An automated screening model for aortic emergencies using convolutional neural networks and cropped computed tomography angiography images of the aorta.

Purpose: Patients with aortic emergencies, such as aortic dissection and rupture, are at risk of rapid deterioration, necessitating prompt diagnosis. This study introduces a novel automated screening model for computed tomography angiography (CTA) of patients with aortic emergencies, utilizing deep convolutional neural network (DCNN) algorithms.

Methods: Our model (Model A) initially predicted the positions of the aorta in the original axial CTA images and extracted the sections containing the aorta from these images.

Patient with penile metastasis from prostate cancer and survival over 5 years: A case report with longitudinal evaluation using computed tomography and magnetic resonance imaging.

Penile metastasis of malignant tumors is a very rare condition, often occurring as a part of systemic metastases, and is therefore associated with a poor prognosis. Although there have been reports of magnetic resonance imaging findings of penile metastasis, longitudinal imaging changes have not been presented previously. We report a case of a 80-year-old male patient with penile metastasis from prostate adenocarcinoma.

Chylothorax treated with targeted sclerotherapy by direct puncture of the lymphatic leakage site.

We report a novel application of targeted sclerotherapy to eradicate high-output chylothorax. The patient underwent thoracic duct embolization; however, cannulation of the thoracic duct failed, and thoracic duct disruption was performed. Leakage continued; therefore, the leakage site in the mediastinum was punctured directly under fluoroscopic guidance and a drainage catheter was inserted, followed by sclerotherapy using OK-432.