G. Condous

Objectives: This preliminary analysis of an ongoing prospective cohort study aims to validate novel threshold-based and decision-tree (DT) based ultrasound (US) and surgical endometriosis staging systems developed on a retrospective cohort …

Objectives: To describe patients sonographically diagnosed with Urinary System deep endometriosis (DIE) during years 2021-2022 in our medical center.Methods: Data was derived from medical file and telephone communication with the patients.R…

Results: We had included 54 videos from 51 patients with 188 labeled frames.Of these, 171/188 frames contained an annotated DE lesion, and 17/188 were without lesion.On lesion-present frames, Dice was 0.45 ± 0.28 (mean ± SD) with a median o…

Background Rapid advances in transvaginal ultrasound techniques to detect endometriosis (eTVUS) require navigation of a steep learning curve. Artificial intelligence (AI) is playing an ever-increasing role in ultrasound and holds potential …

OBJECTIVE: To determine the diagnostic performance of each additional step of the four-step International Deep Endometriosis Analysis (IDEA) consensus protocol for predicting the presence of deep endometriosis (DE) on transvaginal ultrasoun…

Objectives: The location of a Cesarean incision influences future placentation and the risk of placenta accreta spectrum (PAS).We evaluated whether bladder flap dissection at the time of a primary Cesarean section (CS) affects the position …

Artificial intelligence (AI) is revolutionizing how we practice medicine. In areas where we have traditionally struggled, such as diagnosing endometriosis, AI has significant potential to improve the breadth and accuracy of diagnostic servi…

Endometriosis is a widespread gynecological disorder causing severe pain and infertility, with diagnosis currently relying on slow, costly, and risky laparoscopy. This highlights the critical need for non-invasive imaging diagnostics using …

Traditionally, laparoscopy was considered to be the gold standard for the examination of endometriotic lesions, because it allows their direct visualization. Several international and national guidelines have now shifted their focus to non-…

OBJECTIVES: The development of valuable artificial intelligence (AI) tools to assist with ultrasound diagnosis depends on algorithms developed using high-quality data. This study aimed to test the intra- and interobserver agreement of a pro…

BACKGROUND: Cardiovascular disease is the leading cause of death globally. Non-malignant gynaecological diseases (NMGD) significantly affect patient health and well-being and may be associated with cardiovascular or cerebrovascular disease …

Endometriosis is a chronic condition where tissue resembling the uterine lining grows elsewhere in the pelvis, often causing pain, infertility, and inflammation. For decades, textbooks and research papers have described the rectovaginal sep…

OBJECTIVE: To evaluate the performance of transvaginal ultrasound (TVS) using the International Deep Endometriosis Analysis (IDEA) terminology in the detection of deep endometriosis (DE). DESIGN: International multicenter prospective diagn…

Abstract Diagnosis of endometriosis has traditionally relied on laparoscopic surgery, which was considered the ‘gold standard’ diagnostic tool. This is not ideal as surgery carries risk, is expensive, is difficult to access, and disrupts pa…

Objective To identify a diagnostic microbial signature for endometriosis. Design Prospective cohort study Setting Nepean Hospital and UNSW Microbiome Research Centre, St George Hospital, Australia Population 64 age- and sex-matched subjects…

In March 2022 Australian Medicare Benefits Schedule updated gynecological item numbers relating to endometriosis surgery. Specific item numbers include 35637, 35631 and 35632 (a division of 35638) and 35641 (14). Each item number correlates…

With the ESHRE 2022 endometriosis guideline outlining the ‘gold standard’ for endometriosis diagnosis is now imaging, the prior mantra of “see and treat” at time of laparoscopy now has a new meaning. The rASRM, AAGL, UBESS, #ENZIAN and EFI …