Magnetic Marking and Intraoperative Detection of Primary Draining Lymph Nodes in High-Risk Prostate Cancer Using Superparamagnetic Iron Oxide Nanoparticles: Additional Diagnostic Value.

Sentinel lymph node dissection (sLND) using a magnetometer and superparamagnetic iron oxide nanoparticles (SPIONs) as a tracer was successfully applied in prostate cancer (PCa). Radioisotope-guided sLND combined with extended pelvic LND (ePLND) achieved better node removal, increasing the number of affected nodes or the detection of sentinel lymph nodes outside the established ePLND template. We determined the diagnostic value of additional magnetometer-guided sLND after intraprostatic SPION-injection in high-risk PCa. This retrospective study included 104 high-risk PCa patients (PSA >20 ng/mL and/or Gleason score ≥ 8 and/or cT2c) from a prospective cohort who underwent radical prostatectomy with magnetometer-guided sLND and ePLND. The diagnostic accuracy of sLND was assessed using ePLND as a reference standard. Lymph node metastases were found in 61 of 104 patients (58.7%). sLND had a 100% diagnostic rate, 96.6% sensitivity, 95.6% specificity, 96.6% positive predictive value, 95.6% negative predictive value, 3.4% false negative rate, and 4.4% false positive rate (detecting lymph node metastases outside the ePLND template). These findings demonstrate the high sensitivity and additional diagnostic value of magnetometer-guided sLND, exceeding that of ePLND through the individualized extension of PLND or the detection of sentinel lymph nodes/lymph node metastases outside the established node template in high-risk PCa.

Evaluation of Fast Molecular Detection of Lymph Node Metastases in Prostate Cancer Patients Using One-Step Nucleic Acid Amplification (OSNA).

Background: In clinical routine, only fractions of lymph nodes (LNs) are examined histopathologically, often resulting in missed (micro-)metastases and incorrect staging of prostate cancer (PCa). One-step nucleic acid amplification (OSNA) analyzes the entire LN by detecting cytokeratin 19 (CK19) mRNA as a surrogate for LN metastases requiring less effort than conventional biomolecular techniques. We aimed to evaluate performance of OSNA in detecting sentinel LN (SLN) metastases in PCa. Methods: SLNs (n = 534) of 64 intermediate- or high-risk PCa patients undergoing radical prostatectomy with extended and sentinel-guided lymphadenectomy were cut into slices and alternatingly assigned to OSNA and histopathology (hematoxylin-eosin staining, CK19, and CK AE1/AE3 immunohistochemistry). Sensitivity and specificity of OSNA and concordance and measure of agreement (Cohen's kappa (κ)) between OSNA and histopathology were assessed. Results: Histopathology revealed metastases in 76 SLNs. Sensitivity and specificity of OSNA were 84.2% and 96.1%, respectively. Discordant results were recorded for 30 of 534 SLNs, revealing high concordance (94.4%). Twenty-four discordant cases were classified as micrometastases, indicating a possible allocation bias. In 18 cases, positive results were conferred only by OSNA resulting in seven LN-positive patients who were missed by histopathology. Overall, the level of agreement was high (κ = 0.78). Conclusions: OSNA provided a diagnosis that was as least as accurate as detailed histological examination and might improve LN staging in PCa.

Updated Nomogram Incorporating Percentage of Positive Cores to Predict Probability of Lymph Node Invasion in Prostate Cancer Patients Undergoing Sentinel Lymph Node Dissection.

Objectives: To update the first sentinel nomogram predicting the presence of lymph node invasion (LNI) in prostate cancer patients undergoing sentinel lymph node dissection (sPLND), taking into account the percentage of positive cores. Patients and Methods: Analysis included 1,870 prostate cancer patients who underwent radioisotope-guided sPLND and retropubic radical prostatectomy. Prostate-specific antigen (PSA), clinical T category, primary and secondary biopsy Gleason grade, and percentage of positive cores were included in univariate and multivariate logistic regression models predicting LNI, and constituted the basis for the regression coefficient-based nomogram. Bootstrapping was applied to generate 95% confidence intervals for predicted probabilities. The area under the receiver operator characteristic curve (AUC) was obtained to quantify accuracy. Results: Median PSA was 7.68 ng/ml (interquartile range (IQR) 5.5-12.3). The number of lymph nodes removed was 10 (IQR 7-13). Overall, 352 patients (18.8%) had LNI. All preoperative prostate cancer characteristics differed significantly between LNI-positive and LNI-negative patients (P<0.001). In univariate accuracy analyses, the proportion of positive cores was the foremost predictor of LNI (AUC, 77%) followed by PSA (71.1%), clinical T category (69.9%), and primary and secondary Gleason grade (66.6% and 61.3%, respectively). For multivariate logistic regression models, all parameters were independent predictors of LNI (P<0.001). The nomogram exhibited a high predictive accuracy (AUC, 83.5%). Conclusion: The first update of the only available sentinel nomogram predicting LNI in prostate cancer patients demonstrates even better predictive accuracy and improved calibration. As an additional factor, the percentage of positive cores represents the leading predictor of LNI. This updated sentinel model should be externally validated and compared with results of extended PLND-based nomograms.