Background: Although many cervical cytology diagnostic support systems have been developed, it is challenging to classify overlapping cell clusters with a variety of patterns in the same way that humans do. In this study, we developed a fast and accurate system for the detection and classification of atypical cell clusters by using a two-step algorithm based on two different deep learning algorithms. Methods:We created 919 cell images from liquid-based cervical cytological samples collected at Sapporo Medical University and annotated them based on the Bethesda system as a dataset for machine learning. Most of the images captured overlapping and crowded cells, and images were oversampled by digital processing. The detection system consists of two steps: (1) detection of atypical cells using You Only Look Once v4 (YOLOv4) and (2) classification of the detected cells using ResNeSt. A label smoothing algorithm was used for the dataset in the second classification step. This method annotates multiple correct classes from a single cell image with a smooth probability distribution. Results:The first step, cell detection by YOLOv4, was able to detect all atypical cells above ASC-US without any observed false negatives. The detected cell images were then analyzed in the second step, cell classification by the ResNeSt algorithm, which exhibited average accuracy and F-measure values of 90.5% and 70.5%, respectively. The oversampling of the training image and label smoothing algorithm contributed to the improvement of the system's accuracy. Conclusion:This system combines two deep learning algorithms to enable accurate detection and classification of cell clusters based on the Bethesda system, which has been difficult to achieve in the past. We will conduct further research and development of this system as a platform for augmented reality microscopes for cytological diagnosis.

Aim Radical trachelectomy (RT) with pelvic lymphadenectomy has become an option for young patients with early invasive uterine cervical cancer who decide to maintain their fertility. However, this operative method entails a high risk for the following pregnancy due to its radicality. Therefore, RT for pregnant patients can be a challenge both for gynecologic oncologists and obstetricians. Methods We have performed vaginal RT for five pregnant patients with uterine cervical cancer stage 1B1 according to the method of Dargent et al. The operations were performed between 16 and 26 weeks of pregnancy, and the patients were followed up carefully according to the follow‐up methods we reported previously. Results Vaginal RT was performed for five patients without any troubles. Four of the patients continued their pregnancies until almost 34 weeks or longer under our previously published follow‐up schedule. The pregnancy of one patient was terminated at 26 weeks due to recurrence of the cancer. Conclusion Expansion of vaginal RT for pregnant patients with uterine cervical cancer could be a practical option for pregnant patients with early invasive uterine cervical cancer.

A cesarean scar can cause abnormal uterine bleeding including prolonged menstruation or postmenstrual spotting. Our patient showed massive uterine bleeding from a cesarean scar and needed blood transfusion for hemorrhagic shock. A cesarean section had only been performed once for delivery stop 9 years ago. Recurrent hemorrhage could not be controlled by conservative treatment, and we performed laparoscopic scar resection and repair. The abnormal uterine bleeding was successfully stopped, and the menstrual cycle was normalized after surgical treatment. We should be aware that even an uneventful cesarean section may have a risk of massive hemorrhage postoperatively as in the present case.

Superficial myofibroblastoma is a very rare benign mesenchymal tumor that develops in the cervix, vagina, and vulva.We report a case of superficial myofibroblastoma that was diagnosed following laparoscopic surgery for a vaginal tumor arising from the posterior fornix. The patient was a woman in her 40s (gravida 0). A flexible vaginal tumor with a smooth surface was observed arising from the posterior fornix. Magnetic resonance imaging revealed a neoplastic lesion with no signs of malignancy. We performed total laparoscopic hysterectomy and vaginal tumor resection because of the presence of multiple uterine fibroids. We made an incision in the vaginal wall on the vulva side of the tumor and removed it together with the uterus without breaking the tumor. Histopathological examination revealed superficial myofibroblastoma. The tumor was difficult to diagnose based on clinical symptoms and imaging findings. The differential diagnosis included tumors with poorer prognosis, such as aggressive angiomyxoma; thus, surgery with the aim of complete resection was required. Complete resection was possible by laparoscopically removing the uterus and tumor.