MAP score and 2D Shear Wave ultrasound as adherent perinephric fat (APF) preoperative predictors in robot-assisted partial nephrectomy
MAP score and 2D Shear Wave ultrasound as adherent perinephric fat (APF) preoperative predictors in robot-assisted partial nephrectomy
Enrica Nicosia, Giulia Francese, Andrea Cazzato, Federica Martini, Matilde Mattiauda, Francesca Ambrosini, Francesco Chierigo, Jeries Paolo Zawaideh, Veronica Giasotto
Adherent perinephric fat (APF) contributes to surgical complexity and can be associated with adverse perioperative outcomes after robot-assisted partial nephrectomy (RAPN). The Mayo Adhesive Probability (MAP) score, based on CT images, is used to predict the presence of APF preoperatively. Our study validates this nephrometry scoring and it proposes an alternative method based on ultrasound evaluation with 2D Shear Wave Elastography (SWE).
For our study, 100 patients were prospectively enrolled between January 2021 and March 2023 in a single institution. Patient’s characteristics (age, sex, BMI), tumor features (RENAL, PADUA, MAP score) and operative factors (intraoperative APF evaluation and the operative time) were recorded. Perirenal fat was preoperatively evaluated with MAP score and 2D shear wave elastography for each patient. The MAP score was calculated on preoperative CT imaging according to the model proposed by Davidliuk et coll. with posterior renal fat thickness measure (variable 1) and severity grading of perinephric stranding (variable 2) (Table 1). Posterior perinephric fat thickness was measured at the level of the renal vein as a direct line from the renal capsule to the posterior abdominal wall in centimetres (2.0 cm =2 points). Perinephric stranding was identified as soft tissue attenuation in fat surrounding the kidney and graded according to severity if present (0= no stranding, 2= thin mild stranding, 3= diffuse stranding). The two scores were combined to give a MAP score of 0-5. (Figure 1) Ultrasound examination with measurement of perirenal adipose tissue elasticity by 2D shear wave elastography (SWE) was performed with the SWE module on GE Logiq S8 ultrasound scanner using GE convex C1-5D probe. The patient was placed on the supine couch and then rotated on the side contralateral to the kidney to be explored; then three samplings of the perirenal adipose tissue were performed using the ROI of the SWE module with annotation of the corresponding measurements in kPa. Subsequently, the mean of the three values obtained was performed. (Figure 2) Only 88 of 100 patients undergoing to RAPN. The model’s predictive ability of APF was evaluated using the concordance index (C-index) for univariable and multivariable logistic regressions. Linear regression models investigated the association between APF and operative time (OT).
Table 1. MAP score calculated on preoperative TC imaging according to the Davidliuk et coll. model with posterior renal fat thickness measure (variable 1) and severity grading of perinephric stranding (variable 2); the combination of two variables gives the MAP score with grading 0-5.
Figure 1. MAP score: variable 1= measure of posterior perinephric fat thickness in cm at the level of renal vein, divided in grade 0 (<1 cm), grade 1 (1-1.9 cm), grade 2 (≥ 2 cm); variable 2= measure perinephric fat stranding, divided in grade 0 if no stranding, grade 2, thin mild stranding and grade 3 with diffuse stranding.
Figure 2. 2D Shear Wave Elastography (SWE) perinephric fat measured by three samplings in kPa.
Overall, 88 consecutive patients were collected of whom 57 (65%) did not have APF and 31 (35%) had APF. No statistically significant differences were reported with regards to age, smoking habit, diabetes, cT stage, PADUA score, and RENAL score (all p > 0.05). In univariable logistic regression models, the SWE (odd ratio (OR):1.4, 95% confidence interval (CI) = 1.16-1.74; p = 0.001), male gender (OR: 6.94, 95%CI 2.16-31.2; p = 0.003) and BMI (OR 1.19, CI 1.07-1.34; p=0.002) achieved the predictor status for APF (Table.2). Both methods had a comparable predictive ability of APF with a C-index of 0.78 for MAP score and 0.75 for SWE, respectively (Figure 3). According to linear regression analysis, the presence of APF is associated with higher total OT (R squared=0.03, p=0.03) with an average of 158 without APF vs 195 min with APF (Figure 4). The most effective model in predicting APF included MAP score, SWE, gender and BMI.
Table 2. Univariable and multivariable logistic regression models to test whether APF was associated with higher values of SWE, gender and BMI.
Figure 3. Models’ predictive ability for the presence of APF by Concordance index (C-index).
Figure 4. Linear regression analysis showed that the presence of APF is associated with higher total OT (R squared = 0,097, p = 0,012).
The presence of APF contributes to longer operative times during robot-assisted partial nephrectomies. Therefore, an adequate evaluation of APF can be useful in addition to multivariable factors (sex, age, BMI) if correctly measured with MAP score or alternatively with 2-D SWE ultrasound.
Figure 5. Intraoperative image of surgical preparation in a patient without adherent perinephric fat (APF).
Figure 6. Intraoperative image of surgical preparation in a patient with adherent perinephric fat (APF).
