達文西機械手臂輔助部份腎臟切除中沾黏性腎周圍脂肪之預測因子
張雲筑1、程威銘1、鍾孝仁1,2、林登龍1,2、陳光國1,2
台北榮民總醫院泌尿部1
國立陽明大學醫學系泌尿學科2
Prediction of adherent perinephric fat inRobotic-assisted partial nephrectomy
Yun-Chu Chang1, Wei-Ming Cheng 1, Hsiao-Jen Chung1, 2,
Alex T. L. Lin1, 2, Kuang-Kuo Chen1, 2
1 Department of Urology, Taipei Veterans General Hospital
2 Department of Urology, School of Medicine, National Yang-Ming University
Introduction:
Robotic-assisted partial nephrectomy (RAPN) is a challenging procedure, especially for young urologists with limited experiences. Several image-based scoring systems have been proposed to predict the anatomical complexity of the operation; however, adhesive perirenal fat (APF) is also an important patient-specific factor that would increase the difficulty in mobilization of the kidney as well as isolation of the renal mass in RAPN. It is hardly predicted by these well-known scoring system . In the present study, we tried to find out the preoperative predictive factors for APF in patients undergoing RAPN.
Materials and methods:
We prospectively collected patients undergoing RAPN by one single experienced urologist in our institutes from August, 2013 to October, 2014. All the procedures were standardized. The presence of APF, the duration and the difficulty of kidney morbilization / tumor isolation were judged by another urologist independently. Presence of fat stranding, thickness and Housefield Unit (HU) of medial, lateral, anterior, and posterior aspects of perirenal fat at the same side of the renal mass at the level of renal vein on preoperative noncotrast-enhanced transverse CT images, as well as the recently proposed Mayo adhesive probability score (MAPS = degree of fat stranding + thickness of posterior perirenal fat) and perirenal fat density (PFD = total HU / surface area) were recorded by a third urologist who was blind to the surgical details. These image-based factors, along with other demographic data including age at surgery, sex, body weight index (BMI), preoperative biochemical profiles, and comorbidities, were correlated with perioperative surgical outcomes, including presence of APF, operation time, surgical difficulty, estimated blood loss, conversion to open surgery, length of hospital stay, and early compliations within 30 days. Fisher’s exact test and Mann-Whitney test were used for univariate analysis while stepwise correlation was used for multivariate analysis. p value less than 0.05 was defined as statistical significance.
Results:
A total of consecutive 42 patients were included. The mean age at surgery was 58.2 ± 13.1 years and mean BMI was 25.3 ± 3.9 kg/m2.17 patients were female(40.4%) and 18 (42.9%) patients had their tumor at right side. APF was observed in 11 patients(26.0%), and moderate to severe difficulty in kidney mobilization / tumor isolation was noticed in 20 (47.6%) patients. The mean time needed for this step was 50.1 ± 38.5 minutes. The presence of APF was significantly associated with the kidney mobilization / tumor isolation time (83.7 ± 43.0 minutes vs. 38.1 ± 25.6 minutes. p = 0.01) and degree of difficulty (for moderate to severe difficulty, 11(100%) vs. 9(29%), p < 0.001). On univariate analysis, presence of comorbid type 2 diabetes mellitus (5 out of 11 vs. 2 out of 31 p =0.009), presence of diffuse fat stranding(2 out of 11 vs.0 out of 31 p = 0.02), level of preoperative creatinine (OR=17.9, p = 0.036), medial fat thickness (OR=3.9, p = 0.003), and MAPS(p = 0.005), were significantly associated with APF. Other factors were failed to show any significance.
Conclusion:
APF was an important patient-specific factor that would impose adverse effect on time and difficulty of kidney mobilization and tumor isolation. Image-based MAPS could be a preoperative predictor for the presence of APF during RAPN in our study.