Evaluation of Perirenal Fat as a Predictor of cT 1a Renal Cortical Neoplasm Histopathology and Surgical Outcomes

Abstract

Background and Purpose:

With the increasing detection of small renal cortical neoplasms (RCNs), the preoperative prediction of histopathology has become increasingly important. Because perirenal fat (PF) is known to be metabolically active, we evaluated PF as a predictor of renal tumor histopathology.

Patients and Methods:

We retrospectively evaluated patients who underwent laparoscopic nephron-sparing procedures for cT_1a RCN at two institutions. PF was measured using the digital measuring tool function on standard imaging software, at the level of the renal hilum as the perpendicular distance between the posterior surface of the kidney and the external margin of the psoas muscle. The Mann-Whitney test and logistic regression were used to examine PF, selected demographic, clinical, and operative parameters, and their association with tumor histopathology.

Results:

Data from 250 patients were included in this study. There were 157 (63%) men and 93 (37%) women with a median body mass index (BMI) of 28 kg/m². Median tumor size was 2.4 cm, and the median PF distance was 12 mm. Significant correlations were noted between PF and sex and BMI. No significant correlations were found between PF and the operative parameters. Results of a multivariate logistic regression analysis revealed that PF (P<0.01), age (P<0.04), and tumor location (P<0.04) were significant predictors of clear-cell renal-cell carcinoma (RCC) histopathology.

Conclusions:

In this study, PF, location of tumor, and age were significant predictors of clear-cell RCC histopathology. The correlation of PF and histopathology may be useful in preoperative decision-making and surgical planning in the management of small RCN.

Introduction

O besity is a major public health issue in the United States, affecting 30% to 70% of American adults.¹ With increasing obesity prevalence, there is a growing interest to investigate the relationship between obesity metrics and the incidence, progression, and surgical outcomes of different malignancies.^2,3

Increased body mass index (BMI) and obesity have been implicated as risk factors for a number of malignancies including colon, breast, and endometrial, rectal, esophageal, and pancreatic cancer.^2
–4 There is an increasing body of evidence in the literature correlating renal-cell carcinoma (RCC) with obesity.^5,6 The pathophysiology and molecular mechanisms underlying these associations, however, are not fully understood.

Because of the positively correlated volume of visceral fat (VF) with waist circumference (WC),^7,8 several studies have previously evaluated VF as a risk factor for laparoscopic procedures.^9,10 In addition, VF has been shown to be the most metabolically active type of fat and is associated with a variety of cancer types.^11,12 Although the exact role of the hormones and cytokines is unknown, the perirenal fat (PF) may have more far-reaching implications than just technical surgical outcome in RCC cases.

In the current study, we evaluated PF as noninvasive metric to help the practicing urologist identify small (T_1a) renal cortical neoplasms (RCNs), which have the greatest potential to be clinically significant in the patient's lifetime. As such, our primary goal was not to correlate PF with malignant RCN, but rather to correlate PF with those malignant small RCNs that had the highest probability of rapid growth and possible metastasis. The separate evaluation and significantly different outcomes associated with different RCC histopathologic variants is already well recognized and documented by the oncologic community in urology. Different RCC subtypes are very different tumors with recognized differences in survival outcomes^13,14 As such, when evaluating PF, we chose to evaluate its association with conventional (clear-cell) RCC (ccRCC) rather than just with renal malignancy; conventional RCC is by far the most common RCC variant, and it is recognized as an aggressive subtype. To our knowledge, this is the first study that attempts to correlate PF and RCN histopathology.

Patients and Methods

The current study was conducted with approval from the Institutional Review Boards of the participating centers. We performed a retrospective chart review on all patients who had undergone laparoscopic partial nephrectomy (LPN) or laparoscopic cryoablation (LCA) for T_1a RCN performed by two surgeons (JL and MV) between October 2004 and April 2010. The 2002 American Joint Committee on Cancer Tumor-Node-Metastasis classification defined pathologic stage T₁. Tumor size was determined as the maximal diameter of the surgical specimen of a primary lesion and was available for all surgical specimens. Only patients with preoperative renal CT or MRI scans that were available for evaluation were included in the study. Patients without evaluable imaging studies or without definitive final histopathology were excluded.

Patients with a history of ipsilateral extirpative or ablative renal surgery were also excluded from evaluation because of the potential alteration of the perinephric fat that could occur from the previous procedures. Patients with tumors larger than 4 cm in diameter and multifocal tumors were excluded. In addition, patients with renal tumors that were located posteriorly at the level of renal hilum (location where measurements were taken) were excluded to avoid any errors in PF measurement.

All preoperative CT and MRI scans were reviewed by a single urologist (ZO). The quantity of PF was evaluated by measuring the perpendicular distance between the kidney's posterior surface and the external margin of iliopsoas at the level of the renal hilum, using the ruler function on the applicable radiologic software (Fig. 1). To verify the reproducibility of the PF measurement, a second fellowship-trained urologist was asked to measure PF on a subset (n=78) of patients after receiving a brief instruction.

FIG. 1.

Measurement of perirenal fat distance.

In addition to the PF measurement, patients' demographics as well as clinical information, including body mass index (BMI), size and location of renal lesion along with histopathology reports, were recorded and analyzed. The lesion location was classified as described by Finley and colleagues,¹⁵ based on the percent of tumor that extends beyond the renal parenchymal contour; exophytic tumors have more than 60% of their mass outside the natural contour of the kidney. Endophytic tumors have greater than 60% of their mass within the natural border of the kidney, and mesophytic tumors have 40% to 60% of their mass in either direction. Measured operative parameters evaluated were operative (OR) time, estimated blood loss (EBL), transfusion rate, intraoperative complications, conversion rate, postoperative complications, length of hospital stay (LOS), and warm ischemia time (WIT, lapoaroscopic partial nephrectomy [LPN] only). Histopathology for RCC variants was dichotomized into conventional (ccRCC) vs other (Table 1).

Table 1.

Frequencies for Histopathology Subtypes

Pathology	Frequency	Percent
Adipose tissue	19	7.6
Angiomyolypoma	11	4.4
B-cell Hodgkin lymphoma	1	0.4
Cyst	6	2.4
Oncocytoma	29	11.6
RCC chromophobe	22	8.8
RCC clear-cell	127	50.8
RCC papillary	34	13.6
Nondiagnostic	1	0.4

RCC=renal-cell carcinoma.

Statistical methods

The Spearman correlation coefficient was computed to measure the degree of correlation between PF and demographic (age, sex), clinical (BMI, lesion size, location of lesion), and operative variables (OR time, EBL, WIT, postoperative complications, and transfusion rate). Interclass correlation using analysis of variance was used to evaluate the variation between the two urologists' measures of PF (interclass correlation was used because neither surgeon's measures could be considered a “gold standard”). The Mann-Whitney test was used to determine the association between the histopathology (ccRCC vs other) groups and factors such as PF and BMI. Using a P value < 0.25 as the criterion, univariate analyses were conducted to select preoperative and operative variables for inclusion into a multivariate regression model. Multivariate logistic regression was used to explore the joint effects of PF and selected factors on histopathology. A P value < 0.05 was considered significant. Data were analyzed using SAS Version 9.2 (Cary, NC: SAS Institute, 2002–2008).

Results

Two hundred and fifty patients with T_1a RCN (≤4 cm) were identified who met our inclusion and exclusion criteria. The study group included 157 (63%) men and 93 (37%) women. Median age was 61 years and ranged from 22 to 82. BMI ranged from 13.5 to 55 kg/m², with a median BMI of 28 kg/m². There were 196 (78.4%) patients who underwent LPN and 54 (21.6%) patients who underwent LCA. Two hundred and twenty-one (88.8%) procedures were performed transperitoneally, and 28 (11.2%) renal masses were approached retroperitoneally.

Patient demographics, clinical, and operative variables by histopathology are listed in Table 2. Across the sample, the median tumor size was 2.47±0.89 cm. The median PF distance as measured on CT was 12 mm (Q_1–Q₃: 8–16 mm). The median WIT for the LPN patients was 25 minutes (Q_1–Q₃: 19–30 min). There were two Clavien grade II complications after LCA: two (1.6%) transfusions because of significant intraoperative bleeding. Both were managed conservatively. There were no other major intraoperative or postoperative complications in the LCA group. In the LPN group, a total of 21 (10.8%) perioperative and postoperative complications were recorded, including 10 Clavien grade II and 11 Clavien grade IIIb complications. Hemorrhage was the most common complication with a total of 10 (5.5%) patients needing transfusion (3 intraoperative and 7 postoperative hemorrhages). Of the seven postoperative hemorrhages, one patient needed embolization to achieve hemostasis while the other six patients were treated conservatively.

Table 2.

Patient Characteristics, Preoperative and Operative Parameters by Histopathology Subgroups

	Histopathology
Variables, units	ccRCC (n=127) ^b	Other ^a (n=123)^b
Age, median (Q₁, Q₃)	57 (48, 68)	62 (54, 69)
Sex, n (%)
Males	85 (66.93)	72 (58.54)
Females	42 (33.07)	51 (41.46)
BMI, median (Q₁, Q₃)	28 (25, 31.7)	28.6 (25.5, 32.9)
Perirenal fat, mm, median (Q₁, Q₃)	13.1 (8.6, 17)	11 (8, 15)
Clinical tumor size, cm, median (Q₁, Q₃)	2.5 (2, 3)	2.2 (1.7, 3)
Tumor location (depth), n (%)
Exophytic	62 (48.82)	66 (53.66)
Endophytic	23 (18.11)	32 (26.02)
Mesophytic	42 (33.07)	25 (20.33)
Operative variables
Type of surgery, n (%)
LPN	102 (80.31)	94 (76.42)
LCA	25 (19.69)	29 (23.58)
OR time, minutes, median (Q₁, Q₃)	130 (101, 174)	120 (100, 160)
Surgical approach, n (%)
Transperitoneal	115 (90.55)	106 (86.89)
Retroperitoneal	12 (9.45)	16 (13.11)
WIT, minutes, median (Q₁, Q₃)	24 (19, 31)	25 (18, 30)
Blood loss, median (Q₁, Q₃)	200 (100, 300)	137.50 (50, 250)
LOS, median (Q₁, Q₃)	2 (1, 2)	2 (1, 2)
Postoperative complications, n (%)
Yes	12 (9.52)	9 (7.32)
No	114 (90.48)	114 (92.68)
Transfusion rate, n (%)
Yes	2 (1.67)	3 (2.54)
No	118 (98.33)	115 (97.46)

Other: Consists of adipose tissue, B-cell Hodgkin lymphoma, cyst, angiomyolypoma, oncocytoma, chromophobe renal-cell carcinoma, papillary renal-cell carcinoma, and nondiagnostic pathology.

Note: Sample sizes vary because of missing data.

Q₁ refers to the 25th percentile and Q₃ refers to the 75th percentile.

ccRCC=clear-cell renal-cell carcinoma; BMI=body mass index; LPN=laparoscopic partial nephrectomy; LCA=laparoscopic cryoablation; OR=operative; WIT=warm ischemia time; LOS=length of stay.

There were two elective conversions to laparoscopic radical nephrectomy for centrally located tumors. There were no conversions to open surgery. In addition, pleural effusion necessitating drainage developed in one patient, two patients had a pneumothorax treated with insertion of a chest tube, and five patients had a urine leak that resolved with drainage after endoscopic placement of an indwelling stent.

The interclass correlation coefficient for PF measurements was 98% (95% confidence interval [CI]=0.97–0.99), which indicated a high degree of agreement between the two surgeons.

There was a significant difference in PF between men and women (13.6 vs 10.1 mm, respectively, P<0.001). There was a significant correlation between BMI and PF (r=0.148, P<0.027). No other significant correlations were found.

The results of a simple logistic regression model with only PF as a predictor revealed that PF was a statistically significant predictor of ccRCC histopathology (P<0.02). For each additional mm increase in PF, the odds of having a ccRCC increased by 1.05 times (95% CI: 1.006–1.097)

In a multivariate logistic regression analysis with PF, age, and tumor location in the model (sex, BMI, and lesion size were not significant), all three variables were statistically significant predictors of ccRCC (Table 3). Younger patients are 1.02 times more likely to have ccRCC than older patients with each yearly decrease in age (P<0.04; 95% CI: 1.04–1.00). Increased PF is significantly predictive of ccRCC (P<0.01). A patient is 1.06 times more likely to have ccRCC with each mm increase in PF (95% CI: 1.02–1.11). Tumor location was also predictive of ccRCC (P<0.04). Specifically, mesophytic tumor location is 2.55 times more likely to be associated with ccRCC than endophytic tumor location (P<0.01; 95% CI: 1.21–5.38), and mesophytic tumor location is 1.9 times more likely to be associated with ccRCC than exophytic tumor location (P<0.04; 95% CI: 1.02–3.54). No other preoperative or operative parameters were found to be significantly predictive of histopathology.

Table 3.

Multiple Logistic Regression Model: Clear-Cell Renal-Cell Carcinoma as a Function of Age, Perirenal Fat, and Tumor Location

Variable	Coefficent (β)	Standard error	Wald χ²	P value	Odds ratio	95% CI
Intercept	0.21	0.71	–	–	–	–
Age	-0.02	0.01	4.22	0.04	0.98	0.96–0.99
Perirenal fat	0.06	0.02	6.89	0.01	1.06	1.02–1.11
Tumor location
Mesophytic vs endophytic	0.94	0.38	6.04	0.01	2.55	1.21–5.38
Exophytic vs endophytic	0.29	0.33	0.78	0.38	1.34	0.7–2.57

CI=confidence interval.

Discussion

Obesity and kidney cancer are two major health concerns. Several case-control and prospective observational studies have shown obesity as a risk factor for RCC. RCC as characterized by the Heidelberg classification,¹⁶ however, is well known to represent a series of different diseases with different biology and different patient outcomes.^17,18 To date, despite our understanding of the significantly different biology of various RCC subtypes, no effort has been made to examine obesity metrics with different RCC subtypes. The separate evaluation of different RCC histopathologic variants is critical, because these represent very different tumors with recognized differences in survival outcomes.^13,14 Because ccRCC is the most common of the subtypes and is known to be a relatively aggressive histopathologic RCC variant, we focused on identifying metrics, which selected for ccRCC in a T_1a RCN cohort.

Most of the studies that evaluated the role of obesity in kidney cancer used BMI as the key metric. Biologic differences across races and inconsistencies in BMIs, however, have suggested the necessity for a more accurate and reliable measurement of obesity. Other measures of central adiposity, such as waist-to-hip ratio and WC, have been shown to be better indicators of all cause mortality than overall measures such as BMI.¹⁹

Because it is well documented that PF is metabolically active^11,12 and the volume of PF is very variable by patient, we elected to evaluate PF as a possible predictor of RCN histopathology and hypothesized that PF may be a more sensitive metric than BMI as a predictor of T_1a RCN histopathology.

In the current study, we demonstrated that increasing PF correlated with increasing BMI. Indeed, increasing PF is an earlier manifestation of general obesity that appears before other accumulations of body fat.²⁰ Thus, the PF can be measured and potentially may be a more accurate predictor in patients with lower BMI. Despite the correlation of PF with ccRCC, however, when evaluating PF and RCC subtypes, such as papillary and chromophobe, PF was not a significant predictor of either subtype. This finding is not surprising, because the molecular mechanisms of the different RCC subtypes are well characterized, and we speculate that the possible autocrine factors related to PF may only influence some oncogenic pathways. Indeed, the relationship between PF and ccRCC histopathology may be particularly useful, because ccRCC has been shown to be associated with poor survival rates compared with most other RCC subtypes.^21,22

Noninvasive metrics such as PF may ultimately be superior to the relatively invasive practice of preoperative biopsy for predicting which RCN will need intervention and may decrease potentially unnecessary procedures for benign RCN. Further evaluation of PF as a predictor of other RCC subtypes with a larger patient population will certainly be needed to substantiate these findings.

In the current study, we observed that tumor location was a significant predictor of tumor histopathology. There are few reports in the literature that assess tumor location as a predictor of histopathology. Mason and colleagues²³ evaluated tumor location as a predictor of tumor histopathology in patients undergoing LPN. They identified that the peripherally located tumors had 3.5 times higher odds of having benign pathology compared with centrally located tumors. In a series by Frank and associates,²⁴ the proportion of benign disease in peripheral and central tumors was 34% and 20%, respectively (P=0.002). Venkatesh and coworkers²⁵ reported that 45%, 14%, 25%, and 14% of exophytic, mesophytic, endophytic, and hilar renal masses were benign, respectively (P<0.05).

Morbidity associated with technical difficulties in minimally invasive surgery prompted surgeons to look for preoperative risk factors to improve patient selection and surgical outcomes. In this study, PF was not a predictor of surgical outcomes during laparoscopic renal surgery. With experience, a greater amount of PF does not pose more challenge during kidney surgery. Previously, in an attempt to predict surgical outcomes of laparoscopic procedures, several studies have evaluated potential risk factors for laparoscopic procedures. Among other anatomic and surgical parameters, visceral obesity has been documented as a risk factor for poor outcomes after laparoscopic surgery. The urologists performing laparoscopic renal procedures via either a transperitoneal or retroperitoneal approaches encounter PF. Given the intimate nature of the Gerota fascia with critical renal structures, surgical management is critical to success; once the surgeon enters the abdominal cavity, the amount of fat around the kidney obscures anatomic landmarks and makes it more difficult to identify and manage the renal vessels and their tributaries.⁹

Nitori and colleagues¹⁰ in their prospective study of patients undergoing laparoscopic surgery for colorectal surgery, reported that visceral obesity was the only independent predictor of surgical complications and they encountered significantly more complications in patients with visceral obesity measured by WC.¹⁰ Ueda and associates²⁶ evaluated the impact of VF accumulation and showed similar results in patients undergoing laparoscopic surgery for gastric cancer. Anderson and coworkers⁹ evaluated the PF along with abdominal fat as a prognostic factor of surgical complexity in patients undergoing laparoscopic donor nephrectomy. The authors measured PF at three sites, including anterior, posterior, and lateral spleno-renal distances. The study demonstrates that an increased amount of PF is correlated with longer OR time and WIT. There was no correlation to blood loss and surgical complications, however. In their study all PF measurements were significantly correlated with BMI.

Our results substantiate these findings and previous reports that show a correlation between BMI and VF.⁸ In our current study, there was no correlation with PF and any surgical outcomes such as EBL, LOS, or surgical approach (transperitoneal vs retroperitoneal). Our data demonstrated that larger tumor size is significantly correlated with increased EBL, WIT, and transfusion rate, which is consistent with previous reports.²⁷ We demonstrated that PF is greater in men than in women. Our findings support the previous report by Eisner and colleagues.²⁸ They evaluated sex distribution in subcutaneous and PF and found that males had significantly greater PF than females. They found weak correlation between BMI and PF, however.

In the current study, we measured the PF distance at one point. Because there are no comparable studies and established points of PF measurement, we chose the perpendicular distance between the kidney's posterior surface and the external margin of iliopsoas at the level of the renal hilum. We chose the posterior surface because the PF capsule that surrounds the proper capsule of each kidney is more developed and consistent on the posterior surface of the kidney than anteriorly.²⁹ We thought that this measurement technique was the most reproducible. In addition, we evaluated reproducibility of this measurement. Two urologists measured PF, and our results demonstrated excellent interobserver reliability with correlation coefficient of 98% (95% CI=0.97–0.99).

Limitations of the current study include the small cohort studied. Future studies will be needed to confirm the relationship between PF as well as the histopathology. Evaluation of PF on a molecular basis will help to further understand the true relationship between VF and renal tumor histopathology.

Conclusion

For T_1a RCN, PF predicts ccRCC histopathology. As such, PF may be helpful in preoperative noninvasive decision-making for cT_1a RCN.

Footnotes

Disclosure Statement

No competing financial interests exist.

Abbreviations Used

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