This commentary delineates the developmental pathway of artificial intelligence (AI) in ultrasound follicular monitoring, highlighting a paradigm shift from automated segmentation to clinical decision support. The deep learning-based CR-Unet and C-Rend models have enabled accurate follicle segmentation and measurement from two-dimensional to three-dimensional imaging, substantially improving boundary segmentation accuracy and measurement consistency. Building on this foundation, the study further establishes two-dimensional follicle area and three-dimensional follicle volume as novel biomarkers, providing quantitative criteria for predicting oocyte maturity and optimizing the timing of human chorionic gonadotrophin triggering. Through seamless integration of algorithms into the Acclarix LXK9 ultrasonography equipment, an intelligent monitoring platform with real-time analytical capabilities has been developed, demonstrating significantly superior measurement accuracy and consistency compared with manual operations. These advancements represent a transformative leap from image segmentation to AI-driven clinical decision making, offering robust technical support for standardized and precise management in assisted reproduction.
Research question: Should we discard embryos exposed to culture media contaminated with Enterococcus faecalis?
Design: This case report describes an IVF cycle in which the embryo culture medium was contaminated with E. faecalis originating from the sperm sample. The collection and microbiological analysis of the contaminated culture media, as well as the embryological, clinical and neonatal outcomes, are presented.
Results: A couple, both aged 23 years, presented at Brussels IVF in 2023 for a second assisted reproductive technology attempt. Following oocyte retrieval, 14 oocytes underwent conventional IVF in culture media containing 10 µg/ml gentamicin sulphate, yielding 10 fertilized oocytes, and one blastocyst was vitrified on day 5. Contamination with amoxicillin-sensitive E. faecalis was detected on day 6 (after automated aerobic and anaerobic culture; BD Bactec). A sperm culture was performed 11 days later and tested positive for E. faecalis. After obtaining the patient's informed consent, the only vitrified embryo was transferred in a natural cycle. Prophylactic amoxicillin (three times a day for 5 days) was administered to the patient following transfer. Culture medium analysis post-warming (2.5 h culture) still detected E. faecalis, suggesting persistent contamination. A healthy female infant (2845 g) was born at 40 weeks of gestation. All culture media used contained 10µg/mL gentamicin sulphate.
Conclusions: Treatment with prophylactic amoxicillin resulted in a healthy live birth from a blastocyst contaminated with E. faecalis, questioning the systematic discarding of embryos from contaminated culture medium.
Research question: Can the analysis of TikTok posts related to fertility and assisted reproduction technology better characterize the types of information shared, potential biases, and relative engagement?
Design: Using a new TikTok account posing as a woman of reproductive age in September 2024, posts were gathered using fertility- and infertility-related search terms. Descriptive post statistics were extracted, and reviewers coded each post for perceived patient demographics, creator type, post content, type of fertility treatments mentioned, and emotional tone.
Results: In total, 1905 TikTok posts were reviewed, amounting to 1,808,310,047 cumulative views and 117,087,911 cumulative likes. The majority of content creators were patients with fertility challenges (66.82%), followed by physicians (12.39%). Personal posts related to experience were most common (61.36%), followed by educational posts (28.45%). The most popular search terms in terms of both views and likes were 'infertility', 'fertility' and 'IVF' (P < 0.0001). Posts deemed to have a positive emotional tone received significantly more likes than neutral posts (P < 0.05), despite having fewer overall views. While most posts were created by patients with a light skin tone (52.36%), these posts did not differ in emotional tone or receive more engagement.
Conclusion: TikTok content about personal infertility experiences is more prevalent than content created by healthcare professionals, and broad terms such as 'infertility' and positive patient stories attract significantly more engagement than medical terminology or neutral information. It is suggested that physicians should use this information to better engage viewers on social media in order to provide balanced content and combat the spread of misinformation.

