Hirofumi Shimoyama1, Shuji Isotani1, Toshiyuki China1, Masayoshi Nagata1, Isao Yokota2, Kosuke Kitamura1, Yoshiaki Wakumoto1, Hisamitsu Ide3, Satoru Muto3, Akira Tujimura1, Raizo Yamaguchi3, Shigeo Horie4,5. 1. Department of Urology, Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo, Tokyo, Japan. 2. Department of Biostatistics, School of Public Health, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 1130033, Japan. 3. Department of Urology, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi ku, Tokyo, 173-8605, Japan. 4. Department of Urology, Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo, Tokyo, Japan. shorie@juntendo.ac.jp. 5. Department of Urology, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi ku, Tokyo, 173-8605, Japan. shorie@juntendo.ac.jp.
Abstract
BACKGROUND: Renal volume change greatly affects renal function after nephrectomy. Although various measuring techniques were reported, no standard measuring method is available. In this study, we examined the computational automated volumetric method, and evaluated the volumetric change to assess the functional outcome in patients undergoing radical nephrectomy. We developed the predictive equation for postoperative renal function from volume alternation and validated the performance. METHODS: Thirty-two patients undergoing radical nephrectomy participated in this study. Renal volume was calculated using three different methods [ellipsoid method, conventional manual voxel count method for renal parenchyma (manual RPV), and automated voxel count method for renal cortex (automated RCV)] through newly developed imaging software. Statistical analysis was performed to evaluate the correlation between renal functional alternation 7 days after the nephrectomy and renal volumetric change. A simple predictive equation for the postoperative renal function by renal volume loss was developed and externally validated through another 12 cases. RESULTS: The automated RCV method had the strongest correlation between renal function alternation and RCV change (R = 0.82), than manual RPV (R = 0.69) and ellipsoid method (R = 0.50). Subsequently, a simple equation for postoperative renal function by renal volume alternation was developed: predicted postoperative estimated glomerular filtration rate (eGFR) from renal volume change = preoperative eGFR × (postoperative renal volume / preoperative renal volume). In the external validation cohort, automated RCV demonstrated the predictive performance of the constructed equations for renal function (R = 0.77). CONCLUSIONS: The computational automated RCV measurements is a simple estimation of renal functional outcome for patients undergoing radical nephrectomy.
BACKGROUND: Renal volume change greatly affects renal function after nephrectomy. Although various measuring techniques were reported, no standard measuring method is available. In this study, we examined the computational automated volumetric method, and evaluated the volumetric change to assess the functional outcome in patients undergoing radical nephrectomy. We developed the predictive equation for postoperative renal function from volume alternation and validated the performance. METHODS: Thirty-two patients undergoing radical nephrectomy participated in this study. Renal volume was calculated using three different methods [ellipsoid method, conventional manual voxel count method for renal parenchyma (manual RPV), and automated voxel count method for renal cortex (automated RCV)] through newly developed imaging software. Statistical analysis was performed to evaluate the correlation between renal functional alternation 7 days after the nephrectomy and renal volumetric change. A simple predictive equation for the postoperative renal function by renal volume loss was developed and externally validated through another 12 cases. RESULTS: The automated RCV method had the strongest correlation between renal function alternation and RCV change (R = 0.82), than manual RPV (R = 0.69) and ellipsoid method (R = 0.50). Subsequently, a simple equation for postoperative renal function by renal volume alternation was developed: predicted postoperative estimated glomerular filtration rate (eGFR) from renal volume change = preoperative eGFR × (postoperative renal volume / preoperative renal volume). In the external validation cohort, automated RCV demonstrated the predictive performance of the constructed equations for renal function (R = 0.77). CONCLUSIONS: The computational automated RCV measurements is a simple estimation of renal functional outcome for patients undergoing radical nephrectomy.
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