchymal volume (RPV) as along with radiomics features was explored using a multiple linear regression model and multiple logistic regression. Then, a combined model of RPV with radiomics features was constructed to comprehensively evaluate its predictive value. RESULTS: Compared with TKV, decreased RPV presented a closer relationship with renal function impairment, namely, with the impairment rate (RPV: 82.3% vs. TVK: 67.1%) and eGFR (RPV: r = 0.614, p < 0.001 vs. TKV: r = -0.452, p < 0.001), and showed higher predictive power (RPV: AUC = 0.752 [95%CI 0.692-0.805], p < 0.001 vs. TKV: AUC = 0.711 [95%CI 0.649-0.768], p < 0.001). Correspondingly, the radiomics analysis that was derived from the renal parenchyma also showed a satisfactory result (AUC = 0.849 [95%Cl 0.797-0.892], p < 0.001). Importantly, the predictive power for renal function impairment was further improved in the combined model of RPV and radiomics features (AUC = 0.902 [95%Cl 0.857-0.937], p < 0.001). CONCLUSION: Renal parenchyma information may be a sensitive biomarker of renal function impairment in ADPKD, which can provide a new approach for clinically monitoring renal function, and may greatly improve the pre-hospital prevention and treatment effects.
Authors: Arlene B Chapman; James E Bost; Vicente E Torres; Lisa Guay-Woodford; Kyongtae Ty Bae; Douglas Landsittel; Jie Li; Bernard F King; Diego Martin; Louis H Wetzel; Mark E Lockhart; Peter C Harris; Marva Moxey-Mims; Mike Flessner; William M Bennett; Jared J Grantham Journal: Clin J Am Soc Nephrol Date: 2012-02-16 Impact factor: 8.237
Authors: Robert W Schrier; Godela Brosnahan; Melissa A Cadnapaphornchai; Michel Chonchol; Keith Friend; Berenice Gitomer; Sandro Rossetti Journal: J Am Soc Nephrol Date: 2014-06-12 Impact factor: 10.121
Authors: Ronald D Perrone; Mohamad-Samer Mouksassi; Klaus Romero; Frank S Czerwiec; Arlene B Chapman; Berenice Y Gitomer; Vicente E Torres; Dana C Miskulin; Steve Broadbent; Jean F Marier Journal: Kidney Int Rep Date: 2017-01-16