Alison Deslandes

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 …

INTRODUCTION: Imaging is increasingly used for adult endometriosis, but evidence supporting adolescent imaging approaches remains unclear. This scoping review mapped evidence on imaging-based diagnosis of endometriosis in adolescents and yo…

Endometriosis ultrasound reports are often unstructured free-text documents that require manual abstraction for downstream tasks such as analytics, machine learning model training, and clinical auditing. We present \textbf{EndoExtract}, an …

Endometriosis ultrasound reports are often unstructured free-text documents that require manual abstraction for downstream tasks such as analytics, machine learning model training, and clinical auditing. We present \textbf{EndoExtract}, an …

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 …

Endometriosis affects 1 in 10 women globally. We aimed to determine health provider involvement and preferred methods of obtaining an endometriosis diagnosis across international jurisdictions. A global cross-sectional survey, distributed t…

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…

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 …

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…

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…

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…

INTRODUCTION/PURPOSE: The 2016 consensus statement from the International Deep Endometriosis Analysis group (IDEA) outlined a transvaginal ultrasound (TVUS) approach specific for the sonographic assessment of endometriosis (eTVUS). However,…

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…

PURPOSE: The aim of this study was to investigate the current application of artificial intelligence (AI) tools in the teaching of ultrasound skills as they pertain to gynaecological ultrasound. METHODS: A scoping review was performed. Eig…

Endometriosis affects 1 in 9 women and those assigned female at birth. However, it takes 6.4 years to diagnose using the conventional standard of laparoscopy. Noninvasive imaging enables a timelier diagnosis, reducing diagnostic delay as we…

Abstract Study question Can we improve the diagnostic accuracy of the detection of POD obliteration in endometriosis magnetic resonance imaging, by leveraging results from unpaired eTVUS data sets? Summary answer We illustrate effective mul…

Linked article: There is a comment on this article by Young et al. Click here to view the Correspondence. Linked article: There is a comment on this article by Guerriero et al. Click here to view the Correspondence.

We appreciate the feedback from Prof. Guerriero and colleagues and would like to take the opportunity to address their concerns. We agree that the International Deep Endometriosis Analysis (IDEA) consensus opinion1 has contributed significa…

Endometriosis affects 1 in 9 women, taking 6.4 years to diagnose using conventional laparoscopy. Non-invasive imaging enables timelier diagnosis, reducing diagnostic delay, risk and expense of surgery. This review updates literature explori…

This presentation aims to equip healthcare professionals with valuable insights into the role of soft markers and the siding sign as part of a comprehensive ultrasound to detect endometriosis. Attendees will learn; — What soft markers and t…

INTRODUCTION: This study aimed to assess the accuracy of transvaginal ultrasound (TVUS) for the mapping of endometriosis before surgery when performed by sonographers in an outpatient women's imaging centre. METHODS: A prospective longitud…