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Comprehensive Endovascular and Open Surgical Management of Cerebral Arteriovenous Malformations
Published on: October 20, 2017
Regimens and Response Assessment in Minimally Invasive Image-Guided Therapies for Vascular Malformations: Insights
Gesa Doreen Savic1, Giovanni F Torsello2, Anne Frisch1
1Department of Radiology, Campus Virchow-Klinikum, Charité-Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
Abstract:
This retrospective study was aimed at characterizing vascular malformations (VMFs) presenting for minimally invasive image-guided therapies (MIT) at a tertiary-care center and evaluating treatment regimens and image-based outcomes using MRI. We analyzed demographic, disease-related, and radiologic features of VMFs presenting to interventional radiology between May 2008 and August 2020 using compendium vascular anomaly (Compva) criteria. MIT and specific agents were evaluated, and treatment effects were assessed through volumetry and mean signal intensity (MSI) on multiparametric longitudinal MRI. The statistics included the paired t-test, ANOVA, and Fisher's exact test. The cohort included 217 patients (mean age 30 ± 18.4 years; 134 female). Venous malformations were most common (47%). VMFs were frequently located in the head-neck region (23.5%), legs (23.04%), and arms (13.8%). Among 112 treatments, sclerotherapy was performed most frequently (63.9%), followed by embolization (19.3%). MRI showed a significant reduction in T2 MSI for venous (1107.95 vs. 465.26; p = 0.028) and decreased contrast media uptake for lymphatic malformations (557.33 vs. 285.33; p = 0.029) after sclerotherapy, while the lesion volumes did not change significantly (p = 0.8). These findings propose MRI-derived MSI as a potential non-invasive biomarker for assessing the response of VMF to MIT. By leveraging MRI, this study addresses challenges in managing rare diseases like VMFs, while advocating for standardized approaches and prospective studies to better link imaging findings with clinical outcomes.
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