Objective: This retrospective study aimed to investigate the prevalence of chronic endometritis, diagnosed using CD138 immunohistochemistry, among infertile women and to assess the association between chronic endometritis and recurrent implantation failure (RIF). Methods: In total, 266 patients who underwent hysteroscopy due to infertility between 2019 and 2020 were included in the analysis. Of these, 136 patients with RIF and 130 non-RIF patients were included in the study. CD138 immunohistochemistry test results, blood biomarkers (including natural killer cells, white blood cells, and the lymphocyte-to-neutrophil ratio), and data on pregnancy outcomes were obtained. If the CD138 test yielded a positive result, the patients received antibiotic treatment. Results: The overall proportion of CD138-positive patients was 32.7% (87/266). The CD138 positivity rate was not related to the number of cycles with implantation failure. In the RIF patient group, no significant associations were found between CD138 positivity and peripheral blood markers. The clinical pregnancy rates were similar between infertile women treated with antibiotics for chronic endometritis and those without chronic endometritis. Conclusion To improve the pregnancy rate in infertile patients, it may be helpful to combine CD138 testing with other laboratory tests and administer antibiotic treatment if the result is positive.

Purpose: This study aimed to compare the effects of different normalization methods on radiomics features extracted from magnetic resonance imaging (MRI). Materials and Methods: Preoperative T1-contrast enhanced MRI data from 212 patients with meningiomas were obtained from two university hospitals. The tumors were segmented using 3D Slicer software, and the PyRadiomics framework was used to extract radiomics features. We developed four experiments to predict the histological grade of meningiomas prior to surgery. The first experiment was performed without normalization.The next three experiments used the StandardScaler, MinMaxScaler, and RobustScaler to normalize radiomics features. The PyCaret framework was used for feature selection and to explore an optimized machine learning model for predicting meningioma grades. The prediction models were trained and validated using data from the first hospital. External test data from the second hospital were used to test the performance of the final models. Results: Our testing results demonstrated that meningioma grade prediction performance depends highly on the choice of the normalization method. The RobustScaler demonstrated a higher level of accuracy and sensitivity than the other normalization methods. The area under the receiver operating characteristic curve and specificity of the RobustScaler method were comparable to those of no-normalization but higher than those of the Standard and MinMaxScaler methods. Conclusion The results of our study suggest that careful consideration of the normalization method may provide a way to optimize the experimental results.Keywords: Meningiomas; Radiomics features; Magnetic resonance ima

Purpose: The present study aimed to identify microorganisms in follicular fluids and to investigate their association with in vitro fertilization (IVF) outcomes. Materials and Methods: This study was conducted as a prospective study of 49 infertile females undergoing IVF/intracytoplasmic sperm injection cycles between 2013 and 2016. Paired follicular fluid and vaginal secretions were collected on the day of ovum pick up and were cultured to detect microorganisms. Results: Fifteen women (30.6%) had no microorganisms in follicular fluid or vaginal swabs, 23 (46.9%) had microorganisms on vaginal swab alone, 3 (6.1%) had microorganisms in follicular fluid alone, and 8 (16.3%) had microorganisms in both follicular fluid and vaginal swabs. The same microorganisms were detected in both the follicular fluid and vaginal swabs of three women, while different microorganisms were detected between follicular fluid and vaginal swabs in five women. Follicular fluid microorganisms were not associated with embryo quality or clinical pregnancy rates during IVF cycles. However, significantly decreased implantation rates (9.1% vs. 29.4%, p=0.031) and clinical pregnancy rates on embryo transfer day 5 (0% vs. 83.3%, p=0.048) were observed in the group that was positive for vaginal pathogens. Conclusion Follicular fluid contains microorganisms that can differ from those in the vagina of the same women; however, they do not appear to be associated with embryo quality or clinical pregnancy rates in IVF cycles. In contrast, vaginal pathogens were found to be associated with worse implantation rates and clinical pregnancy rates in IVF cycles.

Objective: The aim of this study was to assess the correlation of oocyte number with serum anti-Müllerian hormone (AMH) levels measured by two automated methods (Access or Elecsys) in fresh stimulated in vitro fertilization (IVF) cycles. Methods: In this retrospective study at a university hospital, data were collected from 243 fresh stimulated IVF cycles performed from August 2016 to December 2020. The serum AMH level was measured by Access in 120 cycles and by Elecsys in 123 cycles. The cut-off of serum AMH for prediction of poor responders (three or fewer oocytes) or high responders (15 or more oocytes) was calculated by the receiver operating characteristic curve analysis. Results: For the two automated methods, the following equations were derived: total oocyte number=2.378+1.418×(Access-AMH) (r=0.645, p<0.001) and total oocyte number=2.417+2.163×(Elecsys-AMH) (r=0.686, p<0.001). The following combined equation could be derived: (Access-AMH)=0.028+1.525×(Elecsys-AMH). To predict poor responders, the cut-off of Access-AMH was 1.215 ng/mL (area under the curve [AUC], 0.807; 95% confidence interval [CI], 0.730–0.884; p<0.001), and the cut-off of Elecsys-AMH was 1.095 ng/mL (AUC, 0.848; 95% CI, 0.773–0.923; p<0.001). To predict high responders, the cut-off of Access-AMH was 3.450 ng/mL (AUC, 0.922; 95% CI, 0.862–0.981; p<0.001), and the cut-off of Elecsys-AMH was 2.500 ng/mL (AUC, 0.884; 95% CI, 0.778–0.991; p<0.001). Conclusion Both automated methods for serum AMH measurement showed a good correlation with oocyte number and good performance for predicting poor and high responders in fresh stimulated IVF cycles. The Access method usually yielded higher measured serum AMH levels than the Elecsys method.

Objective: This prospective consecutive study investigated the variation in sperm DNA fragmentation (SDF) in multiple semen samples from patients with cancer. Methods: Eighty-one patients with various cancers underwent multiple semen collections on 3 consecutive days for sperm cryopreservation prior to cancer treatment. A commercial Halosperm kit was used to measure SDF. Within- and between-subject coefficients of variation were estimated via random-effects analysis of variance to assess the consistency of semen parameters and SDF. Intraclass correlation coefficients (ICCs) were calculated to assess the magnitude of the between-subject component of variance relative to the total variance. Results: The volume of semen in the day-2 and day-3 samples was significantly lower compared with the day-1 sample. Most parameters showed high ICC values, suggesting that within-subject fluctuations were small relative to the between-subject variability. The highest ICC values were identified for the SDF (ICC, 0.68; 95% confidence interval [CI], 0.45–0.84) and semen volume (ICC, 0.67; 95% CI, 0.45–0.84). Conclusion Our findings showed that repeated ejaculates from patients with cancer had stable SDF levels.

Timely analysis of imaging data is critical for diagnosis and decision-making for proper treatment strategy in the cases of ischemic stroke. Various efforts have been made to develop computer-assisted systems to improve the accuracy of stroke diagnosis and acute stroke triage. The widespread emergence of artificial intelligence technology has been integrated into the field of medicine. Artificial intelligence can play an important role in providing care to patients with stroke. In the past few decades, numerous studies have explored the use of machine learning and deep learning algorithms for application in the management of stroke. In this review, we will start with a brief introduction to machine learning and deep learning and provide clinical applications of machine learning and deep learning in various aspects of stroke management, including rapid diagnosis and improved triage, identifying large vessel occlusion, predicting time from stroke onset, automated ASPECTS (Alberta Stroke Program Early CT Score) measurement, lesion segmentation, and predicting treatment outcome. This work is focused on providing the current application of artificial intelligence techniques in the imaging of ischemic stroke, including MRI and CT.

Purpose: Preimplantation genetic testing for monogenic disorders (PGT-M) has been successfully used to prevent couples with monogenic disorders from passing them on to their child. Charcot–Marie–Tooth Disease (CMT) is a genetic disorder characterized by progressive extremity muscle degeneration and loss of sensory function. For the first time in Korea, we report our experience of applying single nucleotide polymorphism genotyping and karyomapping for PGT-M of CMT disease. Materials and Methods: Prior to clinical PGT-M, preclinical tests were performed using genotypes of affected families to identify informative single-nucleotide polymorphisms associated with mutant alleles. We performed five cycles of in vitro fertilization PGT-M in four couples with CMT1A, CMT2A, and CMT2S in CHA Fertility Center, Seoul Station. Results: From July 2020 through August 2021, five cycles of PGT-M with karyomapping in four cases with CMT1 and CMT2 were analyzed retrospectively. A total of 17 blastocysts were biopsied and 15 embryos were successfully diagnosed (88.2%).Ten out of 15 embryos were diagnosed as unaffected (66.7%). Five cycles of PGT-M resulted in four transfer cycles, in which four embryos were transferred. Three clinical pregnancies were achieved (75%) and the prenatal diagnosis by amniocentesis for all three women confirmed PGT-M of karyomapping. One woman delivered a healthy baby uneventfully and two pregnancies are currently ongoing. Conclusion This is the first report in Korea on the application of karyomapping in PGT-M for CMT patients. This study shows that karyomapping is an efficient, reliable and accurate diagnostic method for PGT-M in various types of CMT diseases.

Purpose: Although protein-induced vitamin K absence or antagonist II (PIVKA-II) has been used as a diagnostic tool for hepatocellular carcinoma (HCC), its prognostic value remains unclear. Methods: This was a nationwide multicenter study using the database of the Korean Liver Cancer Association. Patients with hepatitis B-related HCC who underwent liver resection as the first treatment after initial diagnosis (2008–2014) were selected randomly. Propensity score matching (1:1) was performed for comparative analysis between those with low and high preoperative PIVKA-II. Univariable and multivariable Cox proportional-hazards regression were used to identify prognostic factors for HCC-specific survival. Results: Among 6,770 patients, 956 patients were included in this study. After propensity score matching, the 2 groups (n = 245, each) were well balanced. The HCC-specific 5-year survival rate was 80.9% in the low PIVKA-II group and 78.7% in the high PIVKA-II group (P = 0.605). In univariable analysis, high PIVKA-II (>106.0 mAU/mL) was not a significant predictor for worse HCC-specific survival (hazard ratio [HR], 1.183; 95% confidence interval [CI], 0.76–1.85; P = 0.461). In multivariable analysis, hyponatremia of <135 mEq/L (HR, 4.855; 95% CI, 1.67–14.12; P = 0.004), preoperative ascites (HR, 4.072; 95% CI, 1.59–10.43; P = 0.003), microvascular invasion (HR, 3.112; 95% CI, 1.69–5.74; P < 0.001), and largest tumor size of ≥5.0 cm (HR, 2.665; 95% CI, 1.65–4.31; P < 0.001), but not preoperative high PIVKA-II, were independent predictors for worse HCCspecific survival. Conclusion Preoperative PIVKA-II is not an independent prognostic factor for HCC-specific survival after liver resection for hepatitis B-related HCC.

Background: To evaluate prescription trends and clinical factors of the sodium-glucose cotransporter 2 inhibitors (SGLT2i) use according to the presence of atherosclerotic cardiovascular disease (ASCVD) or heart failure (HF) in Korean patients with type 2 diabetes mellitus (T2DM). Methods: Prescription patterns of SGLT2i use between 2015 and 2019 were determined using the Korean National Health Insurance Service database of claims. Results: Of all patients with T2DM (n=4,736,493), the annual prescription rate of SGLT2i increased every year in patients with ASCVD (from 2.2% to 10.7%) or HF (from 2.0% to 11.1%). After the first hospitalization for ASCVD (n=518,572), 13.7% (n=71,259) of patients initiated SGLT2i with a median of 10.6 months. After hospitalization for HF (n=372,853), 11.2% (n=41,717) of patients initiated SGLT2i after a median of 8.8 months. In multivariate regression for hospitalization, older age (per 10 years, odds ratio [OR], 0.57; 95% confidence interval [CI], 0.56 to 0.57), lower household income (OR, 0.93; 95% CI, 0.92 to 0.95), rural residents (OR, 0.95; 95% CI, 0.93 to 0.97), and dipeptidyl peptidase-4 inhibitor (DPP-4i) users (OR, 0.82; 95% CI, 0.81 to 0.84) were associated with lesser initiation of SGLT2i in ASCVD. Additionally, female gender (OR, 0.97; 95% CI, 0.95 to 0.99) was associated with lesser initiation of SGLT2i in HF. Conclusion The prescription rate of SGLT2i increased gradually up to 2019 but was suboptimal in patients with ASCVD or HF. After the first hospitalization for ASCVD or HF, older age, female gender, low household income, rural residents, and DPP-4i users were less likely to initiate SGLT2i.