Publications by authors named "K Minowa"
Purpose: To investigate the change in serum albumin levels and hepatic reserve scores before and after portal vein stent placement (PVS) for post-surgical portal vein stenosis.
Material And Methods: A retrospective cohort of patients undergoing PVS after abdominal surgery between 2007 and 2021 was analyzed. Patients' age, sex, and PVS technical success (defined by portal vein patency at final portography) were evaluated.
The aquaporin-4 (AQP4) water channel is essential in neurofluid dynamics. AQP4 loss impairs solute exchange between the cerebrospinal fluid (CSF) and interstitial fluid (ISF). However, whether AQP4 expression affects solute clearance from the CSF space to the extracranial space remains unclear.
View Article and Find Full Text PDFA 78-year-old man was aware of lightheadedness and darkness at a routine outpatient visit, and his blood pressure was declined at 87/51 mmHg. Contrast-enhanced CT scan showed an extravascular leakage image at jejunum. We diagnosed as small intestinal hemorrhage.
View Article and Find Full Text PDF[A Case of Neuroendocrine Carcinoma of the Extrahepatic Bile Duct].
Gan To Kagaku Ryoho
December 2023
Article Synopsis
- A 77-year-old man presented with nausea and chest discomfort, leading to the diagnosis of extrahepatic bile duct cancer through CT scans and cytology tests.
- After undergoing pancreatoduodenectomy, he was diagnosed with small cell neuroendocrine carcinoma at Stage IIIA, but did not receive adjuvant chemotherapy.
- Despite undergoing three lines of chemotherapy, the patient developed multiple liver metastases and died 1 year and 3 months post-surgery, highlighting the poor prognosis associated with this type of cancer.
Article Synopsis
- A convolutional neural network (CNN) model was developed to diagnose skull-base invasion by nasopharyngeal tumors using CT images and assessed for its diagnostic performance.
- The study involved 100 malignant nasopharyngeal tumor cases, split into training and test datasets, and aimed to improve diagnosis accuracy compared to expert radiologists.
- Results showed the CNN model achieved a diagnostic accuracy of 97.3%, outperforming two radiologists, and Grad-CAMs helped visualize the reasoning behind the model's predictions.