The prolonged lockdown of health services providing high-complexity fertility treatments –as currently recommended by many reproductive medicine entities– is detrimental for society as a whole, and infertility patients in particular. Globally, approximately 0.3% of all infants born every year are conceived using assisted reproductive technology (ART) treatments. By contrast, the total number of COVID-19 deaths reported so far represents approximately 1.0% of the total deaths expected to occur worldwide over the first three months of the current year. It seems, therefore, that the number of infants expected to be conceived and born –but who will not be so due to the lockdown of infertility services– might be as significant as the total number of deaths attributed to the COVID-19 pandemic. We herein propose remedies that include a prognostic-stratification of more vulnerable infertility cases in order to plan a progressive restart of worldwide fertility treatments. At a time when preventing complications and limiting burdens for national health systems represent relevant issues, our viewpoint might help competent authorities and health care providers to identify patients who should be prioritized for the continuation of fertility care in a safe environment.

This review article aims to summarize current tools used in the diagnosis of adenomyosis with relative pharmacological and surgical treatment and to clarify the relative association between adenomyosis and infertility, considering the importance of an accurate diagnosis of this heterogeneous disease. Among different reported concepts, direction invagination of gland cells from the basalis endometrium deep into the myometrium is the most widely accepted opinion on the development of adenomyosis. Adenomyosis has been increasingly identified in young women with pain, AUB, infertility, or no symptoms by using imaging techniques such as transvaginal ultrasound and magnetic resonance. Furthermore, adenomyosis often coexists with other gynecological conditions, such as endometriosis and uterine fibroids, increasing the heterogeneity of available data. However, there is no agreement on the definition and classification of adenomyotic lesions from both the histopathology and the imaging points of view, and diagnosis remains difficult and unclear. A standard, universally accepted classification system needs to be implemented to improve our understanding and inform precise diagnosis of the type of adenomyosis. This could be the key to designing RCT studies and evaluating the impact of adenomyosis on quality of life in terms of menstrual symptoms, fertility, and pregnancy outcome, given the high risk of miscarriage and obstetric complications.

The evolution of preimplantation genetic testing for aneuploidy (PGT-A) techniques has been crucial in assisted reproductive technologies (ARTs), improving embryo selection and increasing success rates in in vitro fertilization (IVF) treatments. Techniques ranging from fluorescence in situ hybridization (FISH) to next-generation sequencing (NGS) have relied on cellular material extraction through biopsies of blastomeres at the cleavage stage on day three or from trophectoderm (TE) cells of the blastocyst. However, this has raised concerns about its potential impact on embryo development. As a result, there has been growing interest in developing non-invasive techniques for detecting aneuploidies, such as the analysis of blastocoel fluid (BF), spent culture medium (SCM), and artificial intelligence (AI) models. Non-invasive methods represent a promising advancement in PGT-A, offering the ability to detect aneuploidies without compromising embryo viability. This article reviews the evolution and principles of PGT-A, analyzing both traditional techniques and emerging non-invasive approaches, while highlighting the advantages and challenges associated with these methodologies. Furthermore, it explores the transformative potential of these innovations, which could optimize genetic screening and significantly improve clinical outcomes in the field of assisted reproduction.

A T-shaped uterus is a rare uterine malformation that is classically associated with diethylstilbesterol (DES) exposure. Surprisingly, the prevalence of T- and Y-shaped uterus has increased in recent years despite the absence of a diagnostic consensus and a correlation with the reproductive outcomes has been observed. A systematic electronic database search for all English-language studies published on reproductive outcomes associated with dysmorphic uteri over the past 10 years using PubMed, Google Scholar, and Scopus was performed. This uterine malformation is associated with impaired reproductive outcomes, including primary infertility, miscarriage, ectopic pregnancy, and preterm birth. Hysteroscopic metroplasty is a simple surgical procedure that could potentially improve outcomes in subfertile women, but the data are not robust. Studies reported significant improvements in implantation and pregnancy rates after corrective metroplasty in women undergoing in vitro fertilization. However, multicenter, prospective, randomized, and controlled trials are needed to validate these findings and to help define clear diagnostic criteria, surgical indications, and appropriate follow-up of reproductive outcomes after the procedure.

Background: Embryo selection in in vitro fertilization (IVF) aims to prioritize embryos with the highest reproductive potential. While preimplantation genetic testing for aneuploidy (PGT-A) remains the gold standard for identifying euploid embryos, it is invasive and not universally applicable. Deep learning (DL)-based models, such as the intelligent data analysis (iDA) score, have emerged as non-invasive alternatives for embryo assessment. This review critically evaluates the relationship between iDAScore (versions 1.0 and 2.0), embryo euploidy, and clinical outcomes, including live birth and miscarriage rates. Methods: A narrative review was performed using PubMed and Google Scholar, covering studies published from January 2020 to May 2025. The search included terms such as “iDAScore,” “deep learning,” “euploidy,” and “live birth.” Only English-language full-text studies assessing the predictive performance of iDAScore relative to chromosomal status or reproductive outcomes were included. Results: Six retrospective studies met the inclusion criteria. All reported a statistically significant association between higher iDAScore values and embryo euploidy. AUC values for euploidy prediction ranged from 0.60 to 0.68. In several studies, iDAScore was also positively associated with live birth rates and negatively with miscarriage rates. However, the predictive accuracy was moderate when restricted to euploid embryo cohorts, indicating that iDAScore may be more effective in broader populations where chromosomal status is unknown. Conclusions: iDAScore represents a promising adjunct to traditional embryo assessment. Although it cannot replace PGT-A, it may aid in embryo prioritization when genetic testing is not feasible. Larger prospective studies are warranted to further validate its clinical utility.