Rationale: Despite good sensitivity and negative predictive value, the implementation of sentinel node biopsy (SNB) in robot-assisted radical prostatectomy (RARP) with extended pelvic lymph node dissection (ePLND) for prostate cancer (PCa) is still controversial.Based on this premise, we aimed to define the added value of SNB (with different tracer modalities) to ePLND in the identification of nodal metastases. Complications rates and oncological outcomes were also assessed.Methods: From January 2006 to December 2019, prospectively collected data were retrospectively analyzed from a single institutional database regarding PCa patients all treated with RARP and ePLND with or without additional use of SNB, either with hybrid tracer indocyanine green (ICG)-99m Tc-nanocolloid (ICG-99mTc-nanocolloid) or free ICG.Multivariable logistic and Cox regression models tested the impact of adding SNB (either with hybrid tracer or free-ICG) on lymph nodal invasion detection, complications and oncological outcomes.Results: Overall, 1680 patients were included in the final analysis. 1,168 (69.5%) were in the non SNB-group, 161 (9.6%) in the ICG SNB-group and 351 (20.9%) patients in the Hybrid SNB-group. Hybrid SNB-group (OR 1.61, 95%CI 1.18-2.20, p=0.002) was an independent predictor of nodal involvement, while ICG SNB-group did not reach the independent predictor status when compared to non SNB group (OR 1.35, 95%CI 0.89-2.03, p=0.1). SNB techniques were not associated with higher rates of complications. Lastly, use of Hybrid SNB was associated with lower rates of biochemical recurrence (0.79, 95%CI 0.63-0.98) and of clinical recurrence (HR 0.76, p=0.035) compared to non SNB group. Conclusions:The implementation of hybrid sentinel node biopsy technique with ICG-99m Tc-nanocolloid in prostate cancer improves detection of positive nodes and potentially lowers recurrence rates with subsequent optimization of patient management, without harming patient safety.

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GPS positioning devices are becoming a commodity sensor platform with the emergence and popularity of smartphones. This abundance of GPS trajectories has fueled significant research around map-matching and related applications such as traffic assessment and prediction. Unfortunately, this research has only been used in costly and complex fleet management solutions. Our latest research endeavor addresses this issue by presenting cost-effective solutions for adapting state-of-the-art research around map-matching and live traffic assessment in the context of fleet management applications. This paper showcases various research results wrapped in a single extensible fleet management platform.