Mathew Leonardi

OBJECTIVE: To explore diagnostic preferences among individuals with confirmed or suspected endometriosis to inform the development of patient-centred diagnostic strategies. DESIGN: Qualitative study using semi-structured focus group discus…

OBJECTIVE: This study aimed to determine the accuracy of the sliding-bladder sign assessed using preoperative transvaginal ultrasound (TVS) for identifying the presence of bladder-to-uterine (BTU) adhesions in patients undergoing hysterecto…

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…

OBJECTIVE: To systematically review qualitative and quantitative evidence on the role of social media (SM) in endometriosis awareness and disease management. DATA SOURCES: A systematic search was conducted in PubMed and Scopus up to Decemb…

BACKGROUND: Diagnosis of acute and chronic pelvic inflammatory disease continues to be a challenge despite advances in investigative procedures. Complications of PID include infertility, chronic pelvic pain and ectopic pregnancy. Currently,…

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 …

INTRODUCTION: Endometriosis is a systemic inflammatory condition associated with chronic pelvic pain, delayed diagnosis and substantial impacts on physical and mental health. Many young adults (aged 18–25) experience symptoms for years befo…

In this study, we evaluate locally deployed large language models (LLMs) for converting unstructured endometriosis transvaginal ultrasound (eTVUS) reports into structured data. Across 49 de-identified reports, we compared three on-premise L…

In this study, we evaluate a locally-deployed large-language model (LLM) to convert unstructured endometriosis transvaginal ultrasound (eTVUS) scan reports into structured data for imaging informatics workflows. Across 49 eTVUS reports, we …

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-…

BACKGROUND: Endometriosis is a chronic disease characterized by endometrial-like tissue outside the uterus. Superficial endometriosis (SE) is the most prevalent form, yet it remains underdiagnosed due to subtle clinical and imaging presenta…

Diagnostic delay is a significant issue facing people with endometriosis; however, the Australian perspective and participant voice is missing for why delay occurs. The current study aimed to assess the length of diagnostic delay, whether t…

OBJECTIVES: Accurate diagnosis of pathology from ultrasound images is reliant upon images of a suitable diagnostic quality being acquired. This study aimed to create a novel machine learning model to automatically assess transvaginal ultras…

OBJECTIVE: To evaluate the diagnostic accuracy of transvaginal ultrasonography (TVUS) in detecting deep endometriosis, ovarian endometriosis, and superficial endometriosis using the IDEA (International Deep Endometriosis Analysis) consensus…

STUDY OBJECTIVE: To examine endometriosis-related content on Instagram, a platform increasingly used for health communication, to understand: 1) the identity of Instagram content creators; 2) themes, tones, and emotions evoked from posts; a…

OBJECTIVE: To assess the impact of complex disease states, including pouch of Douglas (POD) obliteration and deep endometriosis (DE) of the bowel, on the diagnostic accuracy of transvaginal ultrasound (TVUS) for detecting endometriosis of t…

BACKGROUND: Inter-observer agreement for the American Association of Gynecologic Laparoscopists (AAGL) 2021 Endometriosis Classification staging system has not been described. Its predecessor staging system, the revised American Society for…

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 …

OBJECTIVE: To identify a microbial signature for endometriosis for use as a diagnostic non-invasive biomarker. DESIGN: Prospective cohort pilot study. SETTING: Nepean Hospital and UNSW Microbiome Research Centre, Australia. POPULATION: S…