Construction of deep learning-based convolutional neural network model for automatic detection of fluid hysteroscopic endometrial micropolyps in infertile women with chronic endometritis.

OBJECTIVE(S): Chronic endometritis (CE) is a localized mucosal inflammatory disorder associated with female infertility of unknown etiology, endometriosis, tubal factors, repeated implantation failure, and recurrent pregnancy loss, along with atypical uterine bleeding and iron deficiency anemia. Diagnosis of CE has traditionally relied on endometrial biopsy and detection of CD138(+) endometrial stromal plasmacytes. To develop a less invasive diagnostic system for CE, we aimed to construct a deep learning-based convolutional neural network (CNN) model for the automatic detection of endometrial micropolyps (EMiP), a fluid hysteroscopy (F-HSC) finding recognized as tiny protrusive lesions that are closely related to this disease. STUDY DESIGN: This is an in silico study using archival images of F-HSC performed at an infertility center in a private clinic. A total of 244 infertile women undergoing F-HSC on the days 6-12 of the menstrual cycle between April 2019 and December 2021 with histopathologically-confirmed CE with the aid of immunohistochemistry for CD138 were utilized. RESULTS: The archival F-HSC images of 208 women (78 with EMiP and 130 without EMiP) who met the inclusion criteria were finally subjected to analysis. Following preprocessing of the images, half a set was input into a CNN architecture for training, whereas the remaining images were utilized as the test set to evaluate the performance of the model, which was compared with that of the experienced gynecologists. The sensitivity, specificity, accuracy, precision, and F1-score of the CNN model-aided diagnosis were 93.6 %, 92.3 %, 92.8 %, 88.0 %, and 0.907, respectively. The area under the receiver operating characteristic curves of the CNN model-aided diagnosis (0.930) was at a similar level (p > .05) to the value of conventional diagnosis by three experienced gynecologists (0.927, 0.948, and 0.906). CONCLUSION: These findings indicate that our deep learning-based CNN is capable of recognizing EMiP in F-HSC images and holds promise for further development of the computer-aided diagnostic system for CE.

Clinical outcomes of single blastocyst transfer with machine learning guided noninvasive chromosome screening grading system in infertile patients.

BACKGROUND: Prospective observational studies have demonstrated that the machine learning (ML) -guided noninvasive chromosome screening (NICS) grading system, which we called the noninvasive chromosome screening-artificial intelligence (NICS-AI) grading system, can be used embryo selection. The current prospective interventional clinical study was conducted to investigate whether this NICS-AI grading system can be used as a powerful tool for embryo selection. METHODS: Patients who visited our centre between October 2018 and December 2021 were recruited. Grade A and B embryos with a high probability of euploidy were transferred in the NICS group. The patients in the control group selected the embryos according to the traditional morphological grading. Finally, 90 patients in the NICS group and 161 patients in the control group were compared statistically for their clinical outcomes. RESULTS: In the NICS group, the clinical pregnancy rate (70.0% vs. 54.0%, p < 0.001), the ongoing pregnancy rate (58.9% vs. 44.7%, p = 0.001), and the live birth rate (56.7% vs. 42.9%, p = 0.001) were significantly higher than those of the control group. When the female was ≥ 35 years old, the clinical pregnancy rate (67.7% vs. 32.1%, p < 0.001), ongoing pregnancy rate (56.5% vs. 25.0%, p = 0.001), and live birth rate (54.8% vs. 25.0%, p = 0.001) in the NICS group were significantly higher than those of the control group. Regardless of whether the patients had a previous record of early spontaneous abortion or not, the live birth rate of the NICS group was higher than that of the control group (61.0% vs. 46.9%; 57.9% vs. 34.8%; 33.3% vs. 0%) but the differences were not statistically significant. CONCLUSIONS: NICS-AI was able to improve embryo utilisation rate, and the live birth rate, especially for those ≥ 35 years old, with transfer of Grade A embryos being preferred, followed by Grade B embryos. NICS-AI can be used as an effective tool for embryo selection in the future.

Rapid screening of infertility-associated gynecological conditions via ambient glow discharge mass spectrometry utilizing urine metabolic fingerprints.

Infertility presents a widespread challenge for many families worldwide, often arising from various gynecological diseases (GDs) that hinder successful pregnancies. Current diagnostic methods for GDs have disadvantages such as low efficiency, high cost, misdiagnose, invasive injury and etc. This paper introduces a rapid, non-invasive, efficient, and straightforward analytical method that utilizes desorption, separation, and ionization mass spectrometry (DSI-MS) platform in conjunction with machine learning (ML) to detect urine metabolite fingerprints in patients with different GDs. We analyzed 257 samples from patients diagnosed with polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), diminished ovarian reserve (DOR), endometriosis (EMS), recurrent pregnancy loss (RPL), recurrent implantation failure (RIF), and 87 samples from healthy control (HC) individuals. We identified metabolite differences and dysregulated pathways through dimensionality reduction methods, with the result of the discovery of 7 potential biomarkers for GDs diagnosis. The ML method effectively distinguished subtle differences in urine metabolite fingerprints. We anticipate that this innovative approach will offer a patient-friendly, rapid screening, and differentiation method for infertility-related GDs patients.

Biomarkers identification in follicular fluid in relation to live birth in in vitro fertilization of women with polycystic ovary syndrome in different subtypes by using UPLC-MS method.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a common infertility disorder which affects reproductive-aged women. However, metabolic change profiles of follicular fluid (FF) in lean and obese women diagnosed with and without PCOS remains unclear. METHODS: 95 infertile women were divided into four subgroups: LC (lean control), OC (overweight control), LP (lean PCOS), and OP (overweight PCOS). The FF samples were collected during oocyte retrieval and assayed by ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) metabolomics. RESULTS: A total of 236 metabolites were identified by metabolic analysis. The pathway enrichment analysis revealed that the glycerophospholipid metabolism (impact = 0.11182), ether lipid metabolism (impact = 0.14458), and primary bile acid biosynthesis (impact = 0.03267) were related to metabolic pathway between PCOS and control. Correlation analyses showed that epitestosterone sulfate was found positively correlated with fertilization rate in PCOS, while falcarindione, lucidone C. and notoginsenoside I was found to be negatively correlated. The combined four biomarkers including lucidone C, epitestosterone sulfate, falcarindione, and notoginsenoside I was better in predicting live birth rate, with AUC of 0.779. CONCLUSION: The follicular fluid of women with PCOS showed unique metabolic characteristics. Our study provides better identification of PCOS follicular fluid metabolic dynamics, which may serve as potential biomarkers of live birth.

Laparoscopic transfundal approach to cervical dilation: a novel treatment for cervical stenosis and cervical factor infertility.

OBJECTIVE: To demonstrate a novel technique used to restore cervical patency in a patient with severe iatrogenic cervical stenosis. DESIGN: Surgical video case report. SETTING: A single academic institution. PATIENT(S): We highlight the case of a 35-year-old nulliparous woman with a history of primary infertility. Her past medical history was significant for focal, invasive, well-differentiated squamous cell carcinoma of the cervix, for which she underwent a loop electrosurgical excision procedure. During her infertility assessment, she was found to have an extremely stenotic cervix that was refractory to conventional treatment options. INTERVENTIONS: This video highlights our innovative laparoscopic transfundal technique used to restore her cervical patency. MAIN OUTCOME MEASURES: None, as this is a descriptive case report. RESULTS: Postoperatively, the patient had continued cervical patency for >1 year with successful fertility treatment resulting in pregnancy. CONCLUSIONS: To our knowledge, this is the first case report describing a laparoscopic transfundal approach used to reestablish cervical patency. This approach may be considered for patients with cervical stenosis who have not responded to standard conservative therapies.

Prophecy, prediction, and prognosis - can we improve the advice we give on the chance of pregnancy and treatment options for infertility?

Giving patients an accurate prognosis of their chances of achieving pregnancy is difficult with our current knowledge and technology. We need new approaches and thinking to provide truthful information.

A comprehensive review of the new FIGO classification of ovulatory disorders.

BACKGROUND: The World Health Organization (WHO) system for the classification of disorders of ovulation was produced 50 years ago and, by international consensus, has been updated by the International Federation of Gynecology and Obstetrics (FIGO). OBJECTIVE AND RATIONALE: This review outlines in detail each component of the FIGO HyPO-P (hypothalamic, pituitary, ovarian, PCOS) classification with a concise description of each cause, and thereby provides a systematic method for diagnosis and management. SEARCH METHODS: We searched the published articles in the PubMed database in the English-language literature until October 2022, containing the keywords ovulatory disorders; ovulatory dysfunction; anovulation, and each subheading in the FIGO HyPO-P classification. We did not include abstracts or conference proceedings because the data are usually difficult to assess. OUTCOMES: We present the most comprehensive review of all disorders of ovulation, published systematically according to the logical FIGO classification. WIDER IMPLICATIONS: Improving the diagnosis of an individual's ovulatory dysfunction will significantly impact clinical practice by enabling healthcare practitioners to make a precise diagnosis and plan appropriate management.

The details matter: personalized prediction of live birth after in vitro fertilization in women with polycystic ovary syndrome.

OBJECTIVE: To derive and internally validate a clinical prediction model for live birth (LB) in women with polycystic ovary syndrome (PCOS) undergoing in vitro fertilization (IVF). DESIGN: Retrospective cohort study. SETTING: Four academic reproductive endocrinology clinics. PATIENTS: A total of 207 women with PCOS confirmed using Rotterdam criteria undergoing their first fresh IVF cycle. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: The primary outcome was cumulative LB per IVF cycle start. This included any LB that resulted from either fresh embryo transfer or any subsequent frozen embryo transfer from embryos obtained at the index oocyte retrieval. A prediction model was derived using multivariable logistic regression. Covariates considered for inclusion in the prediction model included demographic characteristics, medical history, and prior fertility treatment. Predicted probabilities for LB were calculated using the prediction model which included the 90% shrinkage factor for each adjusted odds ratio. RESULTS: The final model, on the basis of maximization of the area under the receiver operating characteristic curve, included age < 35 years, White race, presence of polycystic ovaries on ultrasound (polycystic ovary morphology), normal body mass index (<25 kg/m2), being metabolically healthy (no metabolic risk factors), and being a nonresponder to ovulation induction agents including letrozole and clomiphene citrate. The area under the receiver operating characteristic curve score for the model was 0.68 (95% confidence interval [CI]: 0.60, 0.77). Predicted probabilities of LB ranged from 8.1% (95% CI: 2.8, 21.5) for a woman who had no favorable predictors to 74.2% (95% CI: 59.5, 84.9) for a woman who had all favorable predictors. CONCLUSION: Our study demonstrated that, in addition to anovulation, the underlying pathophysiology and associated comorbidities alter the likelihood of a successful pregnancy in women with PCOS undergoing IVF. Further validation of this model is needed before it can serve as a tool to personalize prediction estimates for the probability of LB in women with PCOS.

Association of platinum-based chemotherapy with live birth and infertility in female survivors of adolescent and young adult cancer.

OBJECTIVE: To estimate the effect of platinum-based chemotherapy on live birth (LB) and infertility after cancer, in order to address a lack of treatment-specific fertility risks for female survivors of adolescent and young adult cancer, which limits counseling on fertility preservation decisions. DESIGN: Retrospective cohort study. SETTING: US administrative database. PATIENTS: We identified incident breast, colorectal, and ovarian cancer cases in females aged 15-39 years who received platinum-based chemotherapy or no chemotherapy and matched them to females without cancer. INTERVENTION: Platinum-based chemotherapy. MAIN OUTCOME MEASURES: We estimated the effect of chemotherapy on the incidence of LB and infertility after cancer, overall, and after accounting for competing events (recurrence, death, and sterilizing surgeries). RESULTS: There were 1,287 survivors in the chemotherapy group, 3,192 in the no chemotherapy group, and 34,147 women in the no cancer group, with a mean age of 33 years. Accounting for competing events, the overall 5-year LB incidence was lower in the chemotherapy group (3.9%) vs. the no chemotherapy group (6.4%). Adjusted relative risks vs. no chemotherapy and no cancer groups were 0.61 (95% confidence interval [CI] 0.42-0.82) and 0.70 (95% CI 0.51-0.93), respectively. The overall 5-year infertility incidence was similar in the chemotherapy group (21.8%) compared with the no chemotherapy group (20.7%). The adjusted relative risks vs. no chemotherapy and no cancer groups were 1.05 (95% CI 0.97-1.15) and 1.42 (95% CI 1.31-1.53), respectively. CONCLUSIONS: Cancer survivors treated with platinum-based chemotherapy experienced modestly increased adverse fertility outcomes. The estimated effects of platinum-based chemotherapy were affected by competing events, suggesting the importance of this analytic approach for interpretations that ultimately inform clinical fertility preservation decisions.

Elevated HbA1c Level has a Linear Association with Infertility in Women.

BACKGROUND: Hemoglobin A1c (HbA1c) is commonly known as a plasma glucose monitoring indicator. However, the relationship between HbA1c and fertility has not been clarified in previous literature. This study aims to investigate the association between HbA1c and the incidence of infertility. METHODS: Data from the U.S. National Health and Nutrition Examination Survey (NHANES) 2013 - 2018 was utilized. The final study contained 3,319 women aged 18 to 45 years. Multivariable logistic regression models were performed to analyze the correlation of HbA1c on female infertility with adjustment for relevant covariates including demographic characteristics, lifestyle, clinical laboratory biomarkers, and comorbidities. RESULTS: We found a significant linear correlation between HbA1c and infertility even in the fully-adjusted model (OR: 1.27, 95% CI: 1.07 - 1.5). Subgroup analysis stratified by age showed a significant linear association with HbA1c and infertility in the younger group (age < 35 years). Whereas, results showed a lack of significant association in the older group (age > 35 years). CONCLUSIONS: Data from a population-based sample in US women aged 18 to 45 years suggest that elevated HbA1c level correlated with increasing risk of infertility, even HbA1c is within the normal range. Further well-designed randomized controlled trials are needed to determine whether strategies to reduce HbA1c levels are effective in decreasing the incidence of female infertility.

Chlamydial Antibody Test in Screening of Tubal Infertility: Specificity and Sensitivity Analysis.

Sexually transmitted infection is a frequent cause of tubal factor abnormality. Chlamydia trachomatis is a common causative organism for sexually transmitted infection. There are studies indicating association of chlamydial antibodies in serum with tubal abnormalities. In many centers chlamydial antibody test is done as part of routine work up for infertility. The objective of the study was to evaluate the sensitivity and specificity of chlamydial antibody test in screening infertile women for tubal factor infertility. This cross-sectional observational study was performed for one year from January 2019 to December 2019 in the Department of Reproductive Endocrinology and Infertility of Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh. The infertile women having laparoscopy as part of infertility work up were enrolled in the study. The women had their serum tested for chlamydial antibody IgG by enzyme linked immune-sorbent assay. The sero-positivity for chlamydial antibody was tested against the findings of laparoscopy and dye test as gold standard for diagnosing tubal factor infertility. Statistical analysis was done to find out the sensitivity and specificity of the chlamydial antibody test in screening infertile women for tubal factor infertility. The study population included 163 infertile women with mean age 29.8±5.8 years. The tubal factor infertility was present in 56.4% of the women. The sero-positivity of Chlamydia trachomatis IgG was 36.6%. Sensitivity and specificity of Chlamydial antibody test (IgG positive) in detecting tubal factor infertility is 47.8% and 70.4% respectively. Positive predictive value of chlamydial antibody test in detecting tubal factor infertility is 41.5% and negative predictive value is 72.4%. Positive likelihood ratio is 1.59. Negative likelihood ratio is 0.74. Accuracy is 57.67%. In conclusion, the chlamydial antibody test may not be an appropriate screening test for tubal factor infertility in women of Bangladesh because of low sensitivity and moderately high specificity.

Subclinical hypothyroidism in the infertile female population: a guideline.

There is controversy regarding whether to treat subtle abnormalities of thyroid function in infertile female patients. This guideline document reviews the risks and benefits of treating subclinical hypothyroidism in female patients with a history of infertility and miscarriage, as well as obstetric and neonatal outcomes in this population.