<![CDATA[Background: Stroke is a leading cause of mortality and disability worldwide, with time-to-diagnosis being a critical determinant of functional outcomes. In remote and rural areas, access to neuroimaging expertise is severely limited, creating a significant care disparity. Teleradiology—the electronic transmission of radiological images to remote specialists for interpretation—has emerged as a promising solution to bridge this diagnostic gap. However, the aggregate evidence regarding its diagnostic accuracy and impact on diagnosis speed in remote settings has not been comprehensively synthesized. Methods: The study strictly adhered to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines. Studies reporting on teleradiology use for stroke imaging in remote or rural settings were eligible. Risk of bias was assessed using the Cochrane RoB 2.0 tool for RCTs and the Newcastle-Ottawa Scale (NOS) for observational studies. Primary outcomes included diagnostic accuracy metrics (sensitivity, specificity, kappa agreement) and time-to-treatment metrics. Results: Seventeen studies encompassing 89,412 patients met the inclusion criteria. Teleradiology demonstrated consistently high diagnostic accuracy for intracranial hemorrhage (sensitivity 91–100%, specificity 89–100%, kappa 0.69–1.0). Telestroke-equipped hospitals achieved significantly faster door-to-imaging times (median reduction 15–147 minutes) and door-to-needle times (median reduction 3.7–77 minutes/year). Thrombolysis rates increased from 2.6% to 15.5% over 10-year network maturation. Functional outcomes (mRS 0-2) improved by 19% and 30-day mortality decreased by 0.5 percentage points in telestroke-capable hospitals. Multimodal CT with teleradiology interpretation added 19.5 percentage points in ischemic stroke detection sensitivity. Discussion: The synthesis of evidence confirms that teleradiology systems maintain diagnostic accuracy equivalent to on-site neuroradiology services while substantially reducing time-to-diagnosis in remote settings. Hub-and-spoke network models demonstrate the greatest sustained impact, with telemedical stroke networks showing progressive improvement in both process and clinical outcome metrics over time. Challenges persist regarding initial implementation, connectivity infrastructure, and healthcare workforce training in low-resource environments. Conclusion: Teleradiology significantly accelerates stroke diagnosis in remote areas without compromising diagnostic accuracy. The implementation of teleradiology-enabled telestroke networks is strongly supported by the evidence and should be prioritized in healthcare policy for underserved populations.]]>
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