No abstract

Primary malignant melanomas (MM) originating from the gynecological tract are rare. They respond poorly to immunotherapy when compared with cutaneous MM. This study reports two cases. The first is of a 54‐year‐old woman with a cervical amelanotic polypoid mass who was diagnosed as having stage IB1 cervical melanoma according to the International Federation of Gynecology and Obstetrics system. At 17 months post‐surgery, a computed tomography examination revealed recurrence of a 68 mm pelvic tumor. The second case is of a 37‐year‐old woman with a 7 cm hemorrhagic mass on the vaginal wall. The patient was diagnosed as having stage IV vaginal melanoma according to the American Joint Committee on Cancer definition. Both patients received nivolumab therapy, programmed cell death receptor 1 monoclonal antibodies, and the tumors almost disappeared. These cases may add the possibility of using colposcopy with narrow‐band imaging and positron‐emission tomography to diagnose and evaluate primary MM.

Cesarean scar pregnancy (CSP) is a rare type of ectopic pregnancy. It is becoming more common, but it can lead to uterine rupture and severe hemorrhage. Here, we report a case of a 37-year-old woman with CSP complicated with pseudoaneurysm. The pseudoaneurysm emerged following focal injection of methotrexate (MTX) and potassium chloride with systemic MTX treatment. Due to a risk of sudden bleeding, uterine artery embolization (UAE) was recommended, but the patient hoped to avoid this if possible. Because the serum human chorionic gonadotropin level and the gestational sac were still persistent, dilation and curettage were performed with interventional radiologists on standby. Severe hemorrhage occurred and continued during the procedure, which necessitated emergent UAE. We reviewed six CSP case reports with vascular abnormalities, and all of them necessitated UAE, surgical excision, or hysterectomy. In the case of CSP combined with pseudoaneurysm, treatment should be planned carefully considering the risk of massive hemorrhage.

Although maternal pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) are related to fetal growth, there is a paucity of data regarding how offspring sex affects the relationship between maternal BMI in underweight mothers (pre-pregnancy BMI <18.5 kg/m2) and size for gestational age at birth. The aim of this study was to investigate the effect of offspring sex on the relationships among maternal pre-pregnancy BMI, GWG and size for gestational age at birth in Japanese underweight mothers. Records of women with full-term pregnancies who underwent perinatal care at Kawasaki Municipal Hospital (Kawasaki, Japan) between January 2013 and December 2017 were retrospectively reviewed. The study cohort included underweight (n=566) and normal-weight women (18.5 kg/m2⩽pre-pregnancy BMI<25 kg/m2; n=2671). The incidence of small for gestational age (SGA) births in the underweight group was significantly higher than that in the normal-weight group (P<0.01). Additionally, SGA incidence in the underweight group was significantly higher than that in the normal-weight group (P<0.01) in female, but not male (P=0.30) neonates. In the women with female neonates, pre-pregnancy underweight was associated with a significantly increased probability of SGA (odds ratio [OR]: 1.80; P<0.01), but inadequate GWG was not (OR: 1.38; P=0.11). In contrast, in women with male neonates, inadequate GWG was associated with a significantly increased probability of SGA (OR: 1.53; P=0.03), but not with pre-pregnancy underweight (OR: 1.30; P=0.10). In conclusion, the present results suggest that pre-pregnancy underweight is associated with SGA in female offspring but not in male offspring.

Introduction: Detection of neurological conditions is of high importance in the current context of increasingly ageing populations. Imaging of the retina and the optic nerve head represents a unique opportunity to detect brain diseases, but requires specific human expertise. We review the current outcomes of artificial intelligence (AI) methods applied to retinal imaging for the detection of neurological and neuro-ophthalmic conditions. Method: Current and emerging concepts related to the detection of neurological conditions, using AI-based investigations of the retina in patients with brain disease were examined and summarised. Results: Papilloedema due to intracranial hypertension can be accurately identified with deep learning on standard retinal imaging at a human expert level. Emerging studies suggest that patients with Alzheimer’s disease can be discriminated from cognitively normal individuals, using AI applied to retinal images. Conclusion: Recent AI-based systems dedicated to scalable retinal imaging have opened new perspectives for the detection of brain conditions directly or indirectly affecting retinal structures. However, further validation and implementation studies are required to better understand their potential value in clinical practice. Keywords: Alzheimer’s disease, deep learning, dementia, optic neuropathy, papilloedema