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The aim of this study was to explore the application value of transvaginal color Doppler ultrasound based on the improved mean shift algorithm in the diagnosis of idiopathic premature ovarian failure (POF). In this study, 80 patients with idiopathic POF were selected and included in the experimental group, and 40 volunteers who underwent health exa...
Citations
... 11 These difference may be due to the fact that the inflow site of the right ovarian vein is the inferior vena cava, while the inflow site of the left ovary is the left renal vein. 11,12 Currently, there are few clinical comparative analyses of the left and right ovaries using three-dimensional ultrasound, and further discussion is warranted. 13,14 Our results reported lower AFC, OV, VI, VFI and FI within both the DORgroup and the POF-group versus the Normal ovarian function group (p<0.05). ...
Objective:
To explore the applicability of three-dimensional transvaginal ultrasonography (3D-TVS) in the evaluation of diminished ovarian reserve (DOR) and premature ovarian failure (POF).
Methods:
One hundred and twenty female patients, who received 3D-TVS in our hospital from January 2020 to March 2022, were included in the study. Based on sex hormone examination, 25 cases were DOR (DOR-group), 32 cases were POF (POF-group) and 63 cases had normal ovarian function (Normal-group). The 3D-TVS quantitative examination results of the three groups of patients were analyzed and compared.
Results:
There was no significant difference between the DOR-group and POF-group regarding antral follicles count (AFC), ovarian volume (OV), vascularization index (VI), vascularization flow index (VFI) and flow index (FI) of left and right ovaries (p>0.05). Compared with the Normal-group, the 3D-TVS examination indexes of the DOR-group and POF-group were significantly lower, and the 3D-TVS examination results of the POF-group were significantly lower than those of the DOR-group (p<0.05). Using sex hormone examination as the gold standard, the diagnostic specificity of 3D-TVS for DOR was 80%, and the sensitivity and accuracy were 90% and 88% respectively; The diagnostic specificity of POF was 87.5%, the sensitivity and accuracy were 95.8% and 93.8% respectively.
Conclusion:
3D-TVS can provide scientific guidance for the clinical diagnosis and evaluation of DOR and POF.
... p < 0.001) (96). An enhanced mean shift algorithm based on artificial intelligence (AI) technology was used to process ultrasound images in women with idiopathic POI, where the functional condition and hemodynamics of patients' ovaries were clearly visible on the transvaginal color Doppler ultrasonography (97). Another study demonstrated that building diagnostic methods for POI prediction may be accomplished using artificial neural networks, where the generalization ability of the train set, validation set, and test set was validated, with a prediction accuracy of over 90% in the test, train, and validation sets (98). ...
Females typically carry most of the burden of reproduction in mammals. In humans, this burden is exacerbated further, as the evolutionary advantage of a large and complex human brain came at a great cost of women’s reproductive health. Pregnancy thus became a highly demanding phase in a woman’s life cycle both physically and emotionally and therefore needs monitoring to assure an optimal outcome. Moreover, an increasing societal trend towards reproductive complications partly due to the increasing maternal age and global obesity pandemic demands closer monitoring of female reproductive health. This review first provides an overview of female reproductive biology and further explores utilization of large-scale data analysis and -omics techniques (genomics, transcriptomics, proteomics, and metabolomics) towards diagnosis, prognosis, and management of female reproductive disorders. In addition, we explore machine learning approaches for predictive models towards prevention and management. Furthermore, mobile apps and wearable devices provide a promise of continuous monitoring of health. These complementary technologies can be combined towards monitoring female (fertility-related) health and detection of any early complications to provide intervention solutions. In summary, technological advances (e.g., omics and wearables) have shown a promise towards diagnosis, prognosis, and management of female reproductive disorders. Systematic integration of these technologies is needed urgently in female reproductive healthcare to be further implemented in the national healthcare systems for societal benefit.
... Ultrasonography has an important role in reproductive medicine and assisted reproductive technologies because of its utility for several purposes including ovarian response monitoring, assessment of endometrial receptivity, transvaginal aspiration of oocytes, transcervical transfer of the embryo to the uterus, pregnancy monitoring, and fetal health assessment. It is also used to measure ovarian volume, antral follicular count (AFC), ovarian stromal blood flow, and to evaluate ovarian function after vascular embolization (3)(4)(5)(6). ...
Background:
Doppler ultrasonography is used to study ovarian vascular characteristics. However, the outcomes are reported with a considerable variability in literature. Here we review the differences in Doppler ultrasound-measured ovarian blood flow indices between women with and without ovarian dysfunction and seeks correlations between Doppler measures and ovarian markers.
Methods:
A literature search was conducted in electronic databases (Google Scholar, Ovid, PubMed, Science Direct, and Springer) to identify studies that used Doppler for ovarian blood flow examination and reported Doppler measures in women with and without ovarian dysfunction and/or the correlations between wDoppler indices and markers of ovarian dysfunction. After quality assessment of included studies, a meta-analysis of weighted mean differences (WMDs) between women with and without ovarian dysfunction in vascularization index (VI), flow index (FI), vascularization flow index (VFI), pulsatility index (PI) and resistance index (RI) was performed. Correlation coefficients between Doppler indices and markers of ovarian dysfunction were pooled to achieve overall estimates.
Results:
A total of 27 studies [2,377 women with ovarian dysfunction and 308 controls; age 27.7 years, 95% confidence interval (CI): 26.4 to 29.1] were included. These studies were of moderate quality. The VI (WMD 9.75; P<0.0001), FI (WMD 2.73; P<0.0001), and VFI (WMD 1.29; P<0.0001) were significantly higher whereas PI (WMD -1.08; P=0.001) and RI (WMD -0.26; P<0.0001) were significantly lower in women with polycystic ovarian syndrome (PCOS) than in normal women. In women undergoing in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI), antral follicle count was positively correlated with VI (r=0.24; P=0.001), FI (r=0.42; P<0.0001), and VFI (r=0.25; P=0.002). In women with PCOS, testosterone had statistically non-significant correlations with VI (r=0.40; P=0.081), and VFI (r=0.39; P=0.063) and was inversely correlated with PI (r=-0.30; P<0.0001) and RI (r=-0.48; P<0.0001). In women with PCOS, luteinizing hormone (LH) was inversely correlated with PI (r=-0.26; P=0.086) and RI (r=-0.25; P=0.007).
Conclusions:
Doppler indices are found significantly different in women with and without ovarian dysfunction and have significant correlations with markers of ovarian dysfunction. These results support the use of Doppler ultrasound to examine ovarian dysfunction. High statistical heterogeneity observed herein should be studies in future investigations.
BACKGROUND
Premature ovarian failure (POF) is the end-stage of a decline in ovarian function prior to the age of 40 years that involves symptoms associated with low estradiol (E2) levels and a minimal probability of pregnancy. This increases the physical and psychological burden experienced by young women of reproductive age, particularly with regards to over-diagnosis.
CASE SUMMARY
Here, we report three cases (29, 22, and 33 years-of-age) diagnosed with POF after experiencing secondary amenorrhea for more than one year, serum levels of follicle-stimulating hormone (FSH) > 40 IU/L on two occasions with an interval of more than 4 wk, and negative progesterone withdrawal tests. All three patients were intermittently administered with drugs to create an artificial cycle. During the subsequent discontinuation period, the patients experienced intermittent follicular growth and spontaneous ovulation. One patient experienced two natural pregnancies (both with embryo arrest).
CONCLUSION
Our findings suggest that young patients with POF can experience unpredictable and intermittent spontaneous follicular development, ovulation, and even natural pregnancy. Clinicians should provide appropriate medical guidance and individualized treatments according to fertility requirements, genetic risks and hypoestrogenic symptoms as soon as possible.
Artificial intelligence (AI) has gained prominence in medical imaging, particularly in obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is considered cost effective and easily accessible but is time consuming and hindered by the need for specialized training. To overcome these limitations, AI models have been proposed for automated plane acquisition, anatomical measurements, and pathology detection. This study aims to overview recent literature on AI applications in OB/GYN US imaging, highlighting their benefits and limitations. For the methodology, a systematic literature search was performed in the PubMed and Cochrane Library databases. Matching abstracts were screened based on the PICOS (Participants, Intervention or Exposure, Comparison, Outcome, Study type) scheme. Articles with full text copies were distributed to the sections of OB/GYN and their research topics. As a result, this review includes 189 articles published from 1994 to 2023. Among these, 148 focus on obstetrics and 41 on gynecology. AI-assisted US applications span fetal biometry, echocardiography, or neurosonography, as well as the identification of adnexal and breast masses, and assessment of the endometrium and pelvic floor. To conclude, the applications for AI-assisted US in OB/GYN are abundant, especially in the subspecialty of obstetrics. However, while most studies focus on common application fields such as fetal biometry, this review outlines emerging and still experimental fields to promote further research.
Due to its high prevalence, infertility has become a prominent public health issue, posing a significant challenge to modern reproductive medicine. Some clinical conditions that lead to female infertility include polycystic ovary syndrome (PCOS), endometriosis, and premature ovarian failure (POF). Follicular fluid (FF) is the biological matrix that has the most contact with the oocyte and can, therefore, be used as a predictor of its quality. Volatilomics has emerged as a non-invasive, straightforward, affordable, and simple method for characterizing various diseases and determining the effectiveness of their current therapies. In order to find potential biomarkers of infertility, this study set out to determine the volatomic pattern of the follicular fluid from patients with PCOS, endometriosis, and POF. The chromatographic data integration was performed through solid-phase microextraction (SPME), followed by gas chromatography–mass spectrometry (GC-MS). The findings pointed to specific metabolite patterns as potential biomarkers for the studied diseases. These open the door for further research into the relevant metabolomic pathways to enhance infertility knowledge and diagnostic tools. An extended investigation may, however, produce a new mechanistic understanding of the pathophysiology of the diseases.
