Background/Objectives: Sentinel lymph node biopsy (SLNB) is a minimally invasive technique used to assess lymphatic involvement in endometrial cancer (EC), offering reduced surgical morbidity compared to routine lymphadenectomy. Despite its widespread use, the optimal combination of tracers for SLN detection remains a subject of debate. Methods: This retrospective cohort study included 119 patients with early-stage EC treated at the Maria Skłodowska-Curie National Research Institute of Oncology between 2016 and 2021. SLNB was performed using technetium-99m (Tc99m), indocyanine green (ICG), Patent Blue, or combinations of these tracers. Detection rates for unilateral and bilateral SLNs and the accuracy of metastasis identification were analyzed. Results: The overall SLN detection rate was 97.5%. Individual tracer detection rates were 100% for ICG, 100% for Patent Blue, and 96% for Tc99m. Combined tracers achieved detection rates of 96.9% (Tc99m and ICG) and 97.3% (Tc99m and Patent Blue). Bilateral detection was highest with Tc99m and ICG (90.6%) and Patent Blue alone (91%). Metastases were identified in 12% of cases, with combined methods improving metastatic detection. Tc99m yielded no “empty nodes”, compared to 1.7% with Patent Blue and 0.8% with ICG. Conclusions: While combining Tc99m with dyes did not significantly improve overall SLN detection rates, it enhanced metastatic identification and reduced false-negative results. These findings suggest that combined tracer methods optimize SLNB accuracy in endometrial cancer. Prospective studies are needed to confirm these results.

Rationale: The ProMisE molecular classification improves risk assessment in endometrial cancer (EC), but 3–11% of cases exhibit overlapping molecular features, complicating clinical decisions. We analyzed the prevalence and clinicopathological profiles of multiple-classifier ECs in a large Polish cohort. Methods: In this retrospective study (2022–2025), 1075 ECs from four institutions were classified by MMR and p53 immunohistochemistry and POLE exon sequencing. Tumors showing ≥2 molecular features (e.g., MMRd–p53abn, POLEmut–p53abn) were categorized as multiple-classifier ECs. Results: Multiple-classifier ECs comprised 6.9% (74/1075), with MMRd–p53abn (3.9%) being most common. These tumors exhibited more aggressive features vs. MMRd-only: G3 (28.57% vs. 11.79%, p = 0.002), non-endometrioid histology (11.9% vs. 2.85%, p = 0.018), and high–intermediate/high-risk (HIR/HR) groups (59.52% vs. 37.80%, p = 0.001). POLEmut–p53abn (N = 4) and POLEmut–MMRd–p53abn (N = 10) tumors showed advanced stages (75% and 40% FIGO III–IV, respectively), in contrast to classical POLEmut tumors (6.7% FIGO III–IV), and higher rates of nodal metastases. Conclusions: Co-occurrence of molecular classifiers, including triple-classifier tumors, correlates with more adverse profiles and may undermine current stratification paradigms. This study emphasizes the need to further investigate and refine molecular risk models to account for overlapping profiles.

Background: Endometrial cancer (EC) incidence and mortality have been steadily rising globally over recent decades. The introduction of advanced molecular technologies, such as next-generation sequencing (NGS) alongside the FIGO 2023 classification, presents opportunities for refined diagnostics and risk stratification. This study aimed to analyze differences in EC classification among oncology centers in southeastern Poland. Methods: Data were collected from 461 consecutive patients newly diagnosed with EC between 2022 and 2024 at four major oncology centers in southeastern Poland. Molecular and immunohistochemical (IHC) analyses were conducted on formalin-fixed paraffin-embedded (FFPE) tissues to identify key markers, including POLE mutations, MSI-H, and p53 status. Results: The application of the FIGO 2023 staging system revealed statistically significant inter-center differences, with Centers 1 and 4 diagnosing a higher proportion of early-stage cases. The most prevalent subtype was NSMP, observed in 51% of cases. MSI-H occurred in 13–36% of patients, depending on the center. p53 mutations ranged from 9% to 26%. POLE mutations were identified in 4% of patients overall. Significant variations in the molecular subtype distribution across centers highlight potential differences in diagnostic access or tumor biology. Conclusions: The findings demonstrate regional differences in EC staging and molecular profiles in Poland, potentially reflecting disparities in diagnostic resources, methodologies, or tumor characteristics. Addressing these variations through standardized diagnostic protocols and equitable access to molecular tools is critical for optimizing patient outcomes. Future research should focus on evaluating the impact of molecular markers on therapy response and prognosis to guide personalized treatment strategies.

Sentinel lymph node (SLN) identification plays a crucial role in the diagnosis and management of gynecological cancers, particularly in the context of lymph node metastases that often remain undetectable through standard imaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Therefore, surgical assessment of lymph nodes remains an essential component of diagnostic procedures. SLN biopsy enables the detection of small metastatic deposits while reducing the need for extensive lymphadenectomy and minimizing associated complications. Lymphoscintigraphy using technetium-99m (Tc-99m) is one of the most commonly applied techniques for lymphatic mapping and is considered the standard method for SLN identification. In clinical practice, Tc-99m is frequently combined with indocyanine green (ICG) or methylene blue (MB) to allow dual visualization. The dye method, despite its simplicity, has certain limitations, such as shorter retention time in lymph nodes and the risk of diffusion into capillaries, which may reduce detection efficiency. Lymphoscintigraphy with Tc-99m provides precise visualization of lymphatic drainage pathways and SLNs, contributing to a more accurate determination of cancer staging and reducing the number of unnecessary lymphadenectomies. The appropriate application of this technique lowers the risk of complications, such as lymphedema, while maintaining high diagnostic accuracy. This review summarizes current evidence on the clinical application of Tc-99m in SLN detection for gynecological cancers, analyzing both its advantages and the challenges related to its practical implementation. Additionally, it discusses the technical aspects of Tc-99m use and its role as a reliable tool for optimizing oncological outcomes. Keywords: technetium-99m sentinel lymph node gynecological cancer

Background/Objectives: The preoperative detection of sentinel lymph nodes (SLN) using technetium-99m (Tc-99m) is crucial for surgical staging in early-stage endometrial cancer (EC). The optimal imaging timing and modality remain debated. This study compares early planar scintigraphy (30 min), SPECT/CT (1 h), and 18-h planar scintigraphy after a single Tc-99m injection. Methods: A total of 125 patients with early-stage EC underwent SLN mapping with Tc-99m (120 MBq). Imaging included 30-min planar scintigraphy, SPECT/CT (1 h), and 18-h planar scintigraphy on the day of surgery. Detection sensitivity, the bilateral mapping rate, and image quality (signal-to-noise ratio (SNR), contrast factor (C-factor)) were evaluated, with intraoperative gamma probe detection and histopathology as references. Results: The 18-h planar scintigraphy achieved the highest SLN detection sensitivity (94.4%, 118/125), compared with SPECT/CT (87.2%, OR = 2.48, 95% CI: 0.98–6.27, p = 0.051) and 30-min scintigraphy (72.0%). Only the 18-h protocol underwent intraoperative and histopathological verification; results for 30-min planar and 1-h SPECT/CT were based on imaging alone, which limits direct comparability. Bilateral detection was higher at 18 h (80.80%) than SPECT/CT (73.60%). All SLNs detected at 18 h were confirmed intraoperatively and histologically, yielding 100% PPV (95% CI: 96.9–100.0%) and NPV (95% CI: 59.0–100.0%). The 18-h protocol showed superior imaging contrast (C-factor: 10.30 ± 1.22) despite lower residual activity. The method remained effective in patients with BMI ≥ 30 (94.00%). Only 1.60% of patients required hysterectomy before mapping due to background interference. Conclusions: The 18-h planar scintigraphy is a highly effective, low-cost, and accessible method for SLN detection in early-stage EC, potentially reducing the need for SPECT/CT, radiation exposure, and costs.

Objective: Scintigraphy with technetium-99m (Tc-99m) is essential for sentinel lymph node (SLN) detection in gynecological cancers, aiding preoperative planning and reducing unnecessary lymphadenectomy. However, traditional image interpretation is subjective. This study applies numerical tools: signal-to-noise ratio (SNR) and C factor (SLN SNR/ background SNR) to objectively assess scintigraphic image quality and protocol efficacy. Materials and methods: A total of 172 patients with endometrial cancer underwent SLN detection at the Maria Sklodowska-Curie National Research Institute of Oncology, Kraków branch (from 2016–2024). Two protocols were compared: 1. short protocol: 40 MBq Tc-99m, planar imaging – 30 minutes post-injection; 2. long protocol: 120 MBq Tc-99m, planar imaging – 18 hours post-injection. SLN detection was confirmed intraoperatively using a gamma probe and subsequently verified by histopathology. Results: The long protocol achieved a detection sensitivity of 94%, compared to 70% in the short protocol. Based on the analysis, the minimum SNR required for effective SLN detection was 1.46, and the threshold C factor was ≥ 3.61. Although the mean SNR in the long protocol was lower (3.51), the prolonged biological retention of Tc-99m in SLNs contributed to improved detection accuracy. Conclusions: Numerical analysis of SLN scintigraphy in 172 patients provides an objective framework for evaluating image quality and improves detection accuracy. The long protocol offers superior visualization of sentinel lymph nodes. Standardized quantitative imaging may support the development of automated and AI-assisted diagnostic tools in nuclear medicine.