Since LPN was first reported by Winfield et al in 1993 [19], it has increasingly become a preferred approach for the surgical management of cT1 renal masses, given evidence supporting similar oncologic efficacy and better perioperative outcomes compared to open PN [4–6]. However, LPN is technically challenging because it requires not only a negative surgical margin resection but time-dependent renal reconstruction [20]. The implementation of LPN is affected by a variety of factors, including tumor size, location, depth, and its relationship to renal hilar vessels and the urinary collecting system. Several scoring systems that quantify renal tumor anatomical factors have been developed to evaluate the surgical complexity and perioperative outcomes. Among them, the PADUA classification system, C-index, and RENAL nephrometry score system are the most widely used algorithms [8–10]. Nevertheless, these algorithms focus entirely on tumor-specific factors and ignore patient-specific factors that may also play an essential role in the LPN procedure.
It is not an uncommon occurrence when performing PN that thick and adherent perinephric adipose tissues within the Gerota’s fascia complicate the exposure of the renal parenchyma and tumor. As a notable patient-specific factor, APF has attracted much attention in the last decade. Prior studies have demonstrated that the presence of APF can result in adverse perioperative outcomes during MIPN. Kocher and colleagues revealed a statistically significant association among APF, longer operative time, and higher estimated blood loss [12]. Additionally, Khene et al emphasized an elevated risk of conversion to open surgery or radical nephrectomy in patients with APF [13]. Similarly, in a large cohort of patients with RCC that underwent LPN, our data also identified APF as significantly correlated with an increased estimated blood loss (P = 0.003) and operative time (P < 0.001). We observed that APF had no impact on the surgical margins and postoperative complications. Additionally, under comparable surgeons’ experience and tumor complexity, the warm ischemia time in cases with APF was 4 min longer than in those without APF (P = 0.001), which agreed with the finding from Borregales et al [21]. The possible explanation for these results is as follows, adherent perinephric adipose tissues are more brittle and prone to bleeding, and when exposing and resecting the renal tumor, a blurred boundary caused by APF usually requires subcapsular dissection and an expanded scope of resection to ensure a negative surgical margin (Fig. 1), which further increases bleeding and suture difficulty and prolongs the warm ischemia time and operative time.
In view of the adverse perioperative outcomes associated with APF, a series of studies have been performed to investigate its physiologic mechanism and predictive factors. While the underlying pathogenesis of APF remains unclear, studies suggest that inflammation, idiopathic fibrosis, and the autoimmune response may account for APF [22]. Previous basic research has indicated the contributions of inflammation and fibrosis to abnormal adipose tissue expansion in obesity. Inflammation can lead to hypoxia and fibrosis in adipocytes, which can, in turn, promote the migration of immune cells into adipose depots [23]. As an index of obesity, the role of BMI in predicting APF is contentious. According to our univariate analysis, BMI was found to be closely associated with APF (P = 0.002), and similar findings were confirmed in other studies [13, 14]. However, it has also been argued that there is no significant correlation between BMI and APF [12], probably because BMI does not accurately reflect the variation in fat distribution, especially visceral fat (obesity), which is strongly related to metabolic syndrome [24]. This variation manifests in gender as well, as women have more subcutaneous fat than men, while men have more perirenal fat than women [15]. As a result, most studies, including ours, indicate that males have a higher incidence of APF (P = 0.001). Furthermore, other clinical factors predicting the presence of APF, such as age, cardiovascular disease, and diabetes mellitus, have been reported in a few studies [12–14, 21]. Notably, in the present study, we found that APF correlated with a decreased preoperative level of eGFR (P = 0.004), which may suggest that a chronic inflammatory response participates in the formation of APF [25].
To further investigate the predictors of APF, the radiographic parameters were analyzed at the same time. Posterior perinephric fat thickness, as a measurement of intra-abdominal fat, has a significant relationship with APF and complications of MIPN [11, 14]. Perinephric fat stranding was initially observed in cross-sectional imaging under inflammatory conditions, such as pyelonephritis and ureteral obstruction [16], and has also been identified in cases of APF recently. Based on these two radiographic factors, a semiquantitative scoring system called the MAP score has been proposed to predict APF during RAPN [14]. Our multivariate analysis revealed that the MAP score was an independent predictor of APF (P < 0.001), providing concomitant external validation in a large cohort of LPN.
As mentioned above, the pathogenesis of APF may correlate with inflammation, while cancer-related inflammation is known to be involved in tumor development and progression, including RCC [26]. Kocher et al showed that APF was associated with malignant renal histology (versus benign disease) [12], and Thiel and colleagues revealed that high MAP scores were related to decreased progression-free survival of RCC [27]. Interestingly, our study failed to elucidate the association between APF and tumor aggressive behaviors.
There are several limitations in this study. First, although we performed our investigation on the same patient population (RCC) with the same surgical approach (LPN), the retrospective nature of this study might introduce selection and recall bias. Second, the limited number of single-center patients with APF and the relatively strong correlations among previously mentioned clinical factors made the application of multivariate model analysis challenging. Third, our subjective definition of APF that follows that of most studies could still be debated.