Kobe Dewilde

status: Published

Ultrasound elastography (USE) assesses tissue stiffness, adding supplemental information to real-time dynamic transvaginal ultrasound. USE is a well-established technique in non-gynecological pathology, but it has not yet been endorsed by international gynecological ultrasound guidelines. Although large prospective data are lacking, recent reports suggested its diagnostic benefit in pelvic scanning. In this mini review, we present an overview of the current gynecological use of the technique and provide a graphic overview of the use of elastography in the sonographic evaluation of the uterus and endometrium.

OBJECTIVE: Recent studies suggest that mucinous borderline ovarian tumors (MBOTs) belong to a high-risk group that is more likely to develop an invasive recurrence. The objective is to determine these risk factors. METHODS: A monocentric retrospective review of all consecutive patients with intestinal-type MBOT diagnosed between 1993 and 2013. All tumors were evaluated by one pathologist without knowledge of clinical outcome. Extensive surgical staging and pathological tumor sampling (1 block/cm diameter in tumors <10 cm and 2 blocks/cm diameter in tumors >10 cm) were performed in all cases. RESULTS: A total of 81 patients were included. Patients with micro-invasion were also included. None of the patients recurred. No bilateral tumors, nor tumors with International Federation of Gynecology and Obstetrics stage II or higher, were diagnosed. Median follow-up was 87 months. CONCLUSIONS: In our series of pure intestinal-type MBOT, including micro-invasion, no recurrences were observed. Given the heterogeneity of these tumors staging with at least unilateral salpingo-oophorectomy, extensive pathological sampling, and expert pathological review are of paramount importance to be able to diagnose a pure intestinal-type MBOT and excluding gastrointestinal mucinous tumors and more important, excluding an invasive focus, defining a mucinous ovarian carcinoma. When these conditions are fulfilled, the prognosis of pure intestinal-type MBOT is excellent.

INTRODUCTION: Ultrasonography in the first trimester of pregnancy offers an early screening tool to identify high risk pregnancies. Artificial intelligence (AI) algorithms have the potential to improve the accuracy of diagnosis and assist the clinician in early risk stratification. OBJECTIVE: The objective of the study was to conduct a systematic review of the use of AI in imaging in the first trimester of pregnancy. METHODS: We conducted a systematic literature review by searching in computerized databases PubMed, Embase, and Google Scholar from inception to January 2024. Full-text peer-reviewed journal publications written in English on the evaluation of AI in first-trimester pregnancy imaging were included. Review papers, conference abstracts, posters, animal studies, non-English and non-peer-reviewed articles were excluded. Risk of bias was assessed by using PROBAST. RESULTS: Of the 1,595 non-duplicated records screened, 27 studies were included. Twelve studies focussed on segmentation, 8 on plane detection, 6 on image classification, and one on both segmentation and classification. Five studies included fetuses with a gestational age of less than 10 weeks. The size of the datasets was relatively small as 16 studies included less than 1,000 cases. The models were evaluated by different metrics. Duration to run the algorithm was reported in 12 publications and ranged between less than one second and 14 min. Only one study was externally validated. CONCLUSION: Even though the included algorithms reported a good performance in a research setting on testing datasets, further research and collaboration between AI experts and clinicians is needed before implementation in clinical practice.