Regional Cerebral Small Vessel Disease (rCSVD) Score: A clinical MRI grading system validated in a stroke cohort

Autor: Saman Hazany, Kim-Lien Nguyen, Martin Lee, Andrew Zhang, Parsa Mokhtar, Alexander Crossley, Sakshi Luthra, Pooja Butani, Sunita Dergalust, Benjamin Ellingson, Jason D. Hinman
Rok vydání: 2022
Předmět:
Zdroj: Journal of Clinical Neuroscience. 105:131-136
ISSN: 0967-5868
DOI: 10.1016/j.jocn.2022.09.014
Popis: Current methods for quantitative assessment of cerebral small vessel disease (CSVD) ignore critical aspects of the disease, namely lesion type and regionality. We developed and tested a new scoring system for CSVD, "regional Cerebral Small Vessel Disease" (rCSVD) based on regional assessment of magnetic resonance imaging (MRI) features.141 patients were retrospectively included with a derivation cohort of 46 consecutive brain MRI exams and a validation cohort of 95 patients with known cerebrovascular disease. We compared the predictive value of rCSVD against existing scoring methods. We determined the predictive value of rCSVD score for all-cause mortality and recurrent strokes.46 (44 male) veteran patients (age: 66-93 years), were included for derivation of the rCSVD score. A non-overlapping validation cohort consisted of 95 patients (89 male; age: 34-91 years) with known cerebrovascular disease were enrolled. Based on ROC analysis with comparison of AUC (Area Under the Curve), "rCSVD" score performed better compared to "total SVD score" and Fazekas score for predicting all-cause mortality (0.75 vs 0.68 vs 0.69; p = 0.046). "rCSVD" and total SVD scores were predictive of recurrent strokes in our validation cohort (p-values 0.004 and 0.001). At a median of 5.1 years (range 2-17 years) follow-up, Kaplan-Meier survival analysis demonstrated an rCSVD score of 2 to be a significant predictor of all-cause-mortality."rCSVD" score can be derived from routine brain MRI, has value in risk stratification of patients at risk of CSVD, and has potential in clinical trials once fully validated in a larger patient cohort.
Databáze: OpenAIRE
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