Patient: Female, 39-year-old Final Diagnosis: Ovarian carcinoma Symptoms: Abdominal pain • abdominal mass • abdominal tenderness Clinical Procedure: Adjuvant chemotherapy • laparotomy Specialty: Obstetrics and Gynecology • Oncology Objective: Rare disease Background: Ovarian cancer is the leading cause of death in women with gynecological cancers. Ovarian Brenner tumor (BT) is an extremely rare type of epithelial ovarian cancer that accounts for about 1–3% of all ovarian cancers. Herein, we report a rare case of ruptured malignant ovarian Brenner tumor. Case Report: A 39-year-old P0A0 woman came to the Emergency Department (ED) with abdominal pain and tenderness. Perforated appendicitis was initially suspected and an emergency laparotomy was performed by the General Surgery Department. Then, a 25×20×15 cm grayish cystic mass originating from the right adnexa was found. We consulted intraoperatively with the Gynecology Oncology Department and decided to perform complete surgical staging. Histopathological examination confirmed the diagnosis of malignant Brenner tumor (MBT). The patient was then given adjuvant chemotherapy with a paclitaxel carboplatin regimen. In this case report, we present our case along with a review of the current literature regarding the diagnosis and therapy of malignant Brenner tumor. Conclusions: Ovarian MBT is an extremely rare ovarian cancer. Diagnosing MBT can be challenging as there are no clinical, laboratory, or imaging features typical for it. Surgery is the mainstay treatment in MBT cases. The role of adjuvant chemotherapy in MBT is still being debated.
Objective Visual inspection of cervix after acetic acid application (VIA) has been considered an alternative to Pap smear in resource-limited settings, like Indonesia. However, VIA results mainly depend on examiner’s experience and with the lack of comprehensive training of healthcare workers, VIA accuracy keeps declining. We aimed to develop an artificial intelligence (AI)-based Android application that can automatically determine VIA results in real time and may be further developed as a health care support system in cervical cancer screening. Result A total of 199 women who underwent VIA test was studied. Images of cervix before and after VIA test were taken with smartphone, then evaluated and labelled by experienced oncologist as VIA positive or negative. Our AI model training pipeline consists of 3 steps: image pre-processing, feature extraction, and classifier development. Out of the 199 data, 134 were used as train-validation data and the remaining 65 data were used as test data. The trained AI model generated a sensitivity of 80%, specificity of 96.4%, accuracy of 93.8%, precision of 80%, and ROC/AUC of 0.85 (95% CI 0.66–1.0). The developed AI-based Android application may potentially aid cervical cancer screening, especially in low resource settings.
Background:Placenta accreta spectrum (PAS) is a complex obstetric complication that poses a major risk for life-threatening hemorrhage. The pathogenesis of PAS is known to be related to placentogenesis, trophoblastic cells invasion, and previous obstetrical procedures that cause uterine wall defects. However, the precise mechanism of this disease has not been fully explained. This study aimed to evaluate the differences in maximum depth of invasion and distribution pattern of implantation site intermediate trophoblasts between PAS and non-accreta cases. Material/methods:This was an observational, analytic, cross-sectional study that utilized paraffin block specimen of peripartum hysterectomy performed in Hasan Sadikin General Hospital Bandung from 2018 to 2020. Sixty-four samples were obtained, then classified as PAS and non-accreta (normal placenta). Implantation site-intermediate trophoblasts were identified using CD-146 staining. Maximum invasion depth of intermediate trophoblasts was measured in micrometers, while the distribution pattern was assessed and classified into 2 groups: confluent and scattered. Results:We found that the maximum invasion depth of the intermediate trophoblasts was significantly higher in the PAS group compared to that of the non-accreta group (2453.52±1172.122 µm vs 1613.59±822.588 µm, P=0.009).The confluent distribution pattern was significantly more common in the PAS group compared to that of the non-accreta group (87.2% vs 17.6%, P=0.0001). Conclusions:The findings of our study suggested that implantation site intermediate trophoblasts play a role in the pathophysiology of placenta accreta. Further studies are needed to determine factors that affect trophoblast invasion leading to placenta accreta spectrum.
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