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AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticleArtificial Intelligence

Data-Driven Prognostication in Distal Medium Vessel Occlusions Using Explainable Machine Learning

Mert Karabacak, Burak Berksu Ozkara, Tobias D. Faizy, Trevor Hardigan, Jeremy J. Heit, Dhairya A. Lakhani, Konstantinos Margetis, J. Mocco, Kambiz Nael, Max Wintermark and Vivek S. Yedavalli
American Journal of Neuroradiology April 2025, 46 (4) 725-732; DOI: https://doi.org/10.3174/ajnr.A8547
Mert Karabacak
aFrom the Departments of Neurosurgery (M.K., T.H., K.M., J.M.), Mount Sinai Health System, New York, New York
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  • ORCID record for Mert Karabacak
Burak Berksu Ozkara
bDepartment of Radiology (B.B.O.), Mount Sinai Health System, New York, New York
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  • ORCID record for Burak Berksu Ozkara
Tobias D. Faizy
cNeuroendovascular Division (T.D.F.), Department of Radiology, University Medical Center Münster, Münster, Germany
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Trevor Hardigan
aFrom the Departments of Neurosurgery (M.K., T.H., K.M., J.M.), Mount Sinai Health System, New York, New York
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Jeremy J. Heit
dDepartments of Radiology and Neurosurgery (J.J.H.), Stanford Medicine, Palo Alto, California
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Dhairya A. Lakhani
eRussell H. Morgan Department of Radiology and Radiological Sciences (D.A.L., V.S.Y.), Johns Hopkins Medicine, Baltimore, Maryland
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Konstantinos Margetis
aFrom the Departments of Neurosurgery (M.K., T.H., K.M., J.M.), Mount Sinai Health System, New York, New York
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J. Mocco
aFrom the Departments of Neurosurgery (M.K., T.H., K.M., J.M.), Mount Sinai Health System, New York, New York
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Kambiz Nael
fRadiological Sciences (K.N.), University of California, San Francisco, San Francisco, California, California
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Max Wintermark
gDepartment of Neuroradiology (M.W.), The University of Texas MD Anderson Center, Houston, Texas
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Vivek S. Yedavalli
eRussell H. Morgan Department of Radiology and Radiological Sciences (D.A.L., V.S.Y.), Johns Hopkins Medicine, Baltimore, Maryland
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Abstract

BACKGROUND AND PURPOSE: Distal medium vessel occlusions (DMVOs) are estimated to cause acute ischemic stroke in 25%–40% of cases. Prognostic models can inform patient counseling and research by enabling outcome predictions. However, models designed specifically for DMVOs are lacking.

MATERIALS AND METHODS: This retrospective study developed a machine learning model to predict 90-day unfavorable outcome (defined as an mRS score of 3–6) in 164 patients with primary DMVO. A model developed with the TabPFN algorithm used selected clinical, laboratory, imaging, and treatment data with the least absolute shrinkage and selection operator feature selection. Performance was evaluated via 5-repeat 5-fold cross-validation. Model discrimination and calibration were evaluated. SHapley Additive Explanations (SHAP) identified influential features. A Web application deployed the model for individualized predictions.

RESULTS: The model achieved an area under the receiver operating characteristic curve of 0.815 (95% CI, 0.79–0.841) for predicting unfavorable outcome, demonstrating good discrimination, and a Brier score of 0.19 (95% CI, 0.177–0.202), demonstrating good calibration. SHAP analysis ranked admission NIHSS score, premorbid mRS, type of thrombectomy, modified TICI score, and history of malignancy as top predictors. The Web application enables individualized prognostication.

CONCLUSIONS: Our machine learning model demonstrated good discrimination and calibration for predicting 90-day unfavorable outcomes in primary DMVO strokes. This study demonstrates the potential for personalized prognostic counseling and research to support precision medicine in stroke care and recovery.

ABBREVIATIONS:

AIS
acute ischemic stroke
AUPRC
area under the PRC
AUROC
area under the ROC curve
DMVO
distal medium vessel occlusion
ER
emergency department
IVT
IV thrombolysis
kNN
k-nearest neighbor
LASSO
least absolute shrinkage and selection operator
mTICI
modified TICI
PDP
partial dependence plot
PRC
precision-recall curve
ROC
receiver operating characteristic
SHAP
SHapley Additive ExPlanations
ST
stroke thrombectomy
  • © 2025 by American Journal of Neuroradiology
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American Journal of Neuroradiology: 46 (4)
American Journal of Neuroradiology
Vol. 46, Issue 4
1 Apr 2025
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Cite this article
Mert Karabacak, Burak Berksu Ozkara, Tobias D. Faizy, Trevor Hardigan, Jeremy J. Heit, Dhairya A. Lakhani, Konstantinos Margetis, J. Mocco, Kambiz Nael, Max Wintermark, Vivek S. Yedavalli
Data-Driven Prognostication in Distal Medium Vessel Occlusions Using Explainable Machine Learning
American Journal of Neuroradiology Apr 2025, 46 (4) 725-732; DOI: 10.3174/ajnr.A8547

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Machine Learning for Medium Vessel Occlusions
Mert Karabacak, Burak Berksu Ozkara, Tobias D. Faizy, Trevor Hardigan, Jeremy J. Heit, Dhairya A. Lakhani, Konstantinos Margetis, J. Mocco, Kambiz Nael, Max Wintermark, Vivek S. Yedavalli
American Journal of Neuroradiology Apr 2025, 46 (4) 725-732; DOI: 10.3174/ajnr.A8547
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