Abstract Details

Title The Metabolic-atherogenic Signature Index (MASI): Predicting Vascular Distribution and Stenosis Burden in Large Vessel Stroke

Topic Cerebrovascular Disease and Interventional Neurology

Presentation(s) P4 - Poster Session 4 (8:00 AM-9:00 AM)

Poster/Presentation
Number 5-010

Objective

To evaluate whether optimized composite indices (MASI-Z, MASI-PCA) integrating serum homocysteine, LDL, and inverse vitamin B12 predict stenosis severity, vascular distribution, and clinical severity in acute large vessel stroke.

Background

Systemic metabolic stressors like Hyperhomocysteinemia, Dyslipidemia, and low B12 synergistically amplify endothelial injury and plaque instability. However, their integrated morphological signature on cerebrovascular CTA remains uncharacterized. MASI provides a unified biochemical framework linking metabolic dysregulation with angiographic burden and topographic distribution of large vessel disease.

Design/Methods In a CTA-based analysis (n = 99), angiographic text data were numerically mapped to stenosis percentages (occlusion = 100%, >70% = 85%, 50-70% = 60%, <50% = 25%, plaque = 10%, none = 0). Primary outcomes included high-grade stenosis (270%), higher NIHSS (5-10 vs <5), and carotid vs vertebrobasilar distribution. Composite indices were MASI-Z = z(Hcy)+z(LDL)+z(1/B12) and MASI-PCA (first principal component; positive loadings). Associations were analyzed using ROC/ AUC, Welch t-tests, x², and Spearman correlations.

Results Mean ± SD biomarkers: homocysteine 38.7 ± 20.9 µmol/L, B12 356.9 ± 221.9 pg/mL, LDL 112.5 ± 31.8 mg/dL. High grade stenosis 20/99. AUCs (=70% stenosis): LDL 0.666, MASI-Z 0.618, MASI-PCA 0.602. AUCs (higher NIHSS): LDL 0.678, MASI-Z 0.591, MASI-PCA 0.585. Spearman p with stenosis%: LDL 0.419 (p < 0.0001), MASI-Z 0.316 (p = 0.0015). Carotid involvement rose across MASI-Z quartiles (10.6 ? 33.0%; x² p = 0.0039).

Conclusions While LDL remains the strongest single discriminator of stenosis and stroke severity, standardized MASI composites enhance the metabolic-angiographic correlation, reflecting global stenosis burden and carotid predominance. These indices bridge systemic metabolism with vascular architecture, enabling early, precision risk stratification and representing a scalable step toward metabolic imaging biomarkers in cerebrovascular disease.

Authors/Disclosures
Sudheendra Lakshman Chintha, MD PRESENTER	Dr. CHINTHA has nothing to disclose.
PRAVIN NAPHADE	PRAVIN NAPHADE has nothing to disclose.
Srivatsav Addepalli, MD	Dr. Addepalli has nothing to disclose.
Chintha V. Sriram, MD, MBBS (IPGMER)	Dr. Sriram has nothing to disclose.

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