Background/Objectives: Endometriosis represents substantial direct and indirect healthcare costs impacted by an absence of uniformly accurate, non-invasive diagnostic tools. We endeavored to demonstrate gastrointestinal myoelectrical activity (GIMA) biomarkers, unique to endometriosis, will allow non-invasive, uniformly accurate diagnosis or exclusion of endometriosis. Methods: Prospective open-label comparative study of 154 patients, age ≥ 18, with or without diagnosed endometriosis. Population included 62 non-endometriosis controls (Cohort 1), 43 subjects with surgically/histologically confirmed endometriosis (Cohort 2), and 49 subjects with abdominal pain and negative imaging (Cohort 3). Non-invasive electroviscerography (EVG) recorded GIMA biomarkers from three abdominal electrodes before and 30 min post water load protocol. Cohort 2 had postoperative EVG and Cohort 3 had preoperative EVG. Calculated specificity, sensitivity, negative predictive value (NPV), positive predictive value (PPV), and predictive probability or C-statistic used univariate, multivariate, linear, and logistical regression analyses of the area under the curve (AUC) at all frequency and time points, including age and pain covariants. Results: The non-endometriosis cohort differed significantly from the endometriosis cohorts (p < 0.001) for median (IQR) and AUC percent frequency distribution of power at baseline, 10 min, 20 min, and 30 min post water load at all frequency ranges: 15–20 cpm, 30–40 cpm, and 40–50 cpm. The endometriosis cohorts were statistically similar (p > 0.05). GIMA biomarker threshold scoring demonstrated 95%/91% sensitivity and PPV, 96%/95% specificity and NPV, and a C-statistic of >99%/98%, respectively, for age subsets. GIMA biomarkers in Cohort 3 predicted 47/49 subjects positive and 2/49 negative for endometriosis, confirmed surgically. Hormonal therapy, surgical stage, nor pain score affected diagnostic accuracy. Conclusions: EVG with GIMA biomarker detection distinguished participants with and without endometriosis based upon endometriosis-specific GIMA biomarkers threshold scoring.

Objective: Validate diagnostic accuracy of new unique biomarker, gastrointestinal myoelectrical activity (GIMA), detected by electroviscerography (EVG) with Ai-derived disease threshold score calculation to noninvasively diagnose endometriosis. Design: Multicenter prospective blinded trial Setting: Women’s Healthcare Center Population of Sample: 165 patients with and without endometriosis diagnosis Methods: Initial 50 patients meeting inclusion criteria in 165-patient multicenter prospective GIMA biomarker trial were selected for interim analysis. Study population included women 27-55 years old, 25 with diagnosis of endometriosis and 25 non-endometriosis controls. Clinical and GIMA data were collected between February 2007 and September 2017, at all harvesting time points and frequency bands using EVG. Ai-derived threshold score calculations used area under the curve (AUC), age and standardized pain scores variables. Main Outcome Measures: Specificity, sensitivity, NPV, PPV and predictive probability or C-Statistic from logistical regression analyses of all AUC frequency and time points. Results: Non-endometriosis versus endometriosis cohort interim analysis differed significantly (p<0.001) for median (IQR), AUC values, and percent frequency power distribution at baseline, 10-minute, 20-minute, and 30-minute post water-load at frequency ranges 15-20cpm, 30-40cpm, 40-50cpm and 50-60cpm. GIMA threshold scoring revealed sensitivity and PPV of 96%, specificity and NPV of 96% and C-statistic of 100%. Ai-derived GIMA biomarkers threshold scoring predicted 25/25 subjects positive and negative for endometriosis, with surgical confirmation. Hormonal therapy, surgical stage, age nor pain score affected diagnostic accuracy. Conclusions: EVG GIMA biomarker data with Ai-derived threshold scoring accurately distinguished participants with and without endometriosis. This interim analysis supports continued investigation of GIMA biomarkers to diagnose endometriosis.