Advancing Stroke Imaging Through Tissue-Based Decision-Making: Rahul Chandra, MD

WATCH TIME: 5 minutes | Captions are auto-generated and may contain errors.

“There is this shift in paradigm in terms of how we’re thinking about stroke care. It’s no longer time-based; it’s more tissue-based. When you make that shift, you need to look at each case on its own merit in terms of how the CT perfusion looks and understand the limitations of the study itself.”

Stroke remains a leading cause of long-term disability and mortality worldwide, with imaging increasingly serving a central role in guiding acute treatment decisions and long-term management strategies. Advances in multimodal imaging have expanded clinicians’ ability to evaluate infarct core, salvageable tissue, collateral circulation, and underlying stroke etiology. In recent years, stroke care has continued to shift from a predominantly time-based treatment paradigm toward a more individualized, tissue-based approach that incorporates imaging findings alongside clinical presentation and physiologic factors.^1,2

Recent research has further highlighted the growing role of imaging-guided treatment selection in acute ischemic stroke. Emerging data suggest that CT perfusion and advanced imaging techniques may improve identification of patients eligible for reperfusion therapies. At the same time, investigators have emphasized the importance of understanding the technical limitations of perfusion imaging, including variability related to bolus timing, cardiac output, and software interpretation.³ Parallel advances in artificial intelligence (AI) are also being explored to improve image processing, automate stroke detection, and streamline triage across stroke systems of care.⁴

To better understand how these advances are influencing contemporary stroke management, NeurologyLive^® spoke with Rahul Chandra, MD, a vascular neurologist and the medical director for telestroke at Allegheny Health Network. In the conversation, Chandra highlighted the growing emphasis on tissue-based decision-making, the clinical value of CT perfusion and vessel wall imaging, and the importance of interpreting imaging findings within the broader clinical context. Furthermore, he also addressed the emerging role of AI-assisted imaging analysis in improving stroke triage, treatment selection, and resource utilization across health systems.

REFERENCES
1. Broocks G, Werner R, Sentker T, Minnerup J, Kemmling A. Current perspective in acute ischemic stroke: net water uptake and imaging-guided selection as bridges to personalized, tissue-based care. Front Neurol. 2026;16:1741898. Published 2026 Jan 22. doi:10.3389/fneur.2025.1741898
2. Al-Salahat A, Pirahanchi Y, Dhasakeerthi T, et al. Current state and advancements of imaging in acute ischemic stroke: a practical review. Neurol Sci. 2025;47(1):29. Published 2025 Dec 22. doi:10.1007/s10072-025-08685-8
3. Bobe RC, Coroiu RE, Cirstian AE, Cristescu CI, Pepelea DA, Manea RM. The Role of CT Perfusion in the Evaluation and Management of Acute Ischemic Stroke-A Systematic Review. Life (Basel). 2025;15(11):1693. Published 2025 Oct 31. doi:10.3390/life15111693
4. Mukhtar H, Ganjizadeh A, Misra A, et al. Imaging-Based Artificial Intelligence in Vascular and Interventional Radiology: A Narrative Review. J Imaging Inform Med. Published online January 5, 2026. doi:10.1007/s10278-025-01803-0