Quantitative DSA Analysis of MCA Aneurysms Using SymDIRECT Pixel Clustering: A Novel Framework for Objective Post-Treatment Evaluation.

Background: Digital subtraction angiography (DSA) remains the gold standard for assessing aneurysm morphology before and after treatment. While visual interpretation is common, quantitative image analysis remains underutilized in clinical practice. This study aimed to evaluate postoperative vascular changes in patients with middle cerebral artery (MCA) aneurysms using SymDIRECT-based pixel clustering on preoperative and postoperative DSA images. Methods: A total of 59 patients with unruptured MCA aneurysms were analyzed retrospectively. SymDIRECT clustering segmented angiographic images into four intensity clusters. Quantitative comparison of cluster pixel counts between pre- and postoperative images was performed. Results: Both neurosurgical clipping and endovascular treatment groups demonstrated significant reductions in medium- and high-intensity pixel clusters postoperatively, reflecting successful aneurysm occlusion. The background cluster increased post-treatment in most cases, with an average rise of over 14%, indicating effective anatomical exclusion of the aneurysm. Conclusions: SymDIRECT-based pixel clustering enables objective, pixel-level quantification of treatment response in DSA images. This approach may support standardized imaging follow-up protocols and improve reproducibility in neurovascular outcome assessment. Future integration with AI-based segmentation could facilitate real-time image interpretation.