62 Gynecologic surgeon agreement and accuracy in describing endometriotic lesions

Objectives/Goals: Endometriotic lesions visualized during diagnostic laparoscopy are heterogenous in their appearance. Our research aims to 1) assess the interobserver variability of surgeons in their description of endometriotic lesions and 2) assess their accuracy for prediction of invasion into underlying tissues. Methods/Study Population: We will recruit at least 3 gynecologic surgeons to review a dataset of a planned minimum of 120 coded abdominopelvic endometriotic lesions that were biopsied during diagnostic laparoscopy and that are linked to pathology results. Surgeons will independently classify each lesion by visual appearance according to standard and established criteria and predict the presence of deep tissue invasion for each lesion using a binary yes/no classification system with pathology as the reference standard. We will analyze interobserver variability using Cohen’s k statistic. For the accuracy of the prediction of lesion invasion, we will use sensitivity, specificity, and +/- predictive values and +/- likelihood ratios. Results/Anticipated Results: We expect that our results for aim 1 will be consistent with prior studies that demonstrate variability in the description of the visual appearance of endometriotic lesions by gynecologic surgeons. We also expect that for aim 2, there will be a discrepancy between surgeon predicted lesion depth invasion and findings on pathologic analysis, highlighting the limitations of visual inspection and interpretation of endometriotic lesion behavior. Discussion/Significance of Impact: Improving our understanding as to the visual perception of endometriotic lesions will allow for a better understanding of the variability of lesion types and will inform ongoing studies for the development of a machine learning system for the detection and classification of endometriosis.