pH-sensitive probes for ischemic stroke: advancing early detection and accurate grading
Z Chena b c, Lijun Wanga, Y Q Wua b c, Pengfei Yanga b, Xianfu Mengd e, J W Liua b, Hongjian Zhanga b
- aNeurovascular Center, Changhai Hospital, Naval Medical University
- bOriental Pan-Vascular Devices Innovation College, University of Shanghai for Science and Technology
- cSchool of Health Science and Engineering, University of Shanghai for Science and Technology
- dDepartment of Materials Science and State Key Laboratory of Molecular Engineering of Polymers, Academy for Engineering and Technology, Fudan University
- eDepartment of Nuclear Medicine, Changhai Hospital, Shanghai Key Laboratory of Nautical Medicine and Translation of Drugs and Medical Devices, Navy Medical University
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Abstract
Early detection and accurate assessment of ischemic stroke (IS) are essential for timely treatment and prognosis evaluation. Conventional bedside and imaging-based approaches, including the National Institutes of Health Stroke Scale (NIHSS), computed tomography (CT), and magnetic resonance imaging (MRI), remain central to acute stroke assessment, but they have important limitations in the hyperacute stage, when neurological deficits may be subtle and structural imaging changes may not yet be fully apparent. Among the metabolic alterations triggered by ischemia, tissue acidosis is particularly informative because pH declines rapidly after cerebral hypoperfusion and may reveal ischemic injury before conventional imaging abnormalities become obvious. In this review, we summarize recent advances in pH-based detection of IS, with emphasis on its potential for early diagnosis and physiologically informed stroke grading. We discuss current clinical and imaging assessment methods, the pathophysiological basis of ischemia-associated acidosis, emerging pH-detection technologies, and the major barriers to clinical translation. Finally, we outline a future perspective in which pH-related information is integrated with perfusion imaging, complementary biomarkers, and artificial intelligence to support a more comprehensive framework for ischemic stroke assessment.