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Inguinal hernias containing ovary have a documented incidence of 3%. Most of the cases are associated with congenital anomalies of genital tract such as Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome. A 20-year-old female presented with primary amenorrhoea, normal secondary sexual characteristics and genetic karyotyping showing 46XX chromosome. On USG abdomen and pelvis examination complete absence of uterus, cervix and vagina was found. Both the ovaries were seen away from normal anatomical location in bilateral inguinal canal without significant complication. MRI study confirmed agenesis of uterus, cervix and vagina; bilateral inguinal hernia with ovaries as contents. Type 1 MRKH syndrome with bilateral ovarian hernias was diagnosed.

Objective To determine whether an artificial intelligence candidate could pass the rapid (radiographic) reporting component of the Fellowship of the Royal College of Radiologists (FRCR) examination. Design Prospective multi-reader diagnostic accuracy study. Setting United Kingdom. Participants One artificial intelligence candidate (Smarturgences, Milvue) and 26 radiologists who had passed the FRCR examination in the preceding 12 months. Main outcome measures Accuracy and pass rate of the artificial intelligence compared with radiologists across 10 mock FRCR rapid reporting examinations (each examination containing 30 radiographs, requiring 90% accuracy rate to pass). Results When non-interpretable images were excluded from the analysis, the artificial intelligence candidate achieved an average overall accuracy of 79.5% (95% confidence interval 74.1% to 84.3%) and passed two of 10 mock FRCR examinations. The average radiologist achieved an average accuracy of 84.8% (76.1-91.9%) and passed four of 10 mock examinations. The sensitivity for the artificial intelligence was 83.6% (95% confidence interval 76.2% to 89.4%) and the specificity was 75.2% (66.7% to 82.5%), compared with summary estimates across all radiologists of 84.1% (81.0% to 87.0%) and 87.3% (85.0% to 89.3%). Across 148/300 radiographs that were correctly interpreted by >90% of radiologists, the artificial intelligence candidate was incorrect in 14/148 (9%). In 20/300 radiographs that most (>50%) radiologists interpreted incorrectly, the artificial intelligence candidate was correct in 10/20 (50%). Most imaging pitfalls related to interpretation of musculoskeletal rather than chest radiographs. Conclusions When special dispensation for the artificial intelligence candidate was provided (that is, exclusion of non-interpretable images), the artificial intelligence candidate was able to pass two of 10 mock examinations. Potential exists for the artificial intelligence candidate to improve its radiographic interpretation skills by focusing on musculoskeletal cases and learning to interpret radiographs of the axial skeleton and abdomen that are currently considered “non-interpretable.”

We report herein the case of a 53-year-old female who came to the emergency room with the chief complaints of severe dysphagia and chest pain following accidental swallowing of her denture. The patient had swelling of the face, neck and eyelids with difficulty in breathing. A skull radiograph was taken, which revealed a missing partial denture from the right lower jaw. Anteroposterior radiograph of the chest showed two metallic objects in the mid-thorax, adjacent to the descending aorta. CT scan of the neck and chest revealed two metallic objects (measuring approximately 17mm each) in the middle one-third of the oesophagus (right posterolateral aspect), causing perforation of the oesophagus and leading to pneumomediastinum, and left pneumothorax with subcutaneous emphysema of the neck and chest. An emergency thoracoscopic removal of the foreign body (partial denture) was performed with subsequent repair of the oesophageal tear in the same sitting. Post surgery, the patient was shifted to intensive care unit and she recovered well over a course of time. In summary, accidental ingestion of a partial denture can lead to grave complications such as oesophageal perforation, which should be managed on an emergency basis with thoracoscopic removal of the foreign body.

We describe two cases of intracranial cystic lesions associated with acrocallosal syndrome. These fetal anomalies were detected on antenatal sonography and confirmed postnatally. Imaging findings include corpus callosum agenesis with interhemispheric cysts and craniofacial anomalies associated with polydactyly. Identifying the above imaging features is of importance to plan management and provide supportive care that may be required.

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Lipoma is a common soft tissue tumour in the human body, but at the same time is very rare in the palm and rarer still in the thenar region. These lipomas in the hand can give rise to various problems such as cosmetic, functional, and neurological compromise among others and removing them becomes important when symptomatic. Diagnosing a hand pathology becomes important as a missed diagnosis can have long-term functional consequences for a patient. In the case report, we discuss a hand palmar prominence which presented as an effusion and later turned out to be a large lipoma. Further, we also present a literature review of published thenar lipoma cases to throw light on the nuances of this rare pathology location, which, to our knowledge, has not been done comprehensively.