Laparoscopic sentinel lymph node mapping with indocyanine green in endometrial cancer: surgeon's learning curve (cumulative sum analysis).

OBJECTIVES: To evaluate surgeons' learning curves for laparoscopic sentinel lymph node biopsy in endometrial cancer. METHODS: A prospective observational study was performed at the Oncogynecology Center, Lithuanian University of Health Sciences Hospital, from March 2018 to October 2022. Participating surgeons had no previous experience of laparoscopic sentinel lymph node biopsy with indocyanine green tracer. Cumulative sum analysis was used to create learning curves for the performance of eight surgeons, based on a specific result over a time period. Two different cumulative sum plots were made for each surgeon: successful bilateral sentinel lymph node mapping and removal of sentinel lymph node specimens containing actual lymphatic tissue. RESULTS: 190 patients were included. The overall rate of sentinel lymph node mapping was 89.5%: successful bilateral mapping was achieved in 134 (70.5%) patients, while in 36 (19%) patients sentinel lymph nodes were mapped unilaterally. The bilateral detection rate significantly improved in later study periods (from 59.3% in the first year to 85.0% in the last year; p=0.03). Analysis of the performance of the surgeons for bilateral sentinel lymph node mapping showed that the cumulative sum plot crossed the H0 limit line after 13 consecutive successful bilateral sentinel lymph node biopsies, indicating an acceptable level of competence to achieve the bilateral detection rate of at least 75%. This was accomplished by only one surgeon after 30 surgeries. Analysis of the performance of the surgeons for identification and removal of specimens containing histologically confirmed lymphatic tissue showed that the cumulative sum plots crossed the H0 limit line after six consecutive successful sentinel lymph node removals. This was accomplished by most of the surgeons (5 of 8). CONCLUSION: At least 30 procedures of indocyanine green traced laparoscopic sentinel lymph node biopsy were needed to reach an acceptable level of competence for a bilateral sentinel lymph node detection rate of at least 75%. TRIAL REGISTRATION NUMBER: ACTRN12619000979156.

The Feasibility of Sentinel Lymph-Node, Mapped with Indocyanine Green, Biopsy in Endometrial Cancer Patients: A Prospective Study.

Background and objectives. Systematic pelvic lymphadenectomy (LND) is an essential part of lymph-node status evaluation in endometrial cancer (EC) patients to tailor the adjuvant treatment. However, it is associated with the post-operative lymphatic complications and does not improve the outcomes of the disease. Indocyanine green (ICG) mapped sentinel lymph-node biopsy (SLB) has recently been introduced into the clinical practice as an alternative for the surgical lymph-node evaluation in EC patients with the potential to decrease LND related complications. The aim of our study was to evaluate the feasibility of ICG mapped SLB in low, intermediate, and high-risk EC patients in a center with no previous experience on endoscopic SLB procedure. Materials and Methods: The prospective study was performed. 170 patients with histologically confirmed EC were included. Sentinel lymph-nodes (SLs) were mapped with ICG dye and removed ahead of the total laparoscopic hysterectomy. Low-risk patients received only SLB, while SLB and LND were performed for intermediate and high-risk patients. Results: The overall detection rate of SLs was 88.8%. Bilateral mapping was achieved in 68.2% of the patients. The overall detection rate for low-risk patients was 93.7%, 85.0% for the intermediate-risk group, and 100% for high-risk patients (p = 0.232). The most common anatomical sites of SLs were the external iliac (45.8% on the right and 46.6% on the left) and obturator regions (20.9% and 25.6%, respectively). Positive lymph-nodes were found in 8 (4.7%) patients. The sensitivity of SLB was 75.0% and negative predictive value (NPV)-97.2%. Conclusions: Even in the center with no previous experience, sentinel lymph-node biopsy using ICG mapping is feasible. However, the favorable outcomes might be associated with the learning process of newly established method.

Performance of the IOTA ADNEX Model on Selected Group of Patients with Borderline Ovarian Tumours.

Background and objectives: ultrasound is considered to be the primary tool for preoperative assessment of ovarian masses; however, the discrimination of borderline ovarian tumours (BOTs) is challenging, and depends highly on the experience of the sonographer. The Assessment of Different NEoplasias in the adneXa (ADNEX) model is considered to be a valuable diagnostic tool for preoperative assessment of ovarian masses; however, its performance for BOTs has not been widely studied, due to the low prevalence of these tumours. The aim of this study was to evaluate the performance of ADNEX model for preoperative diagnosis of BOTs. Methods: retrospective analysis of preoperative ultrasound datasets of patients diagnosed with BOTs on the final histology after performed surgery was done at a tertiary oncogynaecology centre during the period of 2012-2018. Results: 85 patients were included in the study. The performance of ADNEX model based on absolute risk (AR) improved with the selection of a more inclusive cut-off value, varying from 47 (60.3%) correctly classified cases of BOTs, with the selected cut-off of 20%, up to 67 (85.9%) correctly classified cases of BOTs with the cut-off value of 3%. When relative risk (RR) was used to classify the tumours, 59 (75.6%) cases were identified correctly. Forty (70.2%) cases of serous and 16 (72.7%) cases of mucinous BOTs were identified when AR with a 10% cut-off value was applied, compared to 44 (77.2%) and 15 (68.2%) cases of serous and mucinous BOTs, correctly classified by RR. The addition of Ca125 improved the performance of ADNEX model for all BOTs in general, and for different subtypes of BOTs. However, the differences were insignificant. Conclusions: The International Ovarian Tumour Analysis (IOTA) ADNEX model performs well in discriminating BOTs from other ovarian tumours irrespective of the subtype. The calculation based on RR or AR with the cut-off value of at least 10% should be used when evaluating for BOTs.