ArticleRadiologie (Heidelberg, Germany)2026
Susceptibility-weighted imaging in acute ischemic stroke: correlation of susceptibility and prominent vessel signs with clinical severity.
Article in Radiologie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeSusceptibility-weighted imaging (SWI) has emerged as a valuable tool in the evaluation of acute ischemic stroke. This study aimed to assess the correlation between the susceptibility vessel sign (SVS) and the National Institutes of Health Stroke Scale (NIHSS) scores, and as well as to explore the association between the grade of the prominent vessel sign (PVS) and clinical outcomes.
methodsThe study population comprised consecutive patients with ischemic stroke evaluated at our institution over a 6-month period. A total of 124 patients (82 with anterior and 42 with posterior circulation stroke) were evaluated for the presence of the SVS and for thrombus length on SWI. Patients with anterior circulation stroke were further classified according to the grade of PVS. Admission and discharge NIHSS scores were also recorded. Associations between SWI findings, NIHSS scores, and treatment modality were assessed using correlation and group comparison analyses.
resultsThe mean age of the patients was 71.5 ± 13.8 years (range: 23-100). Patients with SVS had significantly higher admission NIHSS scores (p = 0.041), and SVS was more frequently observed in those with prominent veins (p < 0.001). The PVS grade correlated with both admission and discharge NIHSS scores (p = 0.005 and p < 0.001, respectively). Patients with higher PVS grades showed less improvement in NIHSS scores. Endovascular treatment was associated with a significantly greater reduction in NIHSS scores in the overall study population (p = 0.019).
conclusionSusceptibility-weighted imaging provides essential information in acute ischemic stroke, with assessment of SVS presence and PVS grading serving as imaging biomarkers predicting clinical severity.
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