Evaluation of Endometriosis With 18F-fluorofuranylnorprogesterone PET / MRI

The sensitivity of FFNP PET /MR is defined as the ability of readers (radiologists) to correctly detect endometriosis in patients who have endometriosis.

The specificity is similarly defined as the ability of readers to exclude endometriosis in patients who do not have it.

Diagnostic accuracy will be defined by the histologic presence of endometriosis at laparotomy or laparoscopy and/or by symptomatic improvement as defined surgically by the referring physician within 3 months of surgery (surgeon will make final determination).

Diagnostic accuracy will be defined by the histologic presence of endometriosis at laparotomy or laparoscopy and/or by symptomatic improvement as defined surgically by the referring physician within 3 months of surgery (surgeon will make final determination). EHP-30 score is this is the arithmetic mean of 30 questions, each rated 0-100, about function and pain with endometriosis, where 0 indicates the best health status through to 100 worst health status. Scale scores for each scale are calculated from the total of the raw scores of each item in the scale divided by the maximum possible raw score of all the items in the scale, multiplied by 100. The investigators will implement a random effects linear regression model, modeling SUV-max as a function of EHP-30, while controlling for patient-level covariates (BMI, race, age). The investigators will include physician as a random effect to account for physician-level correlation.

Diagnostic accuracy will be defined by the histologic presence of endometriosis at laparotomy or laparoscopy and/or by symptomatic improvement as defined surgically by the referring physician within 3 months of surgery (surgeon will make final determination). The pain intensity is assessed using a visual analogue scale (VAS), which is a horizontal line 100 mm in length. Subjects mark the VAS with a single vertical line to indicate their current pain level, with 0 mm representing "No Pain" and 100 mm representing "Worst Possible Pain". The investigators will implement a random effects linear regression model, modeling SUV-max as a function of the pain rating, while controlling for patient-level covariates (BMI, race, age). The investigators will include physician as a random effect to account for physician-level correlation.