Deep Neural Network Stratification for Use Detecting Endometriosis in Women Affected by Chronic Pelvic Pain (EndoCheck)

Deep Neural Network Stratification for the Use in Detecting Endometriosis in Women Affected by Chronic Pelvic Pain (EndoCheck)

The goal of this observational study is to determine the clinical validity of a deep neural network algorithm that utilizes protein biomarker detection of Endometriosis - "EndoCheck" - as an "aid in diagnosis" for endometriosis and to show validity as a diagnostic test

The objective is to confirm the clinical performance (sensitivity and specificity) of EndoCheck when compared to laparoscopic surgical assessment as an "aid in diagnosis" for endometriosis in subjects who present with chronic pelvic pain.

The primary endpoint of the study is to optimize the test to achieve the success criteria of at least 94% and 79% sensitivity and specificity, respectively. Secondary endpoints include examining the performance of the test in patients stratified by pain severity and other clinical factors.

Inclusion Criteria:

• Participant is willing and able to provide written informed consent.
• Participant is a female aged 14 to 50 years old at time of consent.
• Participant is scheduled to undergo laparotomy or laparoscopy for symptomology consistent with possible endometriosis

Exclusion Criteria:

• Participant is a female in a pre-menarchal state.
• Participant is pregnant.
• Participant has an active malignancy.
• Participant is known to have tested positive for human immunodeficiency virus or hepatitis A, B, or C.
• Participant has an active pelvic infection or other infections contraindicated for surgery.
• Participant has participated (±3 months of study enrollment) in a clinical trial where an investigational drug/ device/ procedure was or is planned to be administered.
• Participant has any general health or behavioral condition that, in the opinion of the investigator, should exclude the participant from participation.
• Participant is under 14 years old or over 50 years old