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This study aimed to assess the value of dual-timepoint F-FDG PET/CT in the prediction of lymph node (LN) status in patients with invasive vulvar cancer (VC) scheduled for inguinofemoral LN dissection. From April 2013 to July 2015, all consecutive patients with VC scheduled for inguinofemoral LN dissection were prospectively enrolled. All patients underwent a preoperative whole-body F-FDG PET/CT scan at 1 h (standard examination) and an additional scan from T11 to the groins at 3 h (delayed examination) afterF-FDG injection. On both scans, each groin was visually scored 0 or 1 concerning F-FDG LN uptake relative to background. Semiquantitative analysis included SUV and the corresponding retention index of SUV, measured on both scans. The optimal cutoff value of these parameters was defined using a receiver-operating-characteristic analysis. Histopathology was the standard of reference. Thirty-three patients were included, with a total of 57 groins dissected and histologically evaluated. At histopathology, 21 of 57 (37%) groins contained metastatic LNs. Concerning visual score, sensitivity, specificity, negative predictive value, positive predictive value, and accuracy were 95.2%, 75%, 96.4%, 69%, and 82.5% on standard scanning and 95.2%, 77.8%, 96.6%, 71.4%, and 84.2% on delayed scanning, respectively. At receiver-operating-characteristic analysis, sensitivity and specificity were 95.2% and 77.8% on standard and delayedF-FDG PET/CT for an SUV cutoff of greater than 1.32 and 1.88, respectively, and 95.2% and 80% for a retention index of SUV cutoff of greater than 0. StandardF-FDG PET/CT is an effective preoperative imaging method for the prediction of LN status in VC, allowing the prediction of pathologically negative groins and thus the selection of patients suitable for minimally invasive surgery. Delayed F-FDG PET/CT did not improve the specificity and the positive predictive value in our series. Larger studies are needed for a further validation.

Purpose This retrospective study aimed to assess the diagnostic performance of preoperative [18F]FDG-PET/CT in predicting the groin and pelvic lymph node (LN) status in a large single-centre series of vulvar cancer patients. Methods Between January 2013 and October 2018, among all consecutive women with proven vulvar cancer submitted to [18F]FDG-PET/CT, 160 patients were included. LNs were analysed by two qualitative methods assessing PET information (defined as visual assessment) and a combination of PET and low-dose CT information (defined as overall assessment), respectively, as well as semi-quantitative analysis (LN-SUVmax). Sensitivity, specificity, accuracy, positive and negative predictive values (PPV and NPV) in predicting the groin and pelvic LN status were calculated in the overall study population; a subset analysis of groin parameters in clinically/ultrasonography negative patients was also performed. Histopathology was the reference standard. Results All patients underwent vulvar and inguinofemoral LN surgery, and 35 pelvic LN surgery. Overall, 338 LN sites (296 groins and 42 pelvic sites) were histologically examined with 30.4% prevalence of metastatic groins and 28.6% for metastatic pelvic sites. In the overall study population, sensitivity (95% confidence interval, CI), specificity (95% CI), accuracy (95% CI), PPV (95% CI) and NPV (95% CI) at the groin level were 85.6% (78.3–92.8), 65.5% (59.0–72.0), 71.6% (66.5–76.8), 52.0% (44.0–60.1) and 91.2% (86.7–95.8) for visual assessment; 78.9% (70.5–87.3), 78.2% (72.5–83.8), 78.4% (73.7–83.1), 61.2% (52.3–70.1) and 89.4% (85.0–93.9) for overall assessment; and 73.3% (64.2–82.5), 85.0% (80.1–89.8), 81.4% (77.0–85.8), 68.0% (58.8–77.3) and 87.9% (83.4–92.5) for semi-quantitative analysis (SUVmax cut-off value 1.89 achieved by ROC analysis). Similar results were observed in the pelvis-based analysis. Conclusion In this large single-centre series of vulvar cancer patients, [18F]FDG-PET/CT showed good values of sensitivity and NPV in discriminating metastatic from non-metastatic LNs. In routine clinical practice, qualitative analysis is a reliable interpretative criterion making unnecessary commonly used semi-quantitative methods such as SUVmax.

This study investigates whether radiomic features derived from preoperative positron emission tomography (PET) images could predict both tumor biology and prognosis in women with invasive squamous cell carcinoma of the vulva. Patients were retrospectively included when they had a unifocal primary cancer of ≥ 2.6 cm in diameter, had received a preoperativeF-fluorodeoxyglucose (F-FDG) PET/computed tomography (CT) scan followed by surgery and had at least six months of follow-up data. F-FDG-PET images were analyzed by semi-automatically drawing on the primary tumor in each PET image, followed by the extraction of 83 radiomic features. Unique radiomic features were identified by principal component analysis (PCA), after which they were compared with histopathology using non-pairwise group comparison and linear regression. Univariate and multivariate Cox regression analyses were used to correlate the identified features with progression-free survival (PFS) and overall survival (OS). Survival curves were estimated using the Kaplan-Meier method. Forty women were included. PCA revealed four unique radiomic features, which were not associated with histopathologic characteristics such as grading, depth of invasion, lymph-vascular space invasion and metastatic lymph nodes. No statistically significant correlation was found between the identified features and PFS. However, Moran's I, a feature that identifies global spatial autocorrelation, was correlated with OS ( = 0.03). Multivariate Cox regression analysis showed that extracapsular invasion of the metastatic lymph nodes and Moran's I were independent prognostic factors for PFS and OS. Our data show that PCA is usable to identify specific radiomic features. Although the identified features did not correlate strongly with tumor biology, Moran's I was found to predict patient prognosis. Larger studies are required to establish the clinical relevance of the observed findings.