Torsion of Tubo-Ovarian Complex during Pregnancy: A Case Report.

Introduction: Adnexal torsion is characterised by the rotation of the ovary and, occasionally, the fallopian tube around their supporting ligaments by more than 45 degrees. It predominantly occurs during the first and second trimesters of pregnancy, with an incidence of up to 0.1% in the third trimester. Dermoid and functional ovarian cysts, most commonly associated with benign serous cystadenomas, are frequently identified among the torted adnexal masses. Case Presentation: We report the case of a 32-year-old primigravida with a known ovarian cyst diagnosed in the first trimester, which was managed conservatively throughout the pregnancy. At 36 weeks of gestation, she presented with abdominal pain and was subsequently managed with an emergency caesarean section at 37 weeks due to the development of an acute surgical abdomen. During the procedure, a torted left tubo-ovarian complex was excised, with partial preservation of the healthy-appearing ovarian tissue. Histopathological examination identified the mass as a benign serous cystadenoma. Conclusions: Ovarian torsion during pregnancy poses a significant diagnostic challenge. The decision between conservative management and surgical intervention is primarily guided by a high index of suspicion for torsion.

A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging.

Gastrointestinal (GI) endoscopy has been an active field of research motivated by the large number of highly lethal GI cancers. Early GI cancer precursors are often missed during the endoscopic surveillance. The high missed rate of such abnormalities during endoscopy is thus a critical bottleneck. Lack of attentiveness due to tiring procedures, and requirement of training are few contributing factors. An automatic GI disease classification system can help reduce such risks by flagging suspicious frames and lesions. GI endoscopy consists of several multi-organ surveillance, therefore, there is need to develop methods that can generalize to various endoscopic findings. In this realm, we present a comprehensive analysis of the Medico GI challenges: Medical Multimedia Task at MediaEval 2017, Medico Multimedia Task at MediaEval 2018, and BioMedia ACM MM Grand Challenge 2019. These challenges are initiative to set-up a benchmark for different computer vision methods applied to the multi-class endoscopic images and promote to build new approaches that could reliably be used in clinics. We report the performance of 21 participating teams over a period of three consecutive years and provide a detailed analysis of the methods used by the participants, highlighting the challenges and shortcomings of the current approaches and dissect their credibility for the use in clinical settings. Our analysis revealed that the participants achieved an improvement on maximum Mathew correlation coefficient (MCC) from 82.68% in 2017 to 93.98% in 2018 and 95.20% in 2019 challenges, and a significant increase in computational speed over consecutive years.