Donald R Cantrell

Donald R Cantrell, MD, PhD is an Assistant Professor in Radiology (Interventional Neuroradiology) and Neurology (Stroke and Vascular Neurology) at Northwestern University's Feinberg School of Medicine. He is affiliated with the Institute for Artificial Intelligence in Medicine's Center for Computational Imaging and Signal Analytics, Northwestern University Clinical and Translational Sciences Institute (NUCATS), and provides clinical services at Northwestern Memorial Hospital and Shirley Ryan AbilityLab.

His academic training includes:

• PhD from Northwestern University (2009)
• MD from Northwestern University (2011)
• Transitional Internship at Saint Francis Hospital, Evanston (2012)
• Radiology Residency at Northwestern University McGaw Medical Center (2016)
• Diagnostic Neuroradiology Fellowship at Northwestern University McGaw Medical Center (2017)

Dr. Cantrell's research integrates interventional neuroradiology with advanced computational techniques, focusing on stroke thrombectomy optimization, health disparities in neurovascular care, and novel imaging methodologies. His work bridges clinical neurology, medical AI, and signal analytics to improve outcomes in vascular neurology through computational modeling and registry-based analytics.

Recent publications reveal a concentrated effort in applying machine learning to neurovascular interventions, with emphasis on predictive modeling for thrombectomy outcomes, racial disparity analysis in stroke treatment, 4D flow MRI hemodynamic assessment, and fluoroscopy-based procedural guidance systems. This research leverages large-scale clinical registries and advanced imaging modalities to address critical gaps in stroke care delivery and technical precision.

He actively contributes to the Center for Computational Imaging and Signal Analytics in Medicine, which develops AI-driven solutions for medical imaging interpretation and signal processing. The center's work focuses on translating computational innovations into clinical practice for enhanced diagnostic accuracy and procedural efficacy in neurointerventional radiology.