Prevalence of ovarian mass and diagnostic performance of ultrasonography pattern recognition among women at the Gynaecologic Ultrasonography Unit at University Hospital in Thailand

The aim of this retrospective study was to determine the prevalence of ovarian masses and calculate the diagnostic performance of the pattern recognition approach in ovarian pathology. A total of 1001 patients diagnosed with ovarian mass were included, of which 92.6% were diagnosed with ovarian pathology and the presence of a pathological result, while 7.4% of cases were diagnosed with functional ovarian cyst. The prevalence of ovarian malignancy was 15%. A specific ultrasound diagnosis was suggested in 62.9% of all cases, while sonographers did not explicitly provide a diagnosis in remaining cases. A subjective assessment showed 80.3% sensitivity (95% confidence interval (CI) 68.7–89.1) and 97.6% specificity (95% CI 96–98.6) in differentiating between benign and malignant ovarian masses. The sensitivity and specificity for the diagnosis of endometriotic cyst were 77.03% and 90.63% and 63.19% and 94.3% for mature cystic teratoma, respectively. In conclusion, assessment showed good performance in differentiating between benign and malignant ovarian mass and it was possible to diagnose several specific ovarian tumours. Impact Statement What is already known on this subject? Pattern recognition is an acceptable method for classifying ovarian mass, which exhibits specific morphological features on grey-scale ultrasonography, and can be used to predict nature and histological type. What do the results of this study add? Even in the hands of an expert examiner, there were a number of cases in which the diagnoses could not be specifically stated. Pattern recognition correctly classified 90.3% of ovarian masses as either benign or malignant and correctly provided specific histologic diagnoses after exclusion of unspecified diagnosis in 80.6% of all cases. The diagnostic performance of this approach was high in differentiating between benign and malignant ovarian mass and in diagnosing some specific ovarian pathologies. What are the implications of these findings for clinical practice and/or further research? A subjective assessment is simple and easy to use in clinical practice and has shown promising results in classifying benign and malignant ovarian mass. Moreover, it can also be used to make some specific diagnoses. However, specialised and experienced gynaecological ultrasound examiners are required to provide the most accurate diagnosis. Therefore, criteria to describe ultrasound features and convincing operators to make a definite diagnosis as often as possible should be encouraged. A prospective study to verify diagnostic performance of pattern recognition or comparing with other ultrasonographic diagnostic tools should be considered

Body Fat Distribution in Thai Reproductive-Aged Polycystic Ovary Syndrome Women Compared with Non-Polycystic Ovary Syndrome Women

Background: The body fat in polycystic ovary syndrome (PCOS) women is mostly centrally distributed and is associated with insulin resistance, diabetes mellitus, and hyperandrogenemia. This study compared the fat distributions of Thai PCOS and non-PCOS women, and it investigated the association between body fat distribution in PCOS women with glucose tolerance and serum androgens. Methods: The PCOS and non-PCOS groups each had 60 women. The body mass indexes (BMI) of the groups were matched. Blood tests and fat distributions were compared between group. Results: The mean age of the non-PCOS group was significantly higher than that of the PCOS group (30.85 ± 6.41 vs. 25.95 ± 5.16 years; p-value < 0.001). The glucose level after a 2-hour, 75-gram, oral glucose tolerance test (75-g OGTT) of the PCOS group, and its insulin resistance, triglyceride, low-density lipoprotein, total testosterone, free testosterone, and dehydroepiandrosterone sulphate levels, were significantly higher than the corresponding values of the non-PCOS group. The fat distribution patterns of the 2 groups were generally not significantly different. The level of fat distributed in the arms was significantly elevated among PCOS women with abnormal 75-g OGTT values. The fat distributions of PCOS women, regardless of hyperandrogenemia status, did not significantly differ. Conclusions: No significant differences in fat distribution were observed between the PCOS and non-PCOS groups. PCOS participants with abnormal 75-g OGTT levels had a higher proportion of arm-fat compared to those with normal results. There were no discernible differences in fat distribution patterns between PCOS women with hyperandrogenemia and those with normal androgen levels