OCTA‐Derived Retinal Biomarkers and Infarct Topography Improve Etiologic Classification of Recent Single Subcortical Infarction: A Nomogram Model
Shuai Jiang, William Robert Kwapong, Yuying Yan, Tang Yang, Le Cao, Chen Ye, Junfeng Liu, Bo Wu

TL;DR
A new model combining retinal scans and brain imaging improves diagnosis of stroke causes in patients with recent subcortical infarction.
Contribution
A novel nomogram integrating OCTA retinal biomarkers and infarct topography improves etiological classification of RSSI.
Findings
The nomogram achieved a C-index of 0.84, outperforming conventional imaging (C-index 0.68).
Three key variables—superficial vascular complex density, lesion slices, and proximal lesion location—were critical for differentiation.
The model may support etiology-driven clinical decisions for RSSI patients.
Abstract
Recent single subcortical infarction (RSSI) in lenticulostriate artery territories exhibits etiological heterogeneity. Misclassification risks persist due to overlapping neuroimaging features between cerebral small‐vessel disease‐related lacunar infarction (CSVD‐related LI) and branch atheromatous disease (BAD). We developed a nomogram that integrates retinal optical coherence tomography angiography (OCTA) metrics with infarct topography to improve etiological classification. Patients with RSSI were prospectively enrolled between December 2021 and December 2023. LASSO regression identified predictors for a logistic regression–based nomogram. Performance was evaluated via concordance index (C‐index), calibration curves, and decision‐curve analysis. A total of 127 RSSI patients (86 CSVD‐related LI, 41 BAD) were included. Three variables—superficial vascular complex density, number of…
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Taxonomy
TopicsRetinal Imaging and Analysis · Retinal and Optic Conditions · Cerebrovascular and Carotid Artery Diseases
