Transient urocolpos due to vesicovaginal reflux in a 37-year-old woman: a case report.

Urocolpos is a urine collection in the vagina, possibly due to vesicovaginal reflux (VVR) or a fistula. Urocolpos is a rare phenomenon in adults, and it is commonly underrecognized by radiologists. The occurrence of urocolpos due to VVR after a Caesarean section in adult females is a rare phenomenon; failure to recognize it may lead to misdiagnosis as vesicovaginal fistula and often leads to unnecessary medical interventions. We report a 37-year-old female who complained of abdominal pain and intermittent daytime urinary incontinence for six months, starting after a Caesarean section for her third baby. An abdominal computed tomography scan revealed a large fluid-filled vagina on a full bladder without anatomical abnormality. A post-voiding scan showed a complete resolution. In conclusion, urocolpos is an underrecognized entity that rarely coexists with VVR. Post-voiding resolution and vaginal contrast reflux are important findings that can aid radiologists in identifying such cases.

Pentalogy of Cantrell Associated with Ectopia Cordis: A Case Report.

Pentalogy of Cantrell is a congenital anomaly of the median mesodermal constructions with a poor prognosis. It is characterized by defects of the anterior diaphragm, the lower sternum, the abdominal wall, pericardium, and various congenital heart malformations. We present a case of ectopia cordis and Pentalogy of Cantrell in a newborn of a healthy 35-year-old woman with no history of embryotoxic exposure or smoking. The infant was first diagnosed with the anomaly in the second trimester of pregnancy and was delivered at 35 weeks of gestational age via a caesarian section. Shortly after birth, he was transferred to the neonatal intensive care unit (NICU) due to progressive respiratory failure, which ultimately, along with septicemia, led to infant death on the second day. In conclusion, the Pentalogy of Cantrell should be appropriately assessed for effective prenatal counseling and postnatal management with a multidisciplinary team; since infant survival assessment and early diagnosis give the parents the option of terminating the pregnancy.

ETECADx: Ensemble Self-Attention Transformer Encoder for Breast Cancer Diagnosis Using Full-Field Digital X-ray Breast Images.

Early detection of breast cancer is an essential procedure to reduce the mortality rate among women. In this paper, a new AI-based computer-aided diagnosis (CAD) framework called ETECADx is proposed by fusing the benefits of both ensemble transfer learning of the convolutional neural networks as well as the self-attention mechanism of vision transformer encoder (ViT). The accurate and precious high-level deep features are generated via the backbone ensemble network, while the transformer encoder is used to diagnose the breast cancer probabilities in two approaches: Approach A (i.e., binary classification) and Approach B (i.e., multi-classification). To build the proposed CAD system, the benchmark public multi-class INbreast dataset is used. Meanwhile, private real breast cancer images are collected and annotated by expert radiologists to validate the prediction performance of the proposed ETECADx framework. The promising evaluation results are achieved using the INbreast mammograms with overall accuracies of 98.58% and 97.87% for the binary and multi-class approaches, respectively. Compared with the individual backbone networks, the proposed ensemble learning model improves the breast cancer prediction performance by 6.6% for binary and 4.6% for multi-class approaches. The proposed hybrid ETECADx shows further prediction improvement when the ViT-based ensemble backbone network is used by 8.1% and 6.2% for binary and multi-class diagnosis, respectively. For validation purposes using the real breast images, the proposed CAD system provides encouraging prediction accuracies of 97.16% for binary and 89.40% for multi-class approaches. The ETECADx has a capability to predict the breast lesions for a single mammogram in an average of 0.048 s. Such promising performance could be useful and helpful to assist the practical CAD framework applications providing a second supporting opinion of distinguishing various breast cancer malignancies.

Primary huge gastric leiomyosarcoma with multiple metastases in a 60-year-old female: a case report.

The incidence of leiomyosarcomas (LMS) has declined drastically. In fact, the introduction of immunohistochemistry (IHC) helped to differentiate LMS from other gastrointestinal stromal tumors (GIST) by receptor tyrosine kinase (KIT)-mutation detection making gastric LMS a sporadic tumor recently. We report a 60-year-old female who presented with a three-week history of abdominal pain. An abdominal computed tomography scan showed a large exophytic mass (22 ×19 ×15 cm) arising from the greater curvature of the stomach with multiple metastases. A biopsy was taken, and the initial histopathological examination was suggestive of GIST. However, further histopathological examination confirmed a high-grade gastric LMS. The patient refused any surgical intervention. Therefore, the patient had only received chemotherapy. On 9-month follow-up, the patient is still alive without disease progression. In conclusion, gastric LMS is a rare tumor. Due to the possibility of being misdiagnosed with other GIST, extensive pathological evaluation through specialized experts and IHC analysis is recommended.