Background: Several factors are frequently considered for outcome prediction rin stroke patients. We assessed the value of digital subtraction angiography (DSA)-based brain perfusion measurements after mechanical thrombectomy (MT) for outcome prediction in acute ischaemic stroke.
Methods: From DSA image data (n = 90; 38 females; age 73.
Objective: We examined the impact of the rs10191329 genetic risk variant on neuroaxonal damage as measured by serum neurofilament light chain (sNfL) levels, and disability progression in people with multiple sclerosis (pwMS).
Methods: In a cohort of pwMS (n = 740), 658 participants were prospectively monitored every 2 years for less than a decade while 82 of 740 pwMS were monitored retrospectively for up to 40 years. We investigated associations between rs10191329 variants and clinical outcome, including Expanded Disability Status Scale (EDSS), disability accrual (defined by EDSS-increase of at least 1.
Purpose: To examine the impact of deep learning-augmented contrast enhancement on image quality and diagnostic accuracy of poorly contrasted CT angiography in patients with suspected stroke.
Methods: This retrospective single-centre study included 102 consecutive patients who underwent CT imaging for suspected stroke between 01/2021 and 12/2022, including whole brain volume perfusion CT (VPCT) and, specifically, a poorly contrasted CT angiography (defined as < 350HU in the proximal MCA). CT angiography imaging data was reconstructed using i.