Objective: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.
Methods: Our retrospective study incorporated 34 patients diagnosed with biliary and pancreatic disorders. We obtained MRCP images using a single breath-hold MRCP on a 3T MRI system.
Objective: Discriminating between hemorrhage and iodine extravasation can pose challenges in conventional computed tomography (CCT) images following preoperative embolization for meningioma. This study aimed to assess the efficacy of dual-energy computed tomography (DECT) in differentiating hemorrhage from iodine extravasation after preoperative embolization for meningioma.
Methods: Twenty-one consecutive meningioma patients who underwent CCT before and DECT immediately after preoperative embolization were included in this study.
Antisense oligonucleotides (ASOs) are an important class of therapeutics to treat genetic diseases, and expansion of this modality to neurodegenerative disorders has been an active area of research. To realize chronic administration of ASO therapeutics to treat neurodegenerative diseases, new chemical modifications that improve activity and safety profiles are still needed. Furthermore, it is highly desirable to develop a single stereopure ASO with a defined activity and safety profile to avoid any efficacy and safety concerns due to the batch-to-batch variation in the composition of diastereomers.
View Article and Find Full Text PDFPurpose: To evaluate the impact of prior teriparatide (TPTD) treatment on the effectiveness of romosozumab (ROMO) in postmenopausal osteoporosis.
Methods: In this retrospective, case-controlled, multicenter study, 323 postmenopausal patients were initiated ROMO. Of these, 275 were treatment-naïve, and 48 were switched from TPTD, with uninterrupted ROMO treatment for 12 months.
Purposes: This study aimed to assess the effectiveness of Super-Resolution Deep Learning Reconstruction (SR-DLR) -a deep learning-based technique that enhances image resolution and quality during MRI reconstruction- in improving the image quality of thin-slice 3D T2-weighted imaging (T2WI) and Prostate Imaging-Reporting and Data System (PI-RADS) assessment in prostate Magnetic Resonance Imaging (MRI).
Methods: This retrospective study included 33 patients who underwent prostate MRI with SR-DLR between November 2022 and April 2023. Thin-slice 3D-T2WI of the prostate was obtained and reconstructed with and without SR-DLR (matrix: 720 × 720 and 240 × 240, respectively).