Objectives: In the context of growing safety concerns regarding the use of gadolinium-based contrast agents in contrast-enhanced MRI, there is a need for dose reduction without compromising diagnostic accuracy. A deep learning (DL) method is proposed and evaluated in this study for predicting full-dose contrast-enhanced T1w images from multiparametric MRI acquired with 20% of the standard dose of gadolinium-based contrast agents.
Materials And Methods: This multicentric prospective study leveraged multiparametric brain MRIs acquired between March and July 2024.
Spinal cord watershed infarction is a rare phenomenon due to the rich collateral blood supply to the organ. It often occurs in elderly patients with preexisting atherosclerotic disease in the setting of global hypoperfusion, such as thoracoabdominal surgery, dissection, coagulopathies, or idiopathic. We present a case of spinal cord infarction (SCI) in both longitudinal and transverse watershed areas as a complication of postoperative blood loss.
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